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Alliant Taxonomy

Segment:

Category:

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Vertical 1:

Vertical 2:

HH/Ind:

Segment	Category	Sub-Category	Vertical 1	Vertical 2	HH/Ind	Modeled/Known/Inferred	Audience Size (Deterministic)	Estimated Audience Size (Digital)	Segment Description
Diesel	Auto	Fuel Type	Auto		Household	Known	1,61	3,37	Households that own a vehicle with a diesel engine, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Electric	Auto	Fuel Type	Auto		Household	Known	84,16	176,74	Households that own an electric vehicle, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Flex-Fuel	Auto	Fuel Type	Auto		Household	Known	5,39	11,31	Households that own a vehicle with a flex-fuel engine, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Hybrid	Auto	Fuel Type	Auto		Household	Known	1,26	2,65	Households that own a hybrid vehicle, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Clunker Owner In-Market for New Car	Auto	In-Market	Auto		Household	Modeled	3,64	7,64	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for Financing	Auto	In-Market	Auto	Financial Services	Household	Modeled	17,11	35,94	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for Insurance	Auto	In-Market	Auto	Financial Services	Household	Modeled	24,22	50,86	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Economy Car	Auto	In-Market	Auto		Household	Modeled	16,94	35,58	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Green Car	Auto	In-Market	Auto		Household	Modeled	15,13	31,78	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Large SUV	Auto	In-Market	Auto		Household	Modeled	9,57	20,09	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously purchased large SUVs.
In-Market for New Luxury Car	Auto	In-Market	Auto		Household	Modeled	16,20	34,02	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Mini Van	Auto	In-Market	Auto		Household	Modeled	13,93	29,25	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Sedan	Auto	In-Market	Auto		Household	Modeled	13,26	27,85	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Small SUV	Auto	In-Market	Auto		Household	Modeled	14,21	29,85	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously purchased small SUVs.
In-Market for New Sports car	Auto	In-Market	Auto		Household	Modeled	519,51	1,09	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New SUV	Auto	In-Market	Auto		Household	Modeled	13,48	28,32	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Truck	Auto	In-Market	Auto		Household	Modeled	17,43	36,60	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Vehicle	Auto	In-Market	Auto		Household	Modeled	19,45	40,83	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for New Wagon	Auto	In-Market	Auto		Household	Modeled	17,50	36,74	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for Parts & Service	Auto	In-Market	Auto		Household	Modeled	33,64	70,65	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
In-Market for Used Vehicle	Auto	In-Market	Auto		Household	Modeled	74,65	156,76	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
Multi-Car Owner In-Market for New Car	Auto	In-Market	Auto		Household	Modeled	21,55	45,25	Built from automotive ownership data that is sourced from nationwide dealership and service department records. The source data is used as a study group, that is then joined to an offline cooperative of multichannel transactions (via digital and offline channels from DTC businesses) , demographics and life stage data (recent home move, new parents, retired, etc.) to identify households who have the same indicators of those who have previously made vehicle purchases.
Acura Switchers	Auto	Loyalty	Auto		Household	Inferred	1,78	3,73	Households that Alliant has identified to be a defector from Acura, meaning they have owned an Acura but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Audi Switchers	Auto	Loyalty	Auto		Household	Inferred	1,01	2,12	Households that Alliant has identified to be a defector from Audi, meaning they have owned a Audi but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Auto Class Switchers	Auto	Loyalty	Auto		Household	Inferred	18,65	39,16	Households that Alliant has identified to be a defector from auto classes, meaning they do not have a repeat history of purchasing a specific vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Auto Make Switchers	Auto	Loyalty	Auto		Household	Inferred	60,27	126,57	Households that Alliant has identified to be a defector from auto makes, meaning they do not have a repeat history of purchasing a specific vehicle make. Identified by known historic auto ownership data through nationwide dealership and service department records.
Auto Style Loyalists	Auto	Loyalty	Auto		Household	Inferred	29,01	60,92	Households that Alliant has identified to be loyal in their continued purchase of an auto style. Identified by known historic auto ownership data through nationwide dealership and service department records.
Auto Style Switchers	Auto	Loyalty	Auto		Household	Inferred	17,07	35,85	Households that Alliant has identified to be a defector from auto style, meaning they do not have a repeat history of purchasing that vehicle style. Identified by known historic auto ownership data through nationwide dealership and service department records.
BMW Loyalists	Auto	Loyalty	Auto		Household	Inferred	297,77	625,33	Households that Alliant has identified to be loyal in their continued purchase of a BMW. Identified by known historic auto ownership data through nationwide dealership and service department records.
BMW Switchers	Auto	Loyalty	Auto		Household	Inferred	2,21	4,65	Households that Alliant has identified to be a defector from BMW, meaning they have owned a BMW but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Cadillac Loyalists	Auto	Loyalty	Auto		Household	Inferred	219,84	461,66	Households that Alliant has identified to be loyal in their continued purchase of a Cadillac. Identified by known historic auto ownership data through nationwide dealership and service department records.
Cadillac Switchers	Auto	Loyalty	Auto		Household	Inferred	2,18	4,58	Households that Alliant has identified to be a defector from Cadillac, meaning they have owned a Cadillac but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Chevrolet Loyalists	Auto	Loyalty	Auto		Household	Inferred	4,01	8,43	Households that Alliant has identified to be loyal in their continued purchase of a Chevrolet. Identified by known historic auto ownership data through nationwide dealership and service department records.
Chevrolet Switchers	Auto	Loyalty	Auto		Household	Inferred	14,73	30,94	Households that Alliant has identified to be a defector from Chevrolet, meaning they have owned a Chevrolet but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Convertible Switchers	Auto	Loyalty	Auto		Household	Inferred	1,51	3,17	Households that Alliant has identified to be a defector from convertibles, meaning they have owned a convertible but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Coupe 2-door Loyalists	Auto	Loyalty	Auto		Household	Inferred	772,28	1,62	Households that Alliant has identified to be loyal in their continued purchase of a coupe 2-door. Identified by known historic auto ownership data through nationwide dealership and service department records.
Coupe 2-door Switchers	Auto	Loyalty	Auto		Household	Inferred	4,36	9,16	Households that Alliant has identified to be a defector from coupe 2-doors, meaning they have owned a coupe 2-door but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Crossover Loyalists	Auto	Loyalty	Auto		Household	Inferred	954,73	2,00	Households that Alliant has identified to be loyal in their continued purchase of a crossover. Identified by known historic auto ownership data through nationwide dealership and service department records.
Dodge Loyalists	Auto	Loyalty	Auto		Household	Inferred	1,06	2,23	Households that Alliant has identified to be loyal in their continued purchase of a Dodge. Identified by known historic auto ownership data through nationwide dealership and service department records.
Dodge Switchers	Auto	Loyalty	Auto		Household	Inferred	8,63	18,13	Households that Alliant has identified to be a defector from Dodge, meaning they have owned a Dodge but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Ford Loyalists	Auto	Loyalty	Auto		Household	Inferred	4,42	9,28	Households that Alliant has identified to be loyal in their continued purchase of a Ford. Identified by known historic auto ownership data through nationwide dealership and service department records.
Ford Switchers	Auto	Loyalty	Auto		Household	Inferred	15,69	32,96	Households that Alliant has identified to be a defector from Ford, meaning they have owned a Ford but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size Car Loyalists	Auto	Loyalty	Auto		Household	Inferred	2,35	4,93	Households that Alliant has identified to be loyal in their continued purchase of a full size car. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size Car Switchers	Auto	Loyalty	Auto		Household	Inferred	6,76	14,20	Households that Alliant has identified to be a defector from full size Cars, meaning they have owned a full size car but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size SUV Loyalists	Auto	Loyalty	Auto		Household	Inferred	4,42	9,28	Households that Alliant has identified to be loyal in their continued purchase of a full size SUV. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size SUV Switchers	Auto	Loyalty	Auto		Household	Inferred	9,12	19,16	Households that Alliant has identified to be a defector from full size SUV, meaning they have owned a full size SUV but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size Truck Loyalists	Auto	Loyalty	Auto		Household	Inferred	6,43	13,50	Households that Alliant has identified to be loyal in their continued purchase of a full size truck. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size Truck Switchers	Auto	Loyalty	Auto		Household	Inferred	9,92	20,83	Households that Alliant has identified to be a defector from full size truck, meaning they have owned a full size truck but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Full Size Van Switchers	Auto	Loyalty	Auto		Household	Inferred	592,52	1,24	Households that Alliant has identified to be a defector from full size van, meaning they have owned a full size van but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
GMC Loyalists	Auto	Loyalty	Auto		Household	Inferred	378,69	795,25	Households that Alliant has identified to be loyal in their continued purchase of a GMC. Identified by known historic auto ownership data through nationwide dealership and service department records.
GMC Switchers	Auto	Loyalty	Auto		Household	Inferred	4,23	8,88	Households that Alliant has identified to be a defector from GMC, meaning they have owned a GMC but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Hatchback Loyalists	Auto	Loyalty	Auto		Household	Inferred	626,89	1,32	Households that Alliant has identified to be loyal in their continued purchase of a hatchback. Identified by known historic auto ownership data through nationwide dealership and service department records.
Honda Loyalists	Auto	Loyalty	Auto		Household	Inferred	1,58	3,32	Households that Alliant has identified to be loyal in their continued purchase of a Honda. Identified by known historic auto ownership data through nationwide dealership and service department records.
Honda Switchers	Auto	Loyalty	Auto		Household	Inferred	9,47	19,89	Households that Alliant has identified to be a defector from Honda, meaning they have owned a Honda but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Hyundai Loyalists	Auto	Loyalty	Auto		Household	Inferred	485,28	1,02	Households that Alliant has identified to be loyal in their continued purchase of a Hyundai. Identified by known historic auto ownership data through nationwide dealership and service department records.
Hyundai Switchers	Auto	Loyalty	Auto		Household	Inferred	4,38	9,20	Households that Alliant has identified to be a defector from Hyundai, meaning they have owned a Hyundai but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Infiniti Switchers	Auto	Loyalty	Auto		Household	Inferred	1,06	2,22	Households that Alliant has identified to be a defector from Infiniti, meaning they have owned a Infiniti but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Jeep Loyalists	Auto	Loyalty	Auto		Household	Inferred	446,67	938,02	Households that Alliant has identified to be loyal in their continued purchase of a Jeep. Identified by known historic auto ownership data through nationwide dealership and service department records.
Jeep Switchers	Auto	Loyalty	Auto		Household	Inferred	5,09	10,68	Households that Alliant has identified to be a defector from Jeep, meaning they have owned a Jeep but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Kia Loyalists	Auto	Loyalty	Auto		Household	Inferred	286,23	601,08	Households that Alliant has identified to be loyal in their continued purchase of a Kia. Identified by known historic auto ownership data through nationwide dealership and service department records.
Kia Switchers	Auto	Loyalty	Auto		Household	Inferred	3,25	6,82	Households that Alliant has identified to be a defector from Kia, meaning they have owned a Kia but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Land Rover Switchers	Auto	Loyalty	Auto		Household	Inferred	310,49	652,04	Households that Alliant has identified to be a defector from Land Rover, meaning they have owned a Land Rover but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Lexus Loyalists	Auto	Loyalty	Auto		Household	Inferred	338,16	710,13	Households that Alliant has identified to be loyal in their continued purchase of a Lexus. Identified by known historic auto ownership data through nationwide dealership and service department records.
Lexus Switchers	Auto	Loyalty	Auto		Household	Inferred	1,40	2,94	Households that Alliant has identified to be a defector from Lexus, meaning they have owned a Lexus but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Lincoln Switchers	Auto	Loyalty	Auto		Household	Inferred	917,13	1,93	Households that Alliant has identified to be a defector from Lincoln, meaning they have owned a Lincoln but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Luxury Car Switchers	Auto	Loyalty	Auto		Household	Inferred	150,24	315,50	Households that Alliant has identified to be a defector from luxury cars, meaning they have owned a luxury car but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mazda Switchers	Auto	Loyalty	Auto		Household	Inferred	1,70	3,57	Households that Alliant has identified to be a defector from Mazda, meaning they have owned a Mazda but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mercedes-Benz Loyalists	Auto	Loyalty	Auto		Household	Inferred	288,67	606,20	Households that Alliant has identified to be loyal in their continued purchase of a Mercedes-Benz. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mercedes-Benz Switchers	Auto	Loyalty	Auto		Household	Inferred	1,21	2,55	Households that Alliant has identified to be a defector from Mercedes-Benz, meaning they have owned a Mercedes-Benz but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mid Size Car Loyalists	Auto	Loyalty	Auto		Household	Inferred	5,87	12,33	Households that Alliant has identified to be loyal in their continued purchase of a mid-size car. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mid Size SUV Switchers	Auto	Loyalty	Auto		Household	Inferred	465,56	977,67	Households that Alliant has identified to be a defector from midsize SUVs, meaning they have owned a mid-size SUV but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mid-Size Car Switchers	Auto	Loyalty	Auto		Household	Inferred	6,94	14,57	Households that Alliant has identified to be a defector from mid-size cars, meaning they have owned a mid-size car but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mid-Size Truck Switchers	Auto	Loyalty	Auto		Household	Inferred	1,14	2,40	Households that Alliant has identified to be a defector from mid-size trucks, meaning they have owned a mid-sized truck but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mini Van Loyalists	Auto	Loyalty	Auto		Household	Inferred	1,82	3,82	Households that Alliant has identified to be loyal in their continued purchase of a mini van. Identified by known historic auto ownership data through nationwide dealership and service department records.
Mini Van Switchers	Auto	Loyalty	Auto		Household	Inferred	3,52	7,39	Households that Alliant has identified to be a defector from mini vans, meaning they have owned a mini van but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Nissan Loyalists	Auto	Loyalty	Auto		Household	Inferred	858,32	1,80	Households that Alliant has identified to be loyal in their continued purchase of a Nissan. Identified by known historic auto ownership data through nationwide dealership and service department records.
Nissan Switchers	Auto	Loyalty	Auto		Household	Inferred	4,39	9,21	Households that Alliant has identified to be a defector from Nissan, meaning they have owned a Nissan but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Pickup Truck Loyalist	Auto	Loyalty	Auto		Household	Inferred	8,08	16,97	Households that Alliant has identified to be loyal in their continued purchase of a pickup truck. Identified by known historic auto ownership data through nationwide dealership and service department records.
Pickup Truck Switchers	Auto	Loyalty	Auto		Household	Inferred	7,64	16,04	Households that Alliant has identified to be a defector from pickup trucks, meaning they have owned a pickup truck but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Sedan Loyalists	Auto	Loyalty	Auto		Household	Inferred	14,06	29,52	Households that Alliant has identified to be loyal in their continued purchase of a sedan. Identified by known historic auto ownership data through nationwide dealership and service department records.
Sedan Switchers	Auto	Loyalty	Auto		Household	Inferred	9,83	20,64	Households that Alliant has identified to be a defector from sedans, meaning they have owned a sedans but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small Car Loyalists	Auto	Loyalty	Auto		Household	Inferred	10,07	21,15	Households that Alliant has identified to be loyal in their continued purchase of a small car. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small Car Switchers	Auto	Loyalty	Auto		Household	Inferred	8,38	17,60	Households that Alliant has identified to be a defector from small cars, meaning they have owned a small car but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small SUV Loyalists	Auto	Loyalty	Auto		Household	Inferred	3,33	6,99	Households that Alliant has identified to be loyal in their continued purchase of a small SUV. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small SUV Switchers	Auto	Loyalty	Auto		Household	Inferred	5,68	11,93	Households that Alliant has identified to be a defector from small SUV, meaning they have owned a Small SUV but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small Truck Loyalists	Auto	Loyalty	Auto		Household	Inferred	355,67	746,91	Households that Alliant has identified to be loyal in their continued purchase of a small truck. Identified by known historic auto ownership data through nationwide dealership and service department records.
Small Truck Switchers	Auto	Loyalty	Auto		Household	Inferred	1,85	3,89	Households that Alliant has identified to be a defector from Small Truck, meaning they have owned a small truck but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Subaru Switchers	Auto	Loyalty	Auto		Household	Inferred	1,44	3,03	Households that Alliant has identified to be a defector from Subaru, meaning they have owned a Subaru but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Toyota Loyalists	Auto	Loyalty	Auto		Household	Inferred	2,44	5,11	Households that Alliant has identified to be loyal in their continued purchase of a Toyota. Identified by known historic auto ownership data through nationwide dealership and service department records.
Toyota Switchers	Auto	Loyalty	Auto		Household	Inferred	7,24	15,21	Households that Alliant has identified to be a defector from Toyota, meaning they have owned a Toyota but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Utility Van Switchers	Auto	Loyalty	Auto		Household	Inferred	9,15	19,22	Households that Alliant has identified to be a defector from utility vans, meaning they have owned a utility van but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Van Loyalists	Auto	Loyalty	Auto		Household	Inferred	1,99	4,18	Households that Alliant has identified to be loyal in their continued purchase of a van. Identified by known historic auto ownership data through nationwide dealership and service department records.
Volkswagen Switchers	Auto	Loyalty	Auto		Household	Inferred	1,73	3,62	Households that Alliant has identified to be a defector from Volkswagen, meaning they have owned a Volkswagen but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Volvo Switchers	Auto	Loyalty	Auto		Household	Inferred	667,53	1,40	Households that Alliant has identified to be a defector from Volvo, meaning they have owned a Volvo but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
Wagon Loyalists	Auto	Loyalty	Auto		Household	Inferred	941,59	1,98	Households that Alliant has identified to be loyal in their continued purchase of a wagon. Identified by known historic auto ownership data through nationwide dealership and service department records.
Wagon Switchers	Auto	Loyalty	Auto		Household	Inferred	3,02	6,35	Households that Alliant has identified to be a defector from wagons, meaning they have owned a wagon but do not have a repeat history of purchasing that vehicle type. Identified by known historic auto ownership data through nationwide dealership and service department records.
0 – 30k Miles	Auto	Mileage Ranges	Auto		Household	Known	12,45	26,14	Households that own a vehicle with mileage ranging between 0-30k, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
100K+ Miles	Auto	Mileage Ranges	Auto		Household	Known	6,01	12,61	Households that own a vehicle with mileage over 100k, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
30k – 50k Miles	Auto	Mileage Ranges	Auto		Household	Known	4,81	10,10	Households that own a vehicle with mileage ranging between 30-50k, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
50k – 75k Miles	Auto	Mileage Ranges	Auto		Household	Known	3,65	7,67	Households that own a vehicle with mileage ranging between 50-75k, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
75k – 100k Miles	Auto	Mileage Ranges	Auto		Household	Known	4,29	9,02	Households that own a vehicle with mileage ranging between 75-100k, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Auto Lease Propensity	Auto	Ownership	Auto		Household	Modeled	12,27	25,77	This audience consists of households in the top 20% of a model predicting the likelihood that a member leases a car. The model is built using survey data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The combined data identifies households in the cooperative that have shared characteristics.
Emerging Consumers - Clunker Owners	Auto	Ownership	Auto		Household	Modeled	6,14	12,90	Households that own a clunker car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Economy Car Owners	Auto	Ownership	Auto		Household	Modeled	13,24	27,81	Households that own an economy car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Green Car Owners	Auto	Ownership	Auto		Household	Modeled	3,20	6,72	Households that own a green car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Luxury Car Owners	Auto	Ownership	Auto		Household	Modeled	2,52	5,30	Households that own a luxury car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Mini Van Owners	Auto	Ownership	Auto		Household	Modeled	2,62	5,49	Households that own a mini van, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Multi-Car Owners	Auto	Ownership	Auto		Household	Modeled	13,66	28,69	Households that own multiple cars, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Sedan Owners	Auto	Ownership	Auto		Household	Modeled	14,61	30,69	Households that own a sedan, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Sports Car Owners	Auto	Ownership	Auto		Household	Modeled	328,47	689,79	Households that own a sports car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - SUV Owners	Auto	Ownership	Auto		Household	Modeled	9,41	19,76	Households that own a SUV, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Truck Owners	Auto	Ownership	Auto		Household	Modeled	6,92	14,53	Households that own a truck, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Emerging Consumers - Wagon Owners	Auto	Ownership	Auto		Household	Modeled	2,25	4,73	Households that own a wagon, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the bottom 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Clunker Owners	Auto	Ownership	Auto		Household	Modeled	8,04	16,88	Households that own a clunker car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Economy Car Owners	Auto	Ownership	Auto		Household	Modeled	20,78	43,63	Households that own an economy car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.
Empowered Consumers - Green Car Owners	Auto	Ownership	Auto		Household	Modeled	5,83	12,23	Households that own a green car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Luxury Car Owners	Auto	Ownership	Auto		Household	Modeled	4,85	10,19	Households that own luxury cars, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Mini Van Owners	Auto	Ownership	Auto		Household	Modeled	4,48	9,41	Households that own mini vans, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Multi-Car Owners	Auto	Ownership	Auto		Household	Modeled	24,27	50,96	Households that own multiple cars, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Sedan Owners	Auto	Ownership	Auto		Household	Modeled	22,19	46,61	Households that own a sedan, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Sports Car Owners	Auto	Ownership	Auto		Household	Modeled	658,50	1,38	Households that own a sports car, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - SUV Owners	Auto	Ownership	Auto		Household	Modeled	16,85	35,38	Households that own a SUV, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Truck Owners	Auto	Ownership	Auto		Household	Modeled	11,30	23,73	Households that own a truck, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Empowered Consumers - Wagon Owners	Auto	Ownership	Auto		Household	Modeled	4,13	8,67	Households that own a wagon, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) who are scored with a payment performance model to identify those who are in the top 50% of buying activity in the Alliant cooperative.)
Hybrid Cars Propensity	Auto	Ownership	Auto		Household	Modeled	14,45	30,35	This audience consists of households in the top 20% of a model predicting the likelihood that they own or lease at least one hybrid vehicle. The model is built using survey data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The combined data identifies households in the cooperative that have shared characteristics.
Motorcycle Owner Propensity	Auto	Ownership	Auto		Household	Modeled	15,01	31,52	This audience consists of households in the top 20% of a model predicting the likelihood that they own a new or used motorcycle. The model is built using survey data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The combined data identifies households in the cooperative that have shared characteristics.
Own a BMW	Auto	Ownership	Auto		Household	Known	3,22	6,77	Households that own a BMW, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Cadillac	Auto	Ownership	Auto		Household	Known	3,23	6,78	Households that own a Cadillac, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet	Auto	Ownership	Auto		Household	Known	23,30	48,94	Households that own a Chevrolet, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Blazer	Auto	Ownership	Auto		Household	Known	1,17	2,46	Households that own a Chevrolet Blazer, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Camaro	Auto	Ownership	Auto		Household	Known	903,24	1,90	Households that own a Chevrolet Camaro, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Cruze	Auto	Ownership	Auto		Household	Known	996,25	2,09	Households that own a Chevrolet Cruze, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Equinox	Auto	Ownership	Auto		Household	Known	1,69	3,56	Households that own a Chevrolet Equinox, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Impala	Auto	Ownership	Auto		Household	Known	2,34	4,92	Households that own a Chevrolet Impala, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Malibu	Auto	Ownership	Auto		Household	Known	2,46	5,17	Households that own a Chevrolet Malibu, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Suburban	Auto	Ownership	Auto		Household	Known	1,61	3,37	Households that own a Chevrolet Suburban, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chevrolet Tahoe	Auto	Ownership	Auto		Household	Known	1,98	4,15	Households that own a Chevrolet Tahoe, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Chrysler	Auto	Ownership	Auto		Household	Known	6,07	12,75	Households that own a Chrysler, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Dodge	Auto	Ownership	Auto		Household	Known	13,50	28,35	Households that own a Dodge, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Dodge Caravan	Auto	Ownership	Auto		Household	Known	2,88	6,05	Households that own a Dodge Caravan, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Dodge RAM	Auto	Ownership	Auto		Household	Known	3,02	6,34	Households that own a Dodge RAM, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford	Auto	Ownership	Auto		Household	Known	24,72	51,91	Households that own a Ford, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford Escape	Auto	Ownership	Auto		Household	Known	2,51	5,27	Households that own a Ford Escape, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford Expedition	Auto	Ownership	Auto		Household	Known	1,67	3,51	Households that own a Ford Expedition, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford Explorer	Auto	Ownership	Auto		Household	Known	3,87	8,13	Households that own a Ford Explorer, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford Fusion	Auto	Ownership	Auto		Household	Known	1,76	3,70	Households that own a Ford Fusion, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Ford Truck	Auto	Ownership	Auto		Household	Known	6,94	14,57	Households that own a Ford Truck, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a GMC	Auto	Ownership	Auto		Household	Known	6,56	13,78	Households that own a GMC, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a GMC Envoy	Auto	Ownership	Auto		Household	Known	752,33	1,58	Households that own a GMC Envoy, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a GMC Sierra	Auto	Ownership	Auto		Household	Known	2,46	5,16	Households that own a GMC Sierra, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda	Auto	Ownership	Auto		Household	Known	13,58	28,52	Households that own a Honda, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda Accord	Auto	Ownership	Auto		Household	Known	5,21	10,94	Households that own a Honda Accord, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda Civic	Auto	Ownership	Auto		Household	Known	3,74	7,85	Households that own a Honda Civic, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda CRV	Auto	Ownership	Auto		Household	Known	2,47	5,18	Households that own a Honda CRV, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda Odyssey	Auto	Ownership	Auto		Household	Known	1,86	3,91	Households that own a Honda Odyssey, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Honda Pilot	Auto	Ownership	Auto		Household	Known	1,40	2,95	Households that own a Honda Pilot, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Hyundai	Auto	Ownership	Auto		Household	Known	6,00	12,61	Households that own a Hyundai, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Jaguar	Auto	Ownership	Auto		Household	Known	388,19	815,21	Households that own a Jaguar, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Jeep	Auto	Ownership	Auto		Household	Known	7,41	15,56	Households that own a Jeep, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Jeep Cherokee	Auto	Ownership	Auto		Household	Known	1,17	2,46	Households that own a Jeep Cherokee, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Jeep Wrangler	Auto	Ownership	Auto		Household	Known	2,07	4,34	Households that own a Jeep Wrangler, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Kia	Auto	Ownership	Auto		Household	Known	4,44	9,32	Households that own a Kia, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Land Rover	Auto	Ownership	Auto		Household	Known	437,12	917,96	Households that own a Land Rover, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Lexus	Auto	Ownership	Auto		Household	Known	3,21	6,74	Households that own a Lexus, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Lincoln	Auto	Ownership	Auto		Household	Known	2,08	4,37	Households that own a Lincoln, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Mazda	Auto	Ownership	Auto		Household	Known	3,83	8,04	Households that own a Mazda, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Mercedes-Benz	Auto	Ownership	Auto		Household	Known	2,93	6,16	Households that own a Mercedes-Benz, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Mini	Auto	Ownership	Auto		Household	Known	469,47	985,89	Households that own a Mini, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Mitsubishi	Auto	Ownership	Auto		Household	Known	2,05	4,31	Households that own a Mitsubishi, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan	Auto	Ownership	Auto		Household	Known	10,41	21,87	Households that own a Nissan, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan Altima	Auto	Ownership	Auto		Household	Known	2,91	6,12	Households that own a Nissan Altima, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan Frontier	Auto	Ownership	Auto		Household	Known	786,31	1,65	Households that own a Nissan Frontier, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan Maxima	Auto	Ownership	Auto		Household	Known	1,26	2,66	Households that own a Nissan Maxima, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan Pathfinder	Auto	Ownership	Auto		Household	Known	841,95	1,77	Households that own a Nissan Pathfinder, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Nissan Sentra	Auto	Ownership	Auto		Household	Known	1,52	3,19	Households that own a Nissan Sentra, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Porsche	Auto	Ownership	Auto		Household	Known	360,91	757,91	Households that own a Porsche, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Subaru	Auto	Ownership	Auto		Household	Known	2,89	6,06	Households that own a Subaru, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota	Auto	Ownership	Auto		Household	Known	17,16	36,03	Households that own a Toyota, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota 4Runner	Auto	Ownership	Auto		Household	Known	1,23	2,58	Households that own a Toyota 4Runner, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Avalon	Auto	Ownership	Auto		Household	Known	856,53	1,80	Households that own a Toyota Avalon, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Camry	Auto	Ownership	Auto		Household	Known	5,01	10,51	Households that own a Toyota Camry, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Corolla	Auto	Ownership	Auto		Household	Known	3,17	6,66	Households that own a Toyota Corolla, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Highlander	Auto	Ownership	Auto		Household	Known	1,39	2,93	Households that own a Toyota Highlander, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Prius	Auto	Ownership	Auto		Household	Known	1,23	2,58	Households that own a Toyota Prius, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota RAV4	Auto	Ownership	Auto		Household	Known	1,64	3,45	Households that own a Toyota RAV4, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Sienna	Auto	Ownership	Auto		Household	Known	1,34	2,81	Households that own a Toyota Sienna, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Tacoma	Auto	Ownership	Auto		Household	Known	1,65	3,46	Households that own a Toyota Tacoma, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Toyota Tundra	Auto	Ownership	Auto		Household	Known	1,25	2,63	Households that own a Toyota Tundra, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Volkswagen	Auto	Ownership	Auto		Household	Known	3,85	8,09	Households that own a Volkswagen, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own a Volvo	Auto	Ownership	Auto		Household	Known	1,40	2,95	Households that own a Volvo, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own an Acura	Auto	Ownership	Auto		Household	Known	2,44	5,12	Households that own an Acura, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own an Audi	Auto	Ownership	Auto		Household	Known	1,39	2,93	Households that own an Audi, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Own an Infiniti	Auto	Ownership	Auto		Household	Known	1,47	3,10	Households that own an Infiniti, identified by nationwide dealership and service department records. These households are also known multichannel buyers (via digital and offline channels from DTC businesses) in the Alliant cooperative.
Executives who are Sports Fans	B2B	Activities & Interests	Sports		Household	Inferred	24,63	51,72	The Executives Who are Sports Fans audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
C-Level Executives Under 50	B2B	Age	Demographics		Household	Known	947,78	1,99	The C-level Executives Under 50 audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives In Market for New Vehicle	B2B	Auto	Auto		Household	Modeled	1,39	2,93	The Executives In Market for New Vehicle audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Apple Buyer Propensity	B2B	Brands	Tech		Household	Modeled	2,29	4,81	The Executives with Apple Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Dell Buyer Propensity	B2B	Brands	Tech		Household	Modeled	1,96	4,11	The Executives with Dell Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Lyft Buyer Propensity	B2B	Brands	Travel		Household	Modeled	2,02	4,25	The Executives with Lyft Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Microsoft Buyer Propensity	B2B	Brands	Tech		Household	Modeled	2,24	4,71	The Executives with Microsoft Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Samsung Buyer Propensity	B2B	Brands	Tech		Household	Modeled	2,06	4,33	The Executives with Samsung Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Tat Buyer Propensity	B2B	Brands	Telecom		Household	Modeled	1,83	3,85	The Executives with AT&T Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with T-Mobile Buyer Propensity	B2B	Brands	Telecom		Household	Modeled	1,77	3,72	The Executives with T-Mobile Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Uber Buyer Propensity	B2B	Brands	Travel		Household	Modeled	2,27	4,77	The Executives with Uber Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Verizon Buyer Propensity	B2B	Brands	Telecom		Household	Modeled	1,83	3,85	The Executives with Verizon Buyer Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Small Business Owners at Home who use AMEX	B2B	Card Type	Home		Household	Known	190,85	400,79	The Small Business Owners who use AMEX audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Small Business Owners at Home who use Discover Card	B2B	Card Type	Home		Household	Known	136,56	286,78	The Small Business Owners who use Discover Card audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Small Business Owners at Home who use Mastercard	B2B	Card Type	Home		Household	Known	311,95	655,09	The Small Business Owners who use Mastercard audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Small Business Owners at Home who use Visa	B2B	Card Type	Home		Household	Known	446,57	937,80	The Small Business Owners who use Visa audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Children 0-12	B2B	Family	Demographics		Household	Known	1,45	3,05	The Executives with Children 0-12 audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives with Teens	B2B	Family	Demographics		Household	Known	876,81	1,84	The Executives with Teens audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Female C-Suite at Home	B2B	Gender	Home		Household	Known	918,88	1,93	The Female C-Suite audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Female Executives at Home	B2B	Gender	Home		Household	Known	3,06	6,42	The Female Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Male C-Suite at Home	B2B	Gender	Home		Household	Known	867,78	1,82	The Male C-Suite audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Male Executives at Home	B2B	Gender	Home		Household	Known	2,13	4,48	The Male Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives Who Have Recently Moved	B2B	New Movers	Demographics		Household	Known	184,13	386,66	The Executives Who Have Recently Moved audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Architecture & Engineering Professionals at Home	B2B	Occupation	Home		Household	Known	100,35	210,73	The Architecture & Engineering Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Arts & Entertainment Professionals at Home	B2B	Occupation	Home		Household	Known	229,63	482,22	The Arts & Entertainment Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Construction & Maintenance Professionals at Home	B2B	Occupation	Home		Household	Known	364,26	764,95	The Construction & Maintenance Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Education Professionals at Home	B2B	Occupation	Home		Household	Modeled	367,02	770,73	The Education Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Finance & Banking Professionals at Home	B2B	Occupation	Home		Household	Known	374,05	785,51	The Finance & Banking Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Food Prep & Hospitality Professionals at Home	B2B	Occupation	Home		Household	Known	98,49	206,83	The Food Prep & Hospitality Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Healthcare Professionals at Home	B2B	Occupation	Home		Household	Known	341,27	716,67	The Healthcare Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
IT Professionals at Home	B2B	Occupation	Home		Household	Known	140,74	295,56	The IT Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Legal Professionals at Home	B2B	Occupation	Home		Household	Known	95,47	200,50	The Legal Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Real Estate & Insurance Professionals at Home	B2B	Occupation	Home		Household	Known	578,54	1,21	The Real Estate & Insurance Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Religious Professionals at Home	B2B	Occupation	Home		Household	Known	104,40	219,24	The Religious Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Sales & Marketing Professionals at Home	B2B	Occupation	Home		Household	Known	299,98	629,97	The Sales & Marketing Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Sports & Training Professionals at Home	B2B	Occupation	Home		Household	Known	197,21	414,14	The Sports & Training Professionals audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Democrat Executives	B2B	Party Affiliations	Politics		Household	Known	757,73	1,59	The Democrat Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Republican Executives	B2B	Party Affiliations	Politics		Household	Known	783,86	1,65	The Republican Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives Interested in New York Post	B2B	Publications	Media & Entertainment		Household	Modeled	1,97	4,15	The Executives Interested in New York Post audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives Interested in New York Times	B2B	Publications	Media & Entertainment		Household	Modeled	1,64	3,45	The Executives Interested in New York Times audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives Interested in Wall Street Journal	B2B	Publications	Media & Entertainment		Household	Modeled	1,59	3,34	The Executives Interested in Wall Street Journal audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Executives Interested in Washington Post	B2B	Publications	Media & Entertainment		Household	Modeled	1,96	4,11	The Executives Interested in Washington Post audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
C-Level Executives with JetBlue Interest	B2B	Travel	Travel		Household	Modeled	596,64	1,25	The C-Level Executives with JetBlue Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
C-Level Executives with United Airlines Interest	B2B	Travel	Travel		Household	Modeled	689,91	1,45	The C-Level Executives with United Airlines Interest audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Domestic Traveling Executives	B2B	Travel	Travel		Household	Known	1,79	3,77	The Domestic Traveling Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
International Traveling Executives	B2B	Travel	Travel		Household	Known	1,72	3,60	The International Traveling Executives audience enables you to reach this niche segment outside of the office, across devices. They are also known direct-to-consumer buyers within the Alliant DataHub.
Top Golf	Brand Propensities	Activities & Interests	Sports		Household	Modeled	13,70	28,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Top Golf. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Alcoholic Beverages	Brand Propensities	Alcoholic Beverages	Food & Beverage		Household	Modeled	15,15	31,82	This audience consists of households in the top 10-20% of a model predicting a purchase from the Alcoholic Beverages category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saucey Buyer Propensity	Brand Propensities	Alcoholic Beverages	Food & Beverage		Household	Modeled	10,51	22,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Saucey. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Total wine & more Buyer Propensity	Brand Propensities	Alcoholic Beverages	Food & Beverage		Household	Modeled	11,05	23,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Total wine & more. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
WSJwine Buyer Propensity	Brand Propensities	Alcoholic Beverages	Food & Beverage		Household	Modeled	11,01	23,12	This audience consists of households in the top 10-20% of a model predicting a purchase from WSJwine. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Abercrombie & Fitch Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,75	26,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Abercrombie & Fitch. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Adidas Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,48	22,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Adidas. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Adore Me Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,20	21,42	This audience consists of households in the top 10-20% of a model predicting a purchase from Adore Me. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ALDO Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,84	24,87	This audience consists of households in the top 10-20% of a model predicting a purchase from ALDO. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Allbirds Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,11	23,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Allbirds. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
American Eagle Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,36	28,05	This audience consists of households in the top 10-20% of a model predicting a purchase from American Eagle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ann Taylor Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,35	23,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Ann Taylor. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Anthropologie Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	33,74	70,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Anthropologie. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ashley Stewart Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,31	25,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Ashley Stewart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Asics Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,30	19,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Asics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
asos Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,58	30,62	This audience consists of households in the top 10-20% of a model predicting a purchase from asos. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Banana Republic Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,30	23,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Banana Republic. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bare Necessities Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	26,27	55,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Bare Necessities. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
BCBG Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,13	23,36	This audience consists of households in the top 10-20% of a model predicting a purchase from BCBG. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Belk Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,59	24,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Belk. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bergdorf Goodman Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,96	29,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Bergdorf Goodman. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bloomingdale's Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,00	29,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Bloomingdale's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blue Nile Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,76	26,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Blue Nile. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bonobos Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,29	25,82	This audience consists of households in the top 10-20% of a model predicting a purchase from Bonobos. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
boohoo Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,10	23,31	This audience consists of households in the top 10-20% of a model predicting a purchase from boohoo. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Boot Barn Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,63	22,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Boot Barn. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Brandy Melville Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,81	22,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Brandy Melville. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Brooks Brothers Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,78	26,83	This audience consists of households in the top 10-20% of a model predicting a purchase from Brooks Brothers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Burberry Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,22	25,66	This audience consists of households in the top 10-20% of a model predicting a purchase from Burberry. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Burlington Coat Factory Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,75	20,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Burlington Coat Factory. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Calvin Klein Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,87	20,72	This audience consists of households in the top 10-20% of a model predicting a purchase from Calvin Klein. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Carters Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,26	21,54	This audience consists of households in the top 10-20% of a model predicting a purchase from Carters. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Casual Male XL Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,04	23,19	This audience consists of households in the top 10-20% of a model predicting a purchase from Casual Male XL. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chanel Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,16	21,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Chanel. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chico's Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	22,00	46,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Chico's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chico's FAS Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,45	26,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Chico’s FAS. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Club Monaco Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,86	27,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Club Monaco. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Coach Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,41	21,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Coach. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cole Haan Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,76	24,70	This audience consists of households in the top 10-20% of a model predicting a purchase from Cole Haan. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Converse Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,54	26,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Converse. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cotton On	Brand Propensities	Apparel	Retail		Household	Modeled	13,52	28,40	This audience consists of households in the top 10-20% of a model predicting a purchase from Cotton On. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Crocs Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,33	21,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Crocs. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dillards Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,86	22,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Dillards. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dior Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,46	19,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Dior. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dolce Vita Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,62	22,29	This audience consists of households in the top 10-20% of a model predicting a purchase from Dolce Vita. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DSW Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,04	23,19	This audience consists of households in the top 10-20% of a model predicting a purchase from DSW. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Duluth Trading Company Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,23	23,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Duluth Trading Company. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Eddie Bauer Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,84	22,76	This audience consists of households in the top 10-20% of a model predicting a purchase from Eddie Bauer. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Express Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,49	24,13	This audience consists of households in the top 10-20% of a model predicting a purchase from Express. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fabletics Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,47	24,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Fabletics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Famous Footwear Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	4,32	9,06	This audience consists of households in the top 10-20% of a model predicting a purchase from Famous Footwear. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Foot Locker Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,54	30,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Foot Locker. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Forever 21 Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,86	24,91	This audience consists of households in the top 10-20% of a model predicting a purchase from Forever 21. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fossil Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,55	22,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Fossil. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gap Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,50	24,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Gap. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gucci Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,63	24,43	This audience consists of households in the top 10-20% of a model predicting a purchase from Gucci. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Guess Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,29	21,62	This audience consists of households in the top 10-20% of a model predicting a purchase from Guess. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
H&M Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,81	24,81	This audience consists of households in the top 10-20% of a model predicting a purchase from H&M. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hanes Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,12	19,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Hanes. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hermes Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,17	27,66	This audience consists of households in the top 10-20% of a model predicting a purchase from Hermes. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hot Topic Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	8,75	18,38	This audience consists of households in the top 10-20% of a model predicting a purchase from Hot Topic. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hush Puppies Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	5,38	11,30	This audience consists of households in the top 10-20% of a model predicting a purchase from Hush Puppies. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Indochino Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,16	21,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Indochino. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
J.Crew Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,10	25,42	This audience consists of households in the top 10-20% of a model predicting a purchase from J.Crew. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
J.JILL Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,49	26,23	This audience consists of households in the top 10-20% of a model predicting a purchase from J.JILL. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
JanSport Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,58	20,12	This audience consists of households in the top 10-20% of a model predicting a purchase from JanSport. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
JCPenney Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	27,27	57,26	This audience consists of households in the top 10-20% of a model predicting a purchase from JCPenney. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jordan Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,92	27,13	This audience consists of households in the top 10-20% of a model predicting a purchase from Jordan. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
JoS. A. Bank Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,25	19,42	This audience consists of households in the top 10-20% of a model predicting a purchase from JoS. A. Bank. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Journeys Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,13	21,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Journeys. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
JustFab Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	8,82	18,53	This audience consists of households in the top 10-20% of a model predicting a purchase from JustFab. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kate Spade Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,99	23,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Kate Spade. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Keds Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,10	23,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Keds. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kipling Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,37	19,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Kipling. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
L.L.Bean Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,40	21,84	This audience consists of households in the top 10-20% of a model predicting a purchase from L.L.Bean. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lady Foot Locker Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	42,86	90,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Lady Foot Locker. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lane Bryant Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,44	26,13	This audience consists of households in the top 10-20% of a model predicting a purchase from Lane Bryant. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Levi's Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,99	25,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Levi's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lids Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,85	20,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Lids. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lilly Pulitzer Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,37	21,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Lilly Pulitzer. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Loft Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,52	24,19	This audience consists of households in the top 10-20% of a model predicting a purchase from LOFT. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lord & Taylor Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,35	28,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Lord & Taylor. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Louis Vuitton Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,07	25,35	This audience consists of households in the top 10-20% of a model predicting a purchase from Louis Vuitton. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lululemon Athletica Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,35	23,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Lululemon Athletica. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lulus Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,31	19,55	This audience consists of households in the top 10-20% of a model predicting a purchase from Lulus. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Luxury Department Store	Brand Propensities	Apparel	Retail		Household	Modeled	16,34	34,32	This audience consists of households in the top 10-20% of a model predicting a purchase from the Luxury Department Store category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Macy's Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,83	22,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Macy's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Madewell	Brand Propensities	Apparel	Retail		Household	Modeled	13,94	29,27	This audience consists of households in the top 10-20% of a model predicting a purchase from Madewell. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Marshalls Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,37	23,87	This audience consists of households in the top 10-20% of a model predicting a purchase from Marshalls. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Men's Wearhouse Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	8,94	18,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Men's Wearhouse. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Merrell Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,10	21,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Merrell. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MeUndies Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,31	25,84	This audience consists of households in the top 10-20% of a model predicting a purchase from MeUndies. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Michael Kors Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,49	22,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Michael Kors. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nautica Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,80	20,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Nautica. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Neiman Marcus Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,45	28,25	This audience consists of households in the top 10-20% of a model predicting a purchase from Neiman Marcus. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
New Balance Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,21	21,45	This audience consists of households in the top 10-20% of a model predicting a purchase from New Balance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
New York & Company Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,16	23,44	This audience consists of households in the top 10-20% of a model predicting a purchase from New York & Company. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nike Buyer Propensity	Brand Propensities	Apparel	Retail	Sports	Household	Modeled	10,04	21,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Nike. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nobull	Brand Propensities	Apparel	Retail		Household	Modeled	14,16	29,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Nobull. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nordstrom Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,75	26,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Nordstrom. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nordstrom Rack Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,75	26,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Nordstrom Rack. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Oakley Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,62	20,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Oakley. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Old Navy Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,20	21,42	This audience consists of households in the top 10-20% of a model predicting a purchase from Old Navy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pacific Sunwear	Brand Propensities	Apparel	Retail		Household	Modeled	13,13	27,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Pacific Sunwear. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pandora Jewelry Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,69	24,56	This audience consists of households in the top 10-20% of a model predicting a purchase from Pandora Jewelry. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Patagonia Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,35	23,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Patagonia. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Puma Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,70	24,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Puma. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ralph Lauren Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,86	24,90	This audience consists of households in the top 10-20% of a model predicting a purchase from Ralph Lauren. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ray-Ban Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,37	23,88	This audience consists of households in the top 10-20% of a model predicting a purchase from Ray Ban. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Reebok Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,24	19,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Reebok. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rent the Runway Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,24	27,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Rent the Runway. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ross Dress For Less Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,72	22,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Ross Dress For Less. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rue La La Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,95	29,29	This audience consists of households in the top 10-20% of a model predicting a purchase from Rue La La. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saks Fifth Avenue Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,92	29,24	This audience consists of households in the top 10-20% of a model predicting a purchase from Saks Fifth Avenue. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saks Fifth Avenue OFF 5TH Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,09	29,59	This audience consists of households in the top 10-20% of a model predicting a purchase from Saks Fifth Avenue OFF 5TH. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Samsonite Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,10	21,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Samsonite. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saucony Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,54	22,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Saucony. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Shoe Carnival Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	4,42	9,29	This audience consists of households in the top 10-20% of a model predicting a purchase from Shoe Carnival. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Shopbop Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,08	29,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Shopbop. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sierra Trading Post Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,26	23,66	This audience consists of households in the top 10-20% of a model predicting a purchase from Sierra Trading Post. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Skechers Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,37	21,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Skechers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Soma.com Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,41	26,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Soma.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Spanx Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,56	24,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Spanx. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Steven Madden Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,91	27,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Steven Madden. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Stitch fix Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,83	26,94	This audience consists of households in the top 10-20% of a model predicting a purchase from Stitch fix. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Stride Rite Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,53	22,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Stride Rite. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sunglass Hut Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,33	23,79	This audience consists of households in the top 10-20% of a model predicting a purchase from Sunglass Hut. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
T.J. Maxx Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,40	26,04	This audience consists of households in the top 10-20% of a model predicting a purchase from T.J. Maxx. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Talbots Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,98	25,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Talbots. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The North Face Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,86	24,91	This audience consists of households in the top 10-20% of a model predicting a purchase from The North face. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ThirdLove Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,30	21,64	This audience consists of households in the top 10-20% of a model predicting a purchase from ThirdLove. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Thursday Boot Co. Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,08	21,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Thursday Boot Co. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tiffany & Co. Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,95	25,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Tiffany & Co. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Timberland Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,21	21,44	This audience consists of households in the top 10-20% of a model predicting a purchase from Timberland. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tommy Bahama Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,47	19,88	This audience consists of households in the top 10-20% of a model predicting a purchase from Tommy Bahama. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tommy Hilfiger Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	9,93	20,85	This audience consists of households in the top 10-20% of a model predicting a purchase from Tommy Hilfiger. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tommy John Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,04	23,18	This audience consists of households in the top 10-20% of a model predicting a purchase from Tommy John. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
TOMS Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,37	21,78	This audience consists of households in the top 10-20% of a model predicting a purchase from TOMS. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tory Burch Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,12	25,45	This audience consists of households in the top 10-20% of a model predicting a purchase from Tory Burch. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
UGG Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	14,76	30,99	This audience consists of households in the top 10-20% of a model predicting a purchase from UGG. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Under Armour Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,00	23,10	This audience consists of households in the top 10-20% of a model predicting a purchase from Under Armour. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Uniqlo Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,01	23,13	This audience consists of households in the top 10-20% of a model predicting a purchase from Uniqlo. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Urban Outfitters Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,81	26,89	This audience consists of households in the top 10-20% of a model predicting a purchase from Urban Outfitters. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Vans Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	4,20	8,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Vans. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Vera Bradley Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,77	24,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Vera Bradley. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Victoria's Secret Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,66	22,38	This audience consists of households in the top 10-20% of a model predicting a purchase from Victoria's Secret. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Warby Parker Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,43	28,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Warby Parker. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
White House Black Market Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	12,31	25,85	This audience consists of households in the top 10-20% of a model predicting a purchase from White House Black Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wrangler Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	3,96	8,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Wrangler. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zappos Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	11,55	24,26	This audience consists of households in the top 10-20% of a model predicting a purchase from Zappos. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ZARA Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	13,58	28,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Zara. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zumiez Buyer Propensity	Brand Propensities	Apparel	Retail		Household	Modeled	10,38	21,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Zumiez. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Advance Auto Parts Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	11,11	23,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Advance Auto Parts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AutoNation Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	10,71	22,49	This audience consists of households in the top 10-20% of a model predicting a purchase from AutoNation. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AutoZone Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	11,53	24,21	This audience consists of households in the top 10-20% of a model predicting a purchase from AutoZone. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Big O tires Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	10,94	22,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Big O tires. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Budget Truck	Brand Propensities	Auto	Auto		Household	Modeled	14,76	31,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Budget Truck. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Carmax Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	10,85	22,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Carmax. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Carquest Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	8,66	18,18	This audience consists of households in the top 10-20% of a model predicting a purchase from Carquest. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Discount Tire Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	4,06	8,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Discount Tire. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
FasTrak	Brand Propensities	Auto	Auto		Household	Modeled	14,57	30,60	This audience consists of households in the top 10-20% of a model predicting a purchase from FasTrak. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ford Credit Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	22,28	46,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Ford Credit. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Harley-Davidson Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	12,78	26,83	This audience consists of households in the top 10-20% of a model predicting a purchase from Harley-Davidson. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jiffy Lube Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	10,96	23,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Jiffy Lube. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Meineke Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	9,60	20,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Meineke. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Midas Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	9,66	20,29	This audience consists of households in the top 10-20% of a model predicting a purchase from Midas. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Napa Auto Parts Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	4,06	8,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Napa Auto Parts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
O'Reilly Auto Parts Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	8,94	18,78	This audience consists of households in the top 10-20% of a model predicting a purchase from O'Rielly Auto Parts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ParkMobile	Brand Propensities	Auto	Auto		Household	Modeled	15,63	32,82	This audience consists of households in the top 10-20% of a model predicting a purchase from ParkMobile. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pep Boys Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	9,04	18,99	This audience consists of households in the top 10-20% of a model predicting a purchase from Pep Boys. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
RockAuto Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	10,36	21,75	This audience consists of households in the top 10-20% of a model predicting a purchase from RockAuto. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
SunPass	Brand Propensities	Auto	Auto		Household	Modeled	14,70	30,87	This audience consists of households in the top 10-20% of a model predicting a purchase from SunPass. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tirerack.com Buyer Propensity	Brand Propensities	Auto	Auto		Household	Modeled	27,14	57,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Tirerack.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Big Lots Stores Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	10,20	21,43	This audience consists of households in the top 10-20% of a model predicting a purchase from Big Lots Stores. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
BJ's Wholesale Club Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	10,53	22,11	This audience consists of households in the top 10-20% of a model predicting a purchase from BJ's Wholesale Club. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Costco Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	10,76	22,60	This audience consists of households in the top 10-20% of a model predicting a purchase from Costco. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dollar General Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	13,04	27,38	This audience consists of households in the top 10-20% of a model predicting a purchase from Dollar General. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dollar Tree Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	11,25	23,62	This audience consists of households in the top 10-20% of a model predicting a purchase from Dollar Tree. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Giant Food	Brand Propensities	Big Box Retail	Retail		Household	Modeled	12,53	26,30	This audience consists of households in the top 10-20% of a model predicting a purchase from Giant Food. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hannaford	Brand Propensities	Big Box Retail	Food & Beverage		Household	Modeled	13,58	28,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Hannaford. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kmart Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	10,01	21,02	This audience consists of households in the top 10-20% of a model predicting a purchase from Kmart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kohl's Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	9,83	20,63	This audience consists of households in the top 10-20% of a model predicting a purchase from Kohl's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Office Max Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	4,29	9,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Office Max. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sam's Club Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	11,13	23,37	This audience consists of households in the top 10-20% of a model predicting a purchase from Sam's Club. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sears Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	11,67	24,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Sears. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ShopRite	Brand Propensities	Big Box Retail	Retail		Household	Modeled	15,26	32,04	This audience consists of households in the top 10-20% of a model predicting a purchase from ShopRite. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sprouts Farmers Market	Brand Propensities	Big Box Retail	Food & Beverage		Household	Modeled	14,07	29,56	This audience consists of households in the top 10-20% of a model predicting a purchase from Sprouts Farmers Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Staples Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	11,00	23,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Staples. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Target Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	10,30	21,63	This audience consists of households in the top 10-20% of a model predicting a purchase from Target. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Walmart Buyer Propensity	Brand Propensities	Big Box Retail	Retail		Household	Modeled	12,68	26,64	This audience consists of households in the top 10-20% of a model predicting a purchase from Walmart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Amazon Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	9,03	18,96	This audience consists of households in the top 10-20% of a model predicting big spenders from Amazon. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
American Eagle Outfitters Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,27	23,67	This audience consists of households in the top 10-20% of a model predicting big spenders from American Eagle Outfitters. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AT&T Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	9,06	19,03	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from AT&T. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blue Apron Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Food & Beverage		Household	Modeled	11,71	24,59	This audience consists of households in the top 10-20% of a model predicting big spenders from Blue Apron. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Boost Mobile Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	9,28	19,50	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from Boost Mobile. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chewy.com Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Pet	Retail	Household	Modeled	11,47	24,09	This audience consists of households in the top 10-20% of a model predicting big spenders from Chewy.com. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Clinique Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Health & Beauty	Retail	Household	Modeled	10,48	22,01	This audience consists of households in the top 10-20% of a model predicting big spenders from Clinique. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Coach Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,60	24,36	This audience consists of households in the top 10-20% of a model predicting big spenders from Coach. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Costco Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail	Food & Beverage	Household	Modeled	9,92	20,83	This audience consists of households in the top 10-20% of a model predicting big spenders from Costco. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Disney Resorts Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Travel		Household	Modeled	9,47	19,88	This audience consists of households in the top 10-20% of a model predicting big spenders from Disney Resorts. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DoorDash Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Food & Beverage		Household	Modeled	11,31	23,76	This audience consists of households in the top 10-20% of a model predicting big spenders from DoorDash. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DraftKings Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Media & Entertainment		Household	Modeled	9,96	20,92	This audience consists of households in the top 10-20% of a model predicting big spenders from DraftKings. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Eddie Bauer Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	10,67	22,41	This audience consists of households in the top 10-20% of a model predicting big spenders from Eddie Bauer. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gap Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,46	24,07	This audience consists of households in the top 10-20% of a model predicting big spenders from GAP. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Grubhub Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Food & Beverage		Household	Modeled	12,44	26,13	This audience consists of households in the top 10-20% of a model predicting big spenders from GrubHub. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LG Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	3,35	7,04	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from LG. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lyft Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Travel		Household	Modeled	12,40	26,04	This audience consists of households in the top 10-20% of a model predicting big spenders from Lyft. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Macy's Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	9,66	20,29	This audience consists of households in the top 10-20% of a model predicting big spenders from Macy's. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MetroPCS Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	12,04	25,29	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from Metro PCS. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MGM Grand Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Media & Entertainment	Travel	Household	Modeled	10,77	22,63	This audience consists of households in the top 10-20% of a model predicting big spenders from MGM Grand. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Michael Kors Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,97	25,14	This audience consists of households in the top 10-20% of a model predicting big spenders from Michael Kors. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Old Navy Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,60	24,37	This audience consists of households in the top 10-20% of a model predicting big spenders from Old Navy. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saks Fifth Avenue Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	12,42	26,08	This audience consists of households in the top 10-20% of a model predicting big spenders from Saks Fifth Avenue. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sam's Club Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Food & Beverage		Household	Modeled	9,34	19,62	This audience consists of households in the top 10-20% of a model predicting big spenders from Sam's Club. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sephora Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Health & Beauty	Retail	Household	Modeled	12,66	26,59	This audience consists of households in the top 10-20% of a model predicting big spenders from Sephora. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sprint Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	8,21	17,24	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from Sprint. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Stamps.com Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Professional Services		Household	Modeled	15,12	31,74	This audience consists of households in the top 10-20% of a model predicting big spenders from Stamps.com. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tiffany Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,99	25,18	This audience consists of households in the top 10-20% of a model predicting big spenders from Tiffany. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
T-Mobile Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	12,38	25,99	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from T-Mobile. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ulta Beauty Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Health & Beauty	Retail	Household	Modeled	11,13	23,38	This audience consists of households in the top 10-20% of a model predicting big spenders from Ulta Beauty. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
USPS Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Professional Services		Household	Modeled	16,51	34,67	This audience consists of households in the top 10-20% of a model predicting big spenders from USPS. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Verizon Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Telecom		Household	Modeled	12,24	25,71	This audience consists of households in the top 10-20% of a model predicting mobile plan switchers from Verizon. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Walmart Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	9,57	20,09	This audience consists of households in the top 10-20% of a model predicting big spenders from Walmart. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Warby Parker Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	11,79	24,77	This audience consists of households in the top 10-20% of a model predicting big spenders from Warby Parker. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wayfair Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	10,63	22,32	This audience consists of households in the top 10-20% of a model predicting big spenders from Wayfair. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wingstop Big Spender Propensity	Brand Propensities	Big Spenders by Brand	QSR	Food & Beverage	Household	Modeled	10,95	22,99	This audience consists of households in the top 10-20% of a model predicting big spenders from Wingstop. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zara Big Spender Propensity	Brand Propensities	Big Spenders by Brand	Retail		Household	Modeled	12,83	26,95	This audience consists of households in the top 10-20% of a model predicting big spenders from Zara. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Active Wear Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail		Household	Modeled	11,47	24,10	This audience consists of households in the top 10-20% of a model predicting big spenders within the Active Wear category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Airlines Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Travel		Household	Modeled	10,14	21,29	This audience consists of households in the top 10-20% of a model predicting big spenders within the Airlines category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Apparel Accessories Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail		Household	Modeled	11,40	23,94	This audience consists of households in the top 10-20% of a model predicting big spenders within the Apparel Accessories category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Auto Insurance Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Auto		Household	Modeled	8,29	17,41	This audience consists of households in the top 10-20% of a model predicting big spenders within the Auto Insurance category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cruise Lines Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Travel		Household	Modeled	10,64	22,34	This audience consists of households in the top 10-20% of a model predicting big spenders within the Cruise Lines category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Delivery Aggregators Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Home		Household	Modeled	11,75	24,67	This audience consists of households in the top 10-20% of a model predicting big spenders within the Delivery Aggregators category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Drug Store Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail	Food & Beverage	Household	Modeled	9,90	20,79	This audience consists of households in the top 10-20% of a model predicting big spenders within the Drug/Pharma category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Electronics Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail	Tech	Household	Modeled	8,91	18,72	This audience consists of households in the top 10-20% of a model predicting big spenders within the Electronics category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fitness Center Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Health & Beauty		Household	Modeled	10,06	21,13	This audience consists of households in the top 10-20% of a model predicting big spenders within the Fitness Centers category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hardware Stores Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail	Home	Household	Modeled	10,47	21,98	This audience consists of households in the top 10-20% of a model predicting big spenders within the Hardware Stores category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Health Care Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Health & Beauty		Household	Modeled	10,55	22,16	This audience consists of households in the top 10-20% of a model predicting big spenders within the Healthcare category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Home Furnishings Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Home	Retail	Household	Modeled	10,43	21,90	This audience consists of households in the top 10-20% of a model predicting big spenders within the Home Furnishing category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Home Improvement Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Home	Retail	Household	Modeled	8,74	18,36	This audience consists of households in the top 10-20% of a model predicting big spenders within the Home Improvements category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Home Security Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Home	Tech	Household	Modeled	11,41	23,97	This audience consists of households in the top 10-20% of a model predicting big spenders within the Home Security category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Intimate Apparel Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail		Household	Modeled	11,53	24,21	This audience consists of households in the top 10-20% of a model predicting big spenders within the Intimate Apparel category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jewelry Watches Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail		Household	Modeled	11,90	25,00	This audience consists of households in the top 10-20% of a model predicting big spenders within the Jewelry/Watches category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lodging Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Travel		Household	Modeled	9,47	19,89	This audience consists of households in the top 10-20% of a model predicting big spenders within the Lodging category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Meal Kits Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Food & Beverage		Household	Modeled	14,94	31,37	This audience consists of households in the top 10-20% of a model predicting big spenders within the Meal Kits category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Mobile Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Telecom		Household	Modeled	8,77	18,42	This audience consists of households in the top 10-20% of a model predicting big spenders within the Mobile category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Occasion Gifts Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail		Household	Modeled	8,42	17,69	This audience consists of households in the top 10-20% of a model predicting big spenders within the Occasion Gifts category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Online Grocers Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Food & Beverage	Retail	Household	Modeled	12,16	25,54	This audience consists of households in the top 10-20% of a model predicting big spenders within the Online Grocers category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
QSR Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Food & Beverage		Household	Modeled	9,55	20,06	This audience consists of households in the top 10-20% of a model predicting big spenders within the QSR category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rental Cars Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Travel		Household	Modeled	9,97	20,93	This audience consists of households in the top 10-20% of a model predicting big spenders within the Rental Cars category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sporting Goods Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Retail	Sports	Household	Modeled	9,49	19,92	This audience consists of households in the top 10-20% of a model predicting big spenders within the Sporting Goods category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Supermarkets Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Food & Beverage		Household	Modeled	9,73	20,43	This audience consists of households in the top 10-20% of a model predicting big spenders within the Super Markets category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ticket Agencies Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Media & Entertainment		Household	Modeled	9,35	19,64	This audience consists of households in the top 10-20% of a model predicting big spenders within the Ticket Agencies category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Travel Agencies Big Spender Propensity	Brand Propensities	Big Spenders by Brand Category	Travel		Household	Modeled	10,28	21,59	This audience consists of households in the top 10-20% of a model predicting big spenders within the Travel Agencies category. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Allstate Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	12,32	25,88	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Allstate Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Farmers Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	9,52	20,00	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Farmers Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Geico Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	10,59	22,25	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Geico Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Progressive Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	8,75	18,37	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Progressive Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Safeco Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	9,87	20,72	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Safeco Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from State Farm Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	9,58	20,12	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from State Farm Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Propensity to Switch from Travelers Insurance	Brand Propensities	Brand/Category Switchers	Financial Services		Household	Modeled	10,06	21,13	This audience consists of households in the top 10-20% of a model predicting auto insurance switchers from Travelers Insurance. The model is built using brand specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
BP Buyer Propensity	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	11,45	24,05	This audience consists of households in the top 10-20% of a model predicting a purchase from BP. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Circle K Buyer Propensity	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	11,22	23,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Circle K. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Citgo Buyer Propensity	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	11,38	23,89	This audience consists of households in the top 10-20% of a model predicting a purchase from Citgo. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Convenience & Gas	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	17,11	35,94	This audience consists of households in the top 10-20% of a model predicting a purchase from the Convenience & Gas category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cumberland Farms Buyer Propensity	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	4,51	9,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Cumberland Farms. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Marathon Petroleum Buyer Propensity	Brand Propensities	Convenience & Gas	Oil & Gas		Household	Modeled	10,04	21,08	This audience consists of households in the top 10-20% of a model predicting a purchase from Marathon Petroleum. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wawa Buyer Propensity	Brand Propensities	Convenience & Gas	Food & Beverage	Oil & Gas	Household	Modeled	11,64	24,43	This audience consists of households in the top 10-20% of a model predicting a purchase from Wawa. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Crest Buyer Propensity	Brand Propensities	CPG	CPG		Household	Modeled	12,45	26,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Crest. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kraft Buyer Propensity	Brand Propensities	CPG	CPG		Household	Modeled	18,61	39,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Kraft. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
L'oreal Buyer Propensity	Brand Propensities	CPG	CPG		Household	Modeled	11,02	23,13	This audience consists of households in the top 10-20% of a model predicting a purchase from L'oreal. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
1-800-Flowers Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	13,24	27,81	This audience consists of households in the top 10-20% of a model predicting a purchase from 1-800-Flowers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AliExpress	Brand Propensities	Ecommerce	Retail		Household	Modeled	14,52	30,50	This audience consists of households in the top 10-20% of a model predicting a purchase from AliExpress. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Amazon Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	13,27	27,87	This audience consists of households in the top 10-20% of a model predicting a purchase from Amazon. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Craigslist Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	10,27	21,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Craigslist. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
delivery.com Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	15,40	32,33	This audience consists of households in the top 10-20% of a model predicting a purchase from delivery.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ebay Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	12,40	26,05	This audience consists of households in the top 10-20% of a model predicting a purchase from Ebay. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Etsy.com Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	12,38	26,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Etsy.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Go Daddy Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	14,07	29,55	This audience consists of households in the top 10-20% of a model predicting a purchase from Go Daddy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Google Wallet Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	35,74	75,05	This audience consists of households in the top 10-20% of a model predicting a purchase from Google Wallet. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Groupon Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	11,75	24,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Groupon. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
HSN Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	11,66	24,48	This audience consists of households in the top 10-20% of a model predicting a purchase from HSN. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jet.com Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	32,69	68,64	This audience consists of households in the top 10-20% of a model predicting a purchase from Jet.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jo-Ann Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	9,01	18,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Jo-Ann. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LinkedIn Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	14,27	29,97	This audience consists of households in the top 10-20% of a model predicting a purchase from LinkedIn. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Meijer Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	12,16	25,54	This audience consists of households in the top 10-20% of a model predicting a purchase from Meijer. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Mercari Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	12,13	25,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Mercari. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Office Depot Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	9,37	19,67	This audience consists of households in the top 10-20% of a model predicting a purchase from Office Depot. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Overstock.com Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	11,54	24,24	This audience consists of households in the top 10-20% of a model predicting a purchase from Overstock.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ProFlowers Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	13,03	27,37	This audience consists of households in the top 10-20% of a model predicting a purchase from ProFlowers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
QVC Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	11,78	24,75	This audience consists of households in the top 10-20% of a model predicting a purchase from QVC. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Shopify Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	15,86	33,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Shopify. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Snapfish Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	9,76	20,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Snapfish. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tiny Prints Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	46,21	97,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Tiny Prints. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
USPS Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	13,18	27,67	This audience consists of households in the top 10-20% of a model predicting a purchase from USPS. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zulily Buyer Propensity	Brand Propensities	Ecommerce	Retail		Household	Modeled	12,17	25,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Zulily. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Babbel.com	Brand Propensities	Education			Household	Modeled	16,20	34,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Babbel.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ABT Electronics	Brand Propensities	Electronics	Tech		Household	Modeled	12,44	26,12	This audience consists of households in the top 10-20% of a model predicting a purchase from ABT Electronics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Adobe Buyer Propensity	Brand Propensities	Electronics	Tech	Media & Entertainment	Household	Modeled	13,65	28,67	This audience consists of households in the top 10-20% of a model predicting a purchase from Adobe. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Apple Buyer Propensity	Brand Propensities	Electronics	Tech	Retail	Household	Modeled	12,92	27,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Apple. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
B&H Photo Video Buyer Propensity	Brand Propensities	Electronics	Tech	Retail	Household	Modeled	11,11	23,34	This audience consists of households in the top 10-20% of a model predicting a purchase from B&H Photo Video. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Best Buy Buyer Propensity	Brand Propensities	Electronics	Retail	Tech	Household	Modeled	12,93	27,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Best Buy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bose Buyer Propensity	Brand Propensities	Electronics	Tech	Retail	Household	Modeled	13,53	28,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Bose. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Crutchfield Buyer Propensity	Brand Propensities	Electronics	Retail	Tech	Household	Modeled	31,06	65,23	This audience consists of households in the top 10-20% of a model predicting a purchase from Crutchfield. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dell Buyer Propensity	Brand Propensities	Electronics	Tech	Retail	Household	Modeled	11,96	25,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Dell. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Garmin Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	10,81	22,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Garmin. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Geek Squad Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	12,68	26,63	This audience consists of households in the top 10-20% of a model predicting a purchase from Geek Squad. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
GoPro Buyer Propensity	Brand Propensities	Electronics	Tech	Media & Entertainment	Household	Modeled	12,27	25,76	This audience consists of households in the top 10-20% of a model predicting a purchase from GoPro. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
GreatCall Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	10,86	22,81	This audience consists of households in the top 10-20% of a model predicting a purchase from GreatCall. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
HP Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	9,29	19,50	This audience consists of households in the top 10-20% of a model predicting a purchase from HP. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
iRobot Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	11,44	24,03	This audience consists of households in the top 10-20% of a model predicting a purchase from iRobot. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lenovo Buyer Propensity	Brand Propensities	Electronics	Tech	Media & Entertainment	Household	Modeled	10,81	22,70	This audience consists of households in the top 10-20% of a model predicting a purchase from Lenovo. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LG Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	12,20	25,63	This audience consists of households in the top 10-20% of a model predicting a purchase from LG. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Microsoft Buyer Propensity	Brand Propensities	Electronics	Tech	Media & Entertainment	Household	Modeled	12,99	27,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Microsoft. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Microsoft Store Buyer Propensity	Brand Propensities	Electronics	Retail	Tech	Household	Modeled	12,98	27,25	This audience consists of households in the top 10-20% of a model predicting a purchase from Microsoft Store. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Motorola Buyer Propensity	Brand Propensities	Electronics	Tech	Telecom	Household	Modeled	12,96	27,22	This audience consists of households in the top 10-20% of a model predicting a purchase from Motorola. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Norton Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	9,50	19,96	This audience consists of households in the top 10-20% of a model predicting a purchase from Norton. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Otterbox Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	11,41	23,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Otterbox. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
P.C. Richard & Son Buyer Propensity	Brand Propensities	Electronics	Retail	Home	Household	Modeled	13,94	29,28	This audience consists of households in the top 10-20% of a model predicting a purchase from P.C. Richard and Son. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
RadioShack Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	32,43	68,09	This audience consists of households in the top 10-20% of a model predicting a purchase from RadioShack. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Samsung Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	12,73	26,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Samsung. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Skype Buyer Propensity	Brand Propensities	Electronics	Tech	Telecom	Household	Modeled	34,81	73,10	This audience consists of households in the top 10-20% of a model predicting a purchase from Skype. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sonos Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	11,67	24,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Sonos. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sony Buyer Propensity	Brand Propensities	Electronics	Tech	Media & Entertainment	Household	Modeled	15,26	32,06	This audience consists of households in the top 10-20% of a model predicting a purchase from Sony. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Toshiba Buyer Propensity	Brand Propensities	Electronics	Tech		Household	Modeled	50,11	105,23	This audience consists of households in the top 10-20% of a model predicting a purchase from Toshiba. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
American Express Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	11,79	24,77	This audience consists of households in the top 10-20% of a model predicting a purchase from American Express. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Coinbase Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	13,41	28,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Coinbase. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Experian	Brand Propensities	Financial	Financial Services		Household	Modeled	14,44	30,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Experian. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Express Scripts	Brand Propensities	Financial	Financial Services		Household	Modeled	11,71	24,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Express Scripts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
H&R Block Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	10,71	22,50	This audience consists of households in the top 10-20% of a model predicting a purchase from H&R Block. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Intuit Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	12,99	27,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Intuit. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LifeLock Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	4,69	9,84	This audience consists of households in the top 10-20% of a model predicting a purchase from LifeLock. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
PayPal Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	13,87	29,12	This audience consists of households in the top 10-20% of a model predicting a purchase from PayPal. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Raise.com Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	12,74	26,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Raise.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sezzle	Brand Propensities	Financial	Financial Services		Household	Modeled	16,16	33,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Sezzle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
StockX	Brand Propensities	Financial	Financial Services		Household	Modeled	14,25	29,92	This audience consists of households in the top 10-20% of a model predicting a purchase from StockX. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tax Preparation	Brand Propensities	Financial	Financial Services		Household	Modeled	13,30	27,94	This audience consists of households in the top 10-20% of a model predicting a purchase from the Tax Preparation category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Western Union Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	13,53	28,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Western Union. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Xoom Buyer Propensity	Brand Propensities	Financial	Financial Services		Household	Modeled	12,42	26,08	This audience consists of households in the top 10-20% of a model predicting a purchase from Xoom. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
7-Eleven Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	13,75	28,88	This audience consists of households in the top 10-20% of a model predicting a purchase from 7-Eleven. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Acme Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	10,14	21,30	This audience consists of households in the top 10-20% of a model predicting a purchase from Acme. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Albertsons Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	11,92	25,02	This audience consists of households in the top 10-20% of a model predicting a purchase from Albertsons. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blue Apron Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	15,84	33,27	This audience consists of households in the top 10-20% of a model predicting a purchase from Blue Apron. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Caviar Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	34,43	72,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Caviar. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cold Stone Creamery	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	16,76	35,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Cold Stone Creamery. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
CVS Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	12,49	26,22	This audience consists of households in the top 10-20% of a model predicting a purchase from CVS. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DAVIDsTEA Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	14,37	30,17	This audience consists of households in the top 10-20% of a model predicting a purchase from DAVIDsTEA. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DoorDash Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	14,17	29,75	This audience consists of households in the top 10-20% of a model predicting a purchase from DoorDash. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Drugstore.com Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	46,01	96,63	This audience consists of households in the top 10-20% of a model predicting a purchase from Drugstore.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Duane Reade Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	13,96	29,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Duane Reade. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Eat24 Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	33,83	71,05	This audience consists of households in the top 10-20% of a model predicting a purchase from Eat24. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
EveryPlate	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	18,59	39,04	This audience consists of households in the top 10-20% of a model predicting a purchase from EveryPlate. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Five Below Buyer Propensity	Brand Propensities	Food & Drugstore	Retail		Household	Modeled	11,49	24,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Five Below. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Food Lion Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	12,22	25,65	This audience consists of households in the top 10-20% of a model predicting a purchase from Food Lion. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fresh Direct Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Health & Beauty	Household	Modeled	16,23	34,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Fresh Direct. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Freshly Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Health & Beauty	Household	Modeled	17,14	36,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Freshly. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
GNC Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	12,25	25,73	This audience consists of households in the top 10-20% of a model predicting a purchase from GNC. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Godiva Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	12,76	26,79	This audience consists of households in the top 10-20% of a model predicting a purchase from Godiva. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Green Chef	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	17,52	36,79	This audience consists of households in the top 10-20% of a model predicting a purchase from Green Chef. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Grubhub Buyer Propensity	Brand Propensities	Food & Drugstore	QSR	Food & Beverage	Household	Modeled	13,23	27,79	This audience consists of households in the top 10-20% of a model predicting a purchase from Grubhub. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Harry & David Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	13,37	28,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Harry & David. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
HEB Grocery Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	11,97	25,15	This audience consists of households in the top 10-20% of a model predicting a purchase from HEB Grocery. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hello Fresh Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Health & Beauty	Household	Modeled	19,15	40,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Hello Fresh. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hint Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	11,76	24,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Hint. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Home Chef	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	19,01	39,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Home Chef. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Instacart Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	14,56	30,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Instacart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
King Arthur Flour Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	10,01	21,02	This audience consists of households in the top 10-20% of a model predicting a purchase from King Arthur Flour. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
KL Wine Merchants Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	13,67	28,71	This audience consists of households in the top 10-20% of a model predicting a purchase from KL Wine Merchants. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kroger Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	11,58	24,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Kroger. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lindt & Sprungli Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	27,04	56,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Lindt & Sprungli. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Marley Spoon	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	17,83	37,44	This audience consists of households in the top 10-20% of a model predicting a purchase from Marley Spoon. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
naturebox.com Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	31,10	65,31	This audience consists of households in the top 10-20% of a model predicting a purchase from naturebox.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nespresso Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	13,31	27,94	This audience consists of households in the top 10-20% of a model predicting a purchase from Nespresso. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Omaha Steaks Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	10,55	22,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Omaha Steaks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Peapod Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	17,85	37,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Peapod. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Postmates Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	36,38	76,40	This audience consists of households in the top 10-20% of a model predicting a purchase from Postmates. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Publix Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	11,48	24,10	This audience consists of households in the top 10-20% of a model predicting a purchase from Publix. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ralphs Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	14,02	29,43	This audience consists of households in the top 10-20% of a model predicting a purchase from Ralphs. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rite Aid Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	12,53	26,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Rite Aid. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Safeway Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	11,95	25,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Safeway. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Shipt Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	20,43	42,91	This audience consists of households in the top 10-20% of a model predicting a purchase from Shipt. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Stop & Shop Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Retail	Household	Modeled	11,44	24,02	This audience consists of households in the top 10-20% of a model predicting a purchase from Stop & Shop. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sun Basket	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	17,63	37,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Sun Basket. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Swanson Vitamins Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Health & Beauty	Household	Modeled	13,76	28,90	This audience consists of households in the top 10-20% of a model predicting a purchase from Swanson Vitamins. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Vitamin Shoppe Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	27,80	58,38	This audience consists of households in the top 10-20% of a model predicting a purchase from The Vitamin Shoppe. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Thrive Market Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage		Household	Modeled	18,37	38,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Thrive Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Vitamin World Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	10,33	21,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Vitamin World. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Vons Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Food & Beverage	Household	Modeled	13,14	27,60	This audience consists of households in the top 10-20% of a model predicting a purchase from Vons. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Walgreens Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	12,07	25,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Walgreens. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wegmans Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Retail	Household	Modeled	11,11	23,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Wegmans. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Weight Watchers International Buyer Propensity	Brand Propensities	Food & Drugstore	Health & Beauty	Fitness	Household	Modeled	13,73	28,83	This audience consists of households in the top 10-20% of a model predicting a purchase from Weight Watchers International. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Whole Foods Market Buyer Propensity	Brand Propensities	Food & Drugstore	Retail	Health & Beauty	Household	Modeled	13,56	28,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Whole Foods Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wine.com Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Alcoholic Beverages	Household	Modeled	13,63	28,62	This audience consists of households in the top 10-20% of a model predicting a purchase from Wine.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Winn-Dixie Buyer Propensity	Brand Propensities	Food & Drugstore	Food & Beverage	Retail	Household	Modeled	11,99	25,19	This audience consists of households in the top 10-20% of a model predicting a purchase from Winn-Dixie. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
1-800-Contacts Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,60	24,36	This audience consists of households in the top 10-20% of a model predicting a purchase from 1-800-Contacts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
24 Hour Fitness Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,78	24,74	This audience consists of households in the top 10-20% of a model predicting a purchase from 24 Hour Fitness. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Amwell Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,23	21,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Amwell. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Anastasia Beverly Hills Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,11	23,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Anastasia Beverly Hills. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Anytime Fitness	Brand Propensities	Health & Beauty	Fitness		Household	Modeled	13,22	27,75	This audience consists of households in the top 10-20% of a model predicting a purchase from Anytime Fitness. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AVON Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,81	24,81	This audience consists of households in the top 10-20% of a model predicting a purchase from AVON. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bare Escentuals Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	27,97	58,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Bare Escentuals. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bareminerals Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	17,77	37,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Bareminerals. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Beachbody Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	23,01	48,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Beachbody. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Beauty Bar Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,54	22,14	This audience consists of households in the top 10-20% of a model predicting a purchase from Beauty Bar. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
BetterHelp Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,95	27,20	This audience consists of households in the top 10-20% of a model predicting a purchase from BetterHelp. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Birchbox Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,31	25,85	This audience consists of households in the top 10-20% of a model predicting a purchase from Birchbox. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bodybuilding.com Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	12,66	26,59	This audience consists of households in the top 10-20% of a model predicting a purchase from Bodybuilding.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
CityMD Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,33	25,90	This audience consists of households in the top 10-20% of a model predicting a purchase from CityMD. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Clinique Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,19	23,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Clinique. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Crunch Fitness Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,70	22,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Crunch Fitness. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DermStore Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	13,32	27,97	This audience consists of households in the top 10-20% of a model predicting a purchase from DermStore. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Doctor On Demand Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	4,45	9,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Doctor On Demand. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dollar Shave Club Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	13,26	27,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Dollar Shave Club. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
e.l.f. Cosmetics Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	20,78	43,65	This audience consists of households in the top 10-20% of a model predicting a purchase from e.l.f. Cosmetics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Equinox Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	12,58	26,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Equinox. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
eSalon Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	26,93	56,56	This audience consists of households in the top 10-20% of a model predicting a purchase from eSalon. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Estee Lauder Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,37	25,98	This audience consists of households in the top 10-20% of a model predicting a purchase from Estee Lauder. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fitbit Buyer Propensity	Brand Propensities	Health & Beauty	Fitness	Health & Beauty	Household	Modeled	13,14	27,60	This audience consists of households in the top 10-20% of a model predicting a purchase from Fitbit. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Free People	Brand Propensities	Health & Beauty	Retail		Household	Modeled	16,09	33,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Free People. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Function of Beauty Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,51	24,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Function of Beauty. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gillette Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	9,77	20,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Gillette. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Glasses USA	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,75	24,67	This audience consists of households in the top 10-20% of a model predicting a purchase from Glasses USA. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Glasses.com	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	14,71	30,89	This audience consists of households in the top 10-20% of a model predicting a purchase from Glasses.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Glossier Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,40	26,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Glossier. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gold's Gym Buyer Propensity	Brand Propensities	Health & Beauty	Fitness	Health & Beauty	Household	Modeled	9,35	19,64	This audience consists of households in the top 10-20% of a model predicting a purchase from Gold's Gym. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Harry's Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,75	24,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Harry's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Headspace Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,96	25,12	This audience consists of households in the top 10-20% of a model predicting a purchase from Headspace. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Heartland Dental Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	4,64	9,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Heartland Dental. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Herbalife Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	13,39	28,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Herbalife. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ilia Beauty Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,52	22,08	This audience consists of households in the top 10-20% of a model predicting a purchase from Ilia Beauty. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Inkbox Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,00	25,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Inkbox. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ipsy Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,79	22,65	This audience consists of households in the top 10-20% of a model predicting a purchase from Ipsy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
KIEHLS Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	13,48	28,31	This audience consists of households in the top 10-20% of a model predicting a purchase from KIEHLS. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kylie Cosmetics Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,14	25,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Kylie Cosmetics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lancome Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,02	23,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Lancome. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LensCrafters Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,11	21,22	This audience consists of households in the top 10-20% of a model predicting a purchase from LensCrafters. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lola Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	14,25	29,92	This audience consists of households in the top 10-20% of a model predicting a purchase from Lola. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
M.A.C Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,86	22,80	This audience consists of households in the top 10-20% of a model predicting a purchase from M.A.C. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Madison-Reed Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,38	26,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Madison-Reed. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Manscaped Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,64	24,45	This audience consists of households in the top 10-20% of a model predicting a purchase from Manscaped. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Mary Kay Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	22,02	46,25	This audience consists of households in the top 10-20% of a model predicting a purchase from Mary Kay. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Massage Envy Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,89	24,98	This audience consists of households in the top 10-20% of a model predicting a purchase from Massage Envy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Maybelline Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,80	22,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Maybelline. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MedExpress Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	4,33	9,10	This audience consists of households in the top 10-20% of a model predicting a purchase from MedExpress. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Mirror Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,10	23,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Mirror. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MyFitnessPal Buyer Propensity	Brand Propensities	Health & Beauty	Fitness	Health & Beauty	Household	Modeled	9,32	19,58	This audience consists of households in the top 10-20% of a model predicting a purchase from MyFitnessPal. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Neutrogena Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	16,18	33,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Neutrogena. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Noom Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	11,55	24,26	This audience consists of households in the top 10-20% of a model predicting a purchase from Noom. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nutrafol Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,05	25,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Nutrafol. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Nutrisystem Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	12,33	25,89	This audience consists of households in the top 10-20% of a model predicting a purchase from Nutrisystem. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pearle Vision Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,43	24,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Pearle Vision. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Peloton Buyer Propensity	Brand Propensities	Health & Beauty	Fitness	Health & Beauty	Household	Modeled	12,11	25,42	This audience consists of households in the top 10-20% of a model predicting a purchase from Peloton. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
PillPack Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	9,86	20,71	This audience consists of households in the top 10-20% of a model predicting a purchase from PillPack. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Planet Fitness Buyer Propensity	Brand Propensities	Health & Beauty	Fitness		Household	Modeled	9,14	19,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Planet Fitness. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Puritan's Pride Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	9,90	20,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Puritan's Pride. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Quest Diagnostics Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,65	24,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Quest Diagnostics. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Scentsy Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,83	22,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Scentsy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sephora Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	13,20	27,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Sephora. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
SkinCareRx Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	31,62	66,41	This audience consists of households in the top 10-20% of a model predicting a purchase from SkinCareRx. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Skinstore.com Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,89	22,87	This audience consists of households in the top 10-20% of a model predicting a purchase from Skinstore.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
SmileDirectClub Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Professional Services	Household	Modeled	12,19	25,59	This audience consists of households in the top 10-20% of a model predicting a purchase from SmileDirectClub. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
soul-cycle.com Buyer Propensity	Brand Propensities	Health & Beauty	Fitness	Health & Beauty	Household	Modeled	29,94	62,88	This audience consists of households in the top 10-20% of a model predicting a purchase from soul-cycle.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Supercuts Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,19	23,51	This audience consists of households in the top 10-20% of a model predicting a purchase from Supercuts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Body Shop Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	11,06	23,22	This audience consists of households in the top 10-20% of a model predicting a purchase from The Body Shop. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Honest Company Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	40,73	85,53	This audience consists of households in the top 10-20% of a model predicting a purchase from The Honest Company. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ULTA Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	15,03	31,57	This audience consists of households in the top 10-20% of a model predicting a purchase from ULTA. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Urban Decay Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	10,14	21,29	This audience consists of households in the top 10-20% of a model predicting a purchase from Urban Decay. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Visionworks Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty		Household	Modeled	9,41	19,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Visionworks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
YMCA Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	8,82	18,52	This audience consists of households in the top 10-20% of a model predicting a purchase from YMCA. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
YogaWorks Buyer Propensity	Brand Propensities	Health & Beauty	Health & Beauty	Fitness	Household	Modeled	13,15	27,62	This audience consists of households in the top 10-20% of a model predicting a purchase from YogaWorks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Allergan	Brand Propensities	Health Supplements			Household	Modeled	15,95	33,49	This audience consists of households in the top 10-20% of a model predicting a purchase from Allergan. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pharmacies	Brand Propensities	Health Supplements	Health & Beauty		Household	Modeled	11,74	24,65	This audience consists of households in the top 10-20% of a model predicting a purchase from the Pharmacies category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Landscaping	Brand Propensities	Home & Garden	Professional Services		Household	Modeled	11,15	23,42	This audience consists of households in the top 10-20% of a model predicting a purchase from the Landscaping category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ace Hardware Corporation Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,44	19,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Ace Hardware Corporation. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
ADT Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,12	23,35	This audience consists of households in the top 10-20% of a model predicting a purchase from ADT. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Angie's List Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Professional Services	Household	Modeled	13,15	27,62	This audience consists of households in the top 10-20% of a model predicting a purchase from Angie's List. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Arhaus Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	10,82	22,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Arhaus. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ashley Furniture Homestore Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	10,62	22,31	This audience consists of households in the top 10-20% of a model predicting a purchase from Ashley Furniture Homestore. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bath & Body Works Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Health & Beauty	Household	Modeled	10,34	21,70	This audience consists of households in the top 10-20% of a model predicting a purchase from Bath & Body Works. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bed Bath & Beyond Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	10,22	21,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Bed Bath & Beyond. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blick Art Materials Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,34	21,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Blick Art Materials. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blinds.com Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	9,75	20,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Blinds.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bosch Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,64	22,35	This audience consists of households in the top 10-20% of a model predicting a purchase from Bosch. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Brinks Home Security Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,44	21,92	This audience consists of households in the top 10-20% of a model predicting a purchase from Brinks Home Security. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
BrylaneHome Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,51	24,18	This audience consists of households in the top 10-20% of a model predicting a purchase from BrylaneHome. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Build.com Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	12,22	25,67	This audience consists of households in the top 10-20% of a model predicting a purchase from Build.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Casper Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	12,13	25,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Casper. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Christmas Tree Shops Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,16	21,34	This audience consists of households in the top 10-20% of a model predicting a purchase from Christmas Tree Shops. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Crate & Barrel Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	12,66	26,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Crate & Barrel. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cuisinart Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	12,31	25,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Cuisinart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dewalt Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	9,42	19,78	This audience consists of households in the top 10-20% of a model predicting a purchase from Dewalt. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Frontpoint Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	12,15	25,52	This audience consists of households in the top 10-20% of a model predicting a purchase from Frontpoint. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
GE Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	12,36	25,95	This audience consists of households in the top 10-20% of a model predicting a purchase from GE. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Harbor Freight Tools Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	3,90	8,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Harbor Freight Tools. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hobby Lobby Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	4,61	9,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Hobby Lobby. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Home Depot Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,55	20,06	This audience consists of households in the top 10-20% of a model predicting a purchase from Home Depot. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
HomeGoods Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	10,20	21,43	This audience consists of households in the top 10-20% of a model predicting a purchase from HomeGoods. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Houzz Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,64	22,35	This audience consists of households in the top 10-20% of a model predicting a purchase from Houzz. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
IKEA Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	13,02	27,33	This audience consists of households in the top 10-20% of a model predicting a purchase from IKEA. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Joss & Main Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	24,19	50,80	This audience consists of households in the top 10-20% of a model predicting a purchase from Joss & Main. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Keurig Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,53	22,12	This audience consists of households in the top 10-20% of a model predicting a purchase from Keurig. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kirkland's Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,74	20,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Kirkland's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kitchenaid Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,01	21,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Kitchenaid. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kohler Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,83	22,75	This audience consists of households in the top 10-20% of a model predicting a purchase from Kohler. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
La-Z-Boy (LZB)	Brand Propensities	Home & Household Goods	Home		Household	Modeled	11,58	24,31	This audience consists of households in the top 10-20% of a model predicting a purchase from La-Z-Boy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lowe's Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,10	21,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Lowe's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Mattress Firm Buyer Propensity	Brand Propensities	Home & Household Goods	Home	Retail	Household	Modeled	11,92	25,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Mattress Firm. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Menard Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,52	19,99	This audience consists of households in the top 10-20% of a model predicting a purchase from Menard. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Michaels Stores Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	4,55	9,55	This audience consists of households in the top 10-20% of a model predicting a purchase from Michaels Stores. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Moen Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	11,17	23,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Moen. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Paper Source Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	12,79	26,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Paper Source. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pier 1 Imports Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	10,88	22,86	This audience consists of households in the top 10-20% of a model predicting a purchase from Pier 1 Imports. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pottery Barn Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	12,40	26,05	This audience consists of households in the top 10-20% of a model predicting a purchase from Pottery Barn. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pottery Barn Kids Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	44,54	93,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Pottery Barn Kids. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Protection One Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,30	19,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Protection One. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Purple Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,16	23,44	This audience consists of households in the top 10-20% of a model predicting a purchase from Purple. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Raymour & Flanigan Buyer Propensity	Brand Propensities	Home & Household Goods	Retail	Home	Household	Modeled	11,50	24,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Raymour & Flanigan. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rent-A-Center Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	13,09	27,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Rent-A-Center. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Restoration Hardware Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	15,58	32,72	This audience consists of households in the top 10-20% of a model predicting a purchase from Restoration Hardware. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rooms To Go Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,77	24,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Rooms To Go. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Saatva	Brand Propensities	Home & Household Goods	Home		Household	Modeled	14,60	30,65	This audience consists of households in the top 10-20% of a model predicting a purchase from Saatva. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Serta Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	12,64	26,54	This audience consists of households in the top 10-20% of a model predicting a purchase from Serta. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sleep Number Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,15	21,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Sleep Number. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Solar CIty Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,69	24,55	This audience consists of households in the top 10-20% of a model predicting a purchase from Solar City. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sur La Table Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,05	23,21	This audience consists of households in the top 10-20% of a model predicting a purchase from Sur La Table. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Container Store Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	13,29	27,91	This audience consists of households in the top 10-20% of a model predicting a purchase from The Container Store. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Home Depot Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,80	20,57	This audience consists of households in the top 10-20% of a model predicting a purchase from The Home Depot. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tractor Supply Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	4,22	8,85	This audience consists of households in the top 10-20% of a model predicting a purchase from Tractor Supply. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
True Value Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,48	19,91	This audience consists of households in the top 10-20% of a model predicting a purchase from True Value. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
TruGreen Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	3,36	7,06	This audience consists of households in the top 10-20% of a model predicting a purchase from TruGreen. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tuesday Morning Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	9,02	18,94	This audience consists of households in the top 10-20% of a model predicting a purchase from Tuesday Morning. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
U-haul Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,63	24,42	This audience consists of households in the top 10-20% of a model predicting a purchase from U-haul. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Vistaprint Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	10,55	22,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Vistaprint. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wayfair Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,65	24,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Wayfair. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
West Elm Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	14,15	29,72	This audience consists of households in the top 10-20% of a model predicting a purchase from West Elm. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Whirlpool Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	11,52	24,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Whirlpool. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Williams-Sonoma Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	12,91	27,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Williams-Sonoma. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
World Market Buyer Propensity	Brand Propensities	Home & Household Goods	Retail		Household	Modeled	11,68	24,53	This audience consists of households in the top 10-20% of a model predicting a purchase from World Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Yankee Candle Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	10,60	22,25	This audience consists of households in the top 10-20% of a model predicting a purchase from Yankee Candle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zoro Tools Buyer Propensity	Brand Propensities	Home & Household Goods	Home		Household	Modeled	4,42	9,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Zoro Tools. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Allstate Insurance Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	10,71	22,49	This audience consists of households in the top 10-20% of a model predicting a purchase from Allstate Insurance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Embrace Pet Insurance Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	12,02	25,24	This audience consists of households in the top 10-20% of a model predicting a purchase from Embrace Pet Insurance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Farmers Insurance Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	11,75	24,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Farmers Insurance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Geico Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	11,32	23,76	This audience consists of households in the top 10-20% of a model predicting a purchase from Geico. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kaiser Permanente Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	11,76	24,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Kaiser Permanente. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Lemonade Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	13,66	28,69	This audience consists of households in the top 10-20% of a model predicting a purchase from Lemonade. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Progressive Casualty Insurance Company Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	15,53	32,60	This audience consists of households in the top 10-20% of a model predicting a purchase from Progressive Casualty Insurance Company. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Safeco Insurance Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	9,62	20,19	This audience consists of households in the top 10-20% of a model predicting a purchase from Safeco Insurance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
State Farm Insurance Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	3,88	8,14	This audience consists of households in the top 10-20% of a model predicting a purchase from State Farm Insurance. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Travelers Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	10,49	22,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Travelers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
United Services Automobile Association Buyer Propensity	Brand Propensities	Insurance	Financial Services		Household	Modeled	34,97	73,43	This audience consists of households in the top 10-20% of a model predicting a purchase from United Services Automobile Association. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cartier Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	13,20	27,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Cartier. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Claire's Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	9,82	20,63	This audience consists of households in the top 10-20% of a model predicting a purchase from Claire's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
David Yurman Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	11,17	23,46	This audience consists of households in the top 10-20% of a model predicting a purchase from David Yurman. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jared Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	11,63	24,42	This audience consists of households in the top 10-20% of a model predicting a purchase from Jared. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kay Jewelers Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	10,96	23,01	This audience consists of households in the top 10-20% of a model predicting a purchase from Kay Jewelers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Omega Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	10,45	21,94	This audience consists of households in the top 10-20% of a model predicting a purchase from Omega. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Zales Buyer Propensity	Brand Propensities	Jewelry	Retail		Household	Modeled	5,15	10,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Zales. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
AbcMouse Buyer Propensity	Brand Propensities	Kids Products	Education		Household	Modeled	10,08	21,17	This audience consists of households in the top 10-20% of a model predicting a purchase from AbcMouse. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Aeropostale Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	10,57	22,20	This audience consists of households in the top 10-20% of a model predicting a purchase from Aeropostale. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
buybuy BABY Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	13,47	28,30	This audience consists of households in the top 10-20% of a model predicting a purchase from buybuy BABY. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Care.com Buyer Propensity	Brand Propensities	Kids Products	Professional Services		Household	Modeled	12,62	26,50	This audience consists of households in the top 10-20% of a model predicting a purchase from Care.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Diapers.com Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	29,61	62,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Diapers.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Disney Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	32,85	68,98	This audience consists of households in the top 10-20% of a model predicting a purchase from Disney. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fisher-Price Buyer Propensity	Brand Propensities	Kids Products	Home		Household	Modeled	15,46	32,47	This audience consists of households in the top 10-20% of a model predicting a purchase from Fisher-Price. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Freshly Picked Buyer Propensity	Brand Propensities	Kids Products	Home		Household	Modeled	9,99	20,98	This audience consists of households in the top 10-20% of a model predicting a purchase from Freshly Picked. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gerber Buyer Propensity	Brand Propensities	Kids Products	Home		Household	Modeled	11,65	24,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Gerber. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Happiest Baby Buyer Propensity	Brand Propensities	Kids Products	Home		Household	Modeled	11,33	23,79	This audience consists of households in the top 10-20% of a model predicting a purchase from Happiest Baby. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Janie and Jack Buyer Propensity	Brand Propensities	Kids Products	Home		Household	Modeled	12,18	25,59	This audience consists of households in the top 10-20% of a model predicting a purchase from Janie and Jack. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kidizen Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	11,46	24,06	This audience consists of households in the top 10-20% of a model predicting a purchase from Kidizen. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
LEGO Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	10,63	22,32	This audience consists of households in the top 10-20% of a model predicting a purchase from LEGO. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Little Passport Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	10,82	22,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Little Passport. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Party City Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	11,74	24,66	This audience consists of households in the top 10-20% of a model predicting a purchase from Party City. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sittercity Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	13,40	28,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Sittercity. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Children's Place Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	32,02	67,24	This audience consists of households in the top 10-20% of a model predicting a purchase from The Children's Place. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Little Gym Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	11,20	23,51	This audience consists of households in the top 10-20% of a model predicting a purchase from The Little Gym. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Toys R Us Buyer Propensity	Brand Propensities	Kids Products	Retail		Household	Modeled	37,40	78,54	This audience consists of households in the top 10-20% of a model predicting a purchase from Toys R Us. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Alamo Drafthouse Cinema	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,18	27,68	This audience consists of households in the top 10-20% of a model predicting a purchase from Alamo Drafthouse Cinema. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ancestry.com Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment	Retail	Household	Modeled	11,85	24,89	This audience consists of households in the top 10-20% of a model predicting a purchase from Ancestry.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Audiobooks Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,74	22,55	This audience consists of households in the top 10-20% of a model predicting a purchase from Audiobooks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Barnes & Noble Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment	Retail	Household	Modeled	11,21	23,53	This audience consists of households in the top 10-20% of a model predicting a purchase from Barnes & Noble. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blurb Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,36	21,76	This audience consists of households in the top 10-20% of a model predicting a purchase from Blurb. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bumble Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,01	23,12	This audience consists of households in the top 10-20% of a model predicting a purchase from Bumble. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chatbooks Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	9,81	20,59	This audience consists of households in the top 10-20% of a model predicting a purchase from Chatbooks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DraftKings Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,52	28,39	This audience consists of households in the top 10-20% of a model predicting a purchase from DraftKings. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Duolingo Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,47	22,00	This audience consists of households in the top 10-20% of a model predicting a purchase from Duolingo. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Eventbrite Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,25	25,73	This audience consists of households in the top 10-20% of a model predicting a purchase from Eventbrite. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fandango Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,62	24,41	This audience consists of households in the top 10-20% of a model predicting a purchase from Fandango. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Financial Times Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,34	25,91	This audience consists of households in the top 10-20% of a model predicting a purchase from Financial Times. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gamestop Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	9,51	19,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Gamestop. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Google Play Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,03	21,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Google Play. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Guitar Center	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,59	26,43	This audience consists of households in the top 10-20% of a model predicting a purchase from Guitar Center. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Half Price Books Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	9,79	20,56	This audience consists of households in the top 10-20% of a model predicting a purchase from Half Price Books. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Hunt A Killer Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,03	21,07	This audience consists of households in the top 10-20% of a model predicting a purchase from Hunt A Killer. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
iTunes Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	49,37	103,69	This audience consists of households in the top 10-20% of a model predicting a purchase from iTunes. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Linkedin Learning Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	14,27	29,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Lynda. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Live Nation Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,53	26,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Live Nation. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Los Angeles Times Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,45	24,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Los Angeles Times. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
MasterClass Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,31	23,74	This audience consists of households in the top 10-20% of a model predicting a purchase from MasterClass. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Match.com Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,50	26,24	This audience consists of households in the top 10-20% of a model predicting a purchase from Match.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Music Streaming	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,09	27,48	This audience consists of households in the top 10-20% of a model predicting a purchase from the Music Streaming category. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
NY Times Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,88	24,95	This audience consists of households in the top 10-20% of a model predicting a purchase from Ny Times. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
OkCupid Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,93	29,24	This audience consists of households in the top 10-20% of a model predicting a purchase from OkCupid. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
OurTime Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,02	27,34	This audience consists of households in the top 10-20% of a model predicting a purchase from OurTime. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pandora Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,21	21,44	This audience consists of households in the top 10-20% of a model predicting a purchase from Pandora. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
People Magazine Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	3,31	6,94	This audience consists of households in the top 10-20% of a model predicting a purchase from People Magazine. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pic Monkey	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	14,20	29,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Pic Monkey. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
pokerstars.net Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	37,59	78,94	This audience consists of households in the top 10-20% of a model predicting a purchase from pokerstars.net. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Quizlet Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,49	22,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Quizlet. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Regal Cinemas Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,47	24,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Regal Cinemas. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Roblox	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,69	26,64	This audience consists of households in the top 10-20% of a model predicting a purchase from Roblox. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Rosetta Stone Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,81	22,71	This audience consists of households in the top 10-20% of a model predicting a purchase from Rosetta Stone. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Scholastic Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,65	26,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Scholastic. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
SeatGeek	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	14,34	30,11	This audience consists of households in the top 10-20% of a model predicting a purchase from SeatGeek. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Shutterfly Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	9,65	20,27	This audience consists of households in the top 10-20% of a model predicting a purchase from Shutterfly. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
SiriusXM Radio Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,88	24,94	This audience consists of households in the top 10-20% of a model predicting a purchase from SiriusXM Radio. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sony Network Entertainment International Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	23,31	48,95	This audience consists of households in the top 10-20% of a model predicting a purchase from Sony Network Entertainment International. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Spotify Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	12,44	26,13	This audience consists of households in the top 10-20% of a model predicting a purchase from Spotify. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Steam Community Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	32,81	68,90	This audience consists of households in the top 10-20% of a model predicting a purchase from Steam Community. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
StubHub Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,71	22,49	This audience consists of households in the top 10-20% of a model predicting a purchase from StubHub. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Economist Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	11,82	24,82	This audience consists of households in the top 10-20% of a model predicting a purchase from The Economist. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Wall Street Journal Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,04	21,09	This audience consists of households in the top 10-20% of a model predicting a purchase from The Wall Street Journal. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
The Washington Post Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	13,83	29,04	This audience consists of households in the top 10-20% of a model predicting a purchase from The Washington Post. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ticketfly Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	25,60	53,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Ticketfly. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Ticketmaster Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	10,05	21,11	This audience consists of households in the top 10-20% of a model predicting a purchase from Ticketmaster. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
wwe.com Buyer Propensity	Brand Propensities	Media & Entertainment	Media & Entertainment		Household	Modeled	24,95	52,41	This audience consists of households in the top 10-20% of a model predicting a purchase from wwe.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Goodwill	Brand Propensities	Non-Profits	Non-Profit		Household	Modeled	11,71	24,59	This audience consists of households in the top 10-20% of a model predicting a purchase from Goodwill. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
World Vision	Brand Propensities	Non-Profits	Non-Profit		Household	Modeled	11,41	23,97	This audience consists of households in the top 10-20% of a model predicting a purchase from World Vision. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Gander Mountain	Brand Propensities	Outerwear	Retail		Household	Modeled	10,18	21,37	This audience consists of households in the top 10-20% of a model predicting a purchase from Gander Mountain. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Active & Tech-Savvy	Brand Propensities	Personas	Tech		Household	Modeled	10,27	21,57	This audience consists of households in the top 10-20% of a model predicting a purchase from Active & Tech-Savvy. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Big Chain Shoppers	Brand Propensities	Personas	Retail		Household	Modeled	12,01	25,22	This audience consists of households in the top 10-20% of a model predicting a purchase from Big Chain Shoppers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Black Friday Buyer Propensity	Brand Propensities	Personas	Holiday	Retail	Household	Modeled	10,51	22,08	This audience consists of households in the top 10-20% of a model predicting a purchase from Black Friday. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Connected Techies	Brand Propensities	Personas	Tech		Household	Modeled	4,68	9,83	This audience consists of households in the top 10-20% of a model predicting a purchase from Connected Techies. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cyber Monday Buyer Propensity	Brand Propensities	Personas	Holiday	Retail	Household	Modeled	11,83	24,85	This audience consists of households in the top 10-20% of a model predicting a purchase from Cyber Monday. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Digital Checkout Buyers	Brand Propensities	Personas	Retail		Household	Modeled	4,59	9,64	This audience consists of households in the top 10-20% of a model predicting a purchase from Digital Checkout Buyers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
DRTV Home Shoppers	Brand Propensities	Personas	Retail		Household	Modeled	10,44	21,92	This audience consists of households in the top 10-20% of a model predicting a purchase from DRTV Home Shoppers. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Fashionistas	Brand Propensities	Personas	Health & Beauty	Retail	Household	Modeled	11,39	23,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Fashionistas. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Kitchen and Homebodies	Brand Propensities	Personas	Home		Household	Modeled	2,94	6,18	This audience consists of households in the top 10-20% of a model predicting a purchase from Kitchen and Homebodies. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Suburban Home	Brand Propensities	Personas	Home		Household	Modeled	10,84	22,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Suburban Home. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Upscale Living	Brand Propensities	Personas	Home		Household	Modeled	11,66	24,49	This audience consists of households in the top 10-20% of a model predicting a purchase from Upscale Living. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Urban Commuters	Brand Propensities	Personas	Home		Household	Modeled	3,80	7,98	This audience consists of households in the top 10-20% of a model predicting a purchase from Urban Commuters. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
1-800-PetMeds Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	11,57	24,31	This audience consists of households in the top 10-20% of a model predicting a purchase from 1-800-PetMeds. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chewy.com Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	14,25	29,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Chewy.com. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Petco Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	34,56	72,58	This audience consists of households in the top 10-20% of a model predicting a purchase from Petco. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
PetSmart Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	12,25	25,73	This audience consists of households in the top 10-20% of a model predicting a purchase from PetSmart. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
PrettyLitter	Brand Propensities	Pets	Pet		Household	Modeled	17,84	37,46	This audience consists of households in the top 10-20% of a model predicting a purchase from PrettyLitter. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Purina Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	11,58	24,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Purina. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Royal Canin Buyer Propensity	Brand Propensities	Pets	Pet		Household	Modeled	11,89	24,97	This audience consists of households in the top 10-20% of a model predicting a purchase from Royal Canin. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Auntie Anne's Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	8,05	16,91	This audience consists of households in the top 10-20% of a model predicting a purchase from Auntie Anne's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blue Bottle Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	12,30	25,84	This audience consists of households in the top 10-20% of a model predicting a purchase from Blue Bottle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Carl's Jr. Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	12,60	26,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Carl's Jr. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Chipotle Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	12,45	26,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Chipotle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Cinnabon Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	11,78	24,74	This audience consists of households in the top 10-20% of a model predicting a purchase from Cinnabon. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Del Taco	Brand Propensities	QSR	Food & Beverage		Household	Modeled	15,15	31,81	This audience consists of households in the top 10-20% of a model predicting a purchase from Del Taco. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Domino's Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	12,12	25,45	This audience consists of households in the top 10-20% of a model predicting a purchase from Domino's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Dunkin Donuts Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	14,12	29,66	This audience consists of households in the top 10-20% of a model predicting a purchase from Dunkin Donuts. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Golden Corral Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	11,39	23,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Golden Corral. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jamba Juice Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	12,32	25,87	This audience consists of households in the top 10-20% of a model predicting a purchase from Jamba Juice. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Jersey Mike's Subs Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	10,52	22,09	This audience consists of households in the top 10-20% of a model predicting a purchase from Jersey Mike's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
KFC Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	16,30	34,23	This audience consists of households in the top 10-20% of a model predicting a purchase from Kentucky Fried Chicken. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Krispy Kreme Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	11,51	24,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Krispy Kreme. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Panera Bread Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	12,94	27,17	This audience consists of households in the top 10-20% of a model predicting a purchase from Panera Bread. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Papa John's Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	11,50	24,16	This audience consists of households in the top 10-20% of a model predicting a purchase from Papa John's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Pizza Hut Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	12,87	27,03	This audience consists of households in the top 10-20% of a model predicting a purchase from Pizza Hut. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Sbarro Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	10,76	22,60	This audience consists of households in the top 10-20% of a model predicting a purchase from Sbarro. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Starbucks Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	13,08	27,46	This audience consists of households in the top 10-20% of a model predicting a purchase from Starbucks. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Tim Hortons Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	11,18	23,48	This audience consists of households in the top 10-20% of a model predicting a purchase from Tim Hortons. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
White Castle Buyer Propensity	Brand Propensities	QSR	QSR		Household	Modeled	13,31	27,95	This audience consists of households in the top 10-20% of a model predicting a purchase from White Castle. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Wingstop Buyer Propensity	Brand Propensities	QSR	QSR	Food & Beverage	Household	Modeled	11,79	24,77	This audience consists of households in the top 10-20% of a model predicting a purchase from Wingstop. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Applebee's Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	10,61	22,28	This audience consists of households in the top 10-20% of a model predicting a purchase from Applebee's. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bahama Breeze Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	11,88	24,94	This audience consists of households in the top 10-20% of a model predicting a purchase from Bahama Breeze. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Baja Fresh Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	11,39	23,93	This audience consists of households in the top 10-20% of a model predicting a purchase from Baja Fresh. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Barcelona Wine Bar Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	11,63	24,42	This audience consists of households in the top 10-20% of a model predicting a purchase from Barcelona Wine Bar. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Blaze Pizza	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	16,26	34,15	This audience consists of households in the top 10-20% of a model predicting a purchase from Blaze Pizza. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bob Evans Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	10,15	21,32	This audience consists of households in the top 10-20% of a model predicting a purchase from Bob Evans. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Bonefish Grill Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	10,16	21,33	This audience consists of households in the top 10-20% of a model predicting a purchase from Bonefish Grill. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Boston Market Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	11,45	24,04	This audience consists of households in the top 10-20% of a model predicting a purchase from Boston Market. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
Buffalo Wild Wings Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage		Household	Modeled	10,11	21,23	This audience consists of households in the top 10-20% of a model predicting a purchase from Buffalo Wild Wings. The model is built using brand-specific e-commerce data as a study group, that is then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics.
By CHLOE Buyer Propensity	Brand Propensities	Restaurants & Dining	Food & Beverage