A high-end bedding marketer that relied heavily on direct mail for lead generation struggled with converting responders into paying customers. They had a long multistep order process which required an in-home consultation, causing many leads to fall out of the sales funnel.


The client wanted to improve their targeting strategy by promoting only those prospects most likely to result in profitable, paying customers – without jeopardizing the overall performance of their acquisition program.


Alliant recommended a custom optimization model capable of predicting the profitability, or lack there of, of every prospect in the campaign. The retailer could then use this insight to proactively suppress poor performers from the campaign and save wasted direct mail dollars.


By mapping the data to Alliant’s cooperative of consumer transactional, demographic, lifestyle and socioeconomic data — the team was able to the unique makeup of each segment and build the model capable of identifying similar consumers.


The client saw a 30% increase in ROI for their direct mail efforts.




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