How custom audiences bridge the patient and provider data divider

Healthcare and pharma marketers have traditionally approached DTC and HCP marketing as two different disciplines, each built on its own data. Patient strategies might begin with claims, condition indicators, demographics, or lifestyle data. Provider strategies typically start with NPI, specialty, prescribing data, or professional attributes.  

That separation is breaking down. As marketers look across the full patient and provider journey, there’s growing value in bringing both audiences into one cohesive data framework: a foundation that preserves the signals unique to each while adding a shared layer of consumer context. 

Those healthcare signals remain essential. But patients and providers are also consumers, shaped by what they buy, how they live, what matters to them, how they prefer to engage, and what motivates them to act.  

Adding that broader consumer intelligence to healthcare audience design creates an opportunity to move beyond static, one-size-fits-all segments toward audiences built around the specific goals of a campaign. 

That’s where custom audiences become especially powerful.  

Go beyond what you already know

Most healthcare marketers can define an audience by diagnosis, treatment stage, specialty, or prescribing behavior. Fewer can describe them by what they buy, what motivates them, or what early signals show up before a healthcare decision ever gets made. That’s not a knock on the industry. It’s a reflection of how audience data has historically been built in this space. 

Ask yourself what a truly robust view of your audience would look like if you connected all of it: purchase behavior, lifestyle signals, social engagement, psychology-driven insights, and channel preference, linked to the same person across both their patient and provider identities where relevant. Most organizations haven’t built that view because most data providers weren’t built to support it. 

The identity layer connects the dots

Connecting consumer data to a healthcare audience strategy starts with a strong identity foundation. Patient, member, and provider records need to connect to meaningful consumer signals in a compliant way that can scale across a full audience, not just a small pool of matched records. 

That foundation is what makes truly custom audience building possible. Custom audience building isn’t simply about creating a smaller slice of a static list. It’s about giving marketers more dimensions to work with — and the flexibility to identify the combination of attributes most relevant to a specific campaign. 

Transaction data and cognitive science, together 

The “what” of consumer behavior, purchases, brand affinities, category activity, tells you what someone has done. The “why,” rooted in psychological and motivational research, tells you what’s likely to move them next. Combining both is what allows a brand to catch a real signal early: someone shopping for products tied to a condition, for example, often shows that behavior well before a formal diagnosis enters any healthcare record. 

That combination isn’t just insight for insight’s sake. It’s an audience strategy opportunity that enables a healthcare or pharma brand to construct a custom audience around a specific behavioral or motivational signal, rather than settling for a static demographic or condition-based segment. 

What a custom healthcare audience can actually look like 

Take a pharma brand trying to decide how to split attention between a DTC campaign and an HCP-focused push for the same condition area. A static audience approach treats these as two separate builds: one pulled from condition or lifestyle segments for consumers; one pulled from specialty and prescribing data for providers. 

A custom approach starts earlier on the consumer side. Many people show real signals before a diagnosis ever appears in a record: buying related products, searching relevant symptoms, or engaging with related content. Layering that behavior with consumer attributes and purchase history lets a brand reach people already in-market, rather than waiting for a diagnosis code to catch up to what their behavior already shows. 

On the HCP side, the same consumer data adds a different kind of value: not new segments, but a fuller picture of the same providers already on a specialty and prescribing list. Take a physician who fits the right clinical profile, but who, according to consumer data, is also an avid dog owner active in pet communities online. That detail doesn’t change who to target. It changes how a brand shows up: a lifestyle-relevant creative angle, a channel that physician is genuinely active on personally, a tone that reads as one person talking to another rather than a rep talking to a specialty code. 

Built on the same identity layer as the DTC audience, this kind of provider audience adds a human dimension to a list that used to run on professional data alone, without losing the clinical relevance that made it a fit to begin with. 

This isn’t about replacing the clinical or claims-based data healthcare marketers already rely on. It’s about strengthening that foundation with consumer intelligence to build more relevant, precise audiences across both patient and provider strategies. 

Get a custom audience recommendation around your DTC or HCP marketing goals, or connect with our team to turn your strategy into an audience built to perform.