At A Glance
Healthcare marketers are spending record amounts on pharma advertising, but most still can't connect campaign exposure to prescribing outcomes. This article explains why fragmented data, identity, and measurement systems break the link between patient (DTC) and healthcare professional (HCP) audiences, and the infrastructure that closes that gap.Originally published in AdExchanger
Key takeaways
- Pharma digital ad spend is tracking between $22 billion and $26 billion in 2026, yet most brands still can’t connect ad exposure to prescribing behavior.
- DTC and HCP teams need to agree on a shared measurement framework before a campaign launches, not after, so performance can be judged on one standard.
- Experian’s identity infrastructure keeps DTC and HCP data governed separately through two distinct paths while still making cross-audience measurement possible.
- Experian’s Audience Engine connects audience building to activation, giving teams access to premium publisher inventory and a marketplace of 19+ verified health data partners.
Healthcare marketing teams are spending more than ever. Pharma digital ad spend is now tracking between $22 billion and $26 billion in 2026, with connected TV (CTV) overtaking search as the most noticed healthcare ad channel. Yet most brands still can’t draw a straight line from campaign exposure to a filled prescription.
The problem isn’t budget or creative. It’s a structural gap in how healthcare marketers connect data, identity, and measurement across patient (DTC) and healthcare professional (HCP) audiences.
That gap is widening as campaigns grow more complex. A brand running a simultaneous patient (DTC) push and healthcare professional (HCP) engagement program is running two disconnected programs with different data sources, identity schemas, agency relationships, and definitions of success. When a patient sees a CTV ad and their cardiologist receives a targeted digital engagement the same week, almost no brand can confirm that those two exposures happened, let alone measure their combined effect on prescribing behavior.
Why is data fragmentation becoming a bigger challenge for healthcare marketers?
Data fragmentation is becoming a bigger challenge for healthcare marketers because the accuracy pharma brands are paying for in digital media doesn’t match what most measurement stacks can deliver. As pharma shifts spend from linear television to digital channels, the expectation of accuracy comes with it. Brands can no longer accept “we reached the right demographic” as a measurement answer when they are paying programmatic CPMs and expecting outcomes measured in script lift.
The typical healthcare marketer is working with three or four disconnected data environments. Consumer data lives in one place. Claims and National Provider Identifier (NPI) records live in another. Media reporting from the agency is in a third. Analytics and measurement are downstream of all of them, often running on a different timeline. Each handoff introduces the potential for data loss, and those losses compound across a campaign flight.
This creates a reporting picture that tells you what happened in each channel but not what worked across them. That distinction matters enormously when the goal isn’t impressions but activation, adherence, or prescribing behavior.
The missing layer in pharma marketing. Watch our Q&A
Does fixing healthcare data fragmentation mean merging DTC and HCP data together?
No, merging DTC and HCP data together isn’t the answer to healthcare data fragmentation. Healthcare data environments have strict governance requirements, and the separation of DTC and HCP data is both a regulatory and a strategic necessity. Merging DTC and HCP data into a single undifferentiated pool is not a goal worth pursuing.
What healthcare marketers actually need is a shared infrastructure that lets disparate data environments speak a common language without eliminating the boundaries between them. Three elements make that possible:
Experian’s identity infrastructure is built on this principle, acting as a neutral, interoperable workflow layer. For DTC audiences, that means high-fidelity tokenized matching that preserves accuracy from onboarding through activation and into partner-enabled measurement. For HCP audiences, it means deterministic NPI-based resolution using verified professional attributes including specialty, practice location, and professional address. These are two distinct identity paths, governed to keep DTC and HCP data separate while enabling measurement across both.
From onboarding to outcomes
Pharma marketing teams need identity workflows that can support accurate audience creation, governed activation, and partner-enabled measurement without combining DTC and HCP identity paths.
Download our pharma marketing playbook to help your team:
- Plan DTC and HCP identity strategies with clearer separation
- Prepare audiences for activation across approved channels and partners
- Evaluate audience quality, usable reach, and governance
What does a connected view of DTC and HCP audiences look like in healthcare marketing?
A connected view means DTC and HCP audiences in healthcare marketing runs on identity workflows matched to what each requires, deterministic resolution for HCPs and high-fidelity matching for DTC, with both feeding into shared measurement instead of siloed reporting. Building this kind of connected infrastructure isn’t a one-quarter initiative, but three questions show you where your program stands today.
Why is infrastructure the foundation for durable healthcare marketing programs?
Infrastructure is the foundation for durable healthcare marketing programs because it’s what lets audience planning, activation, and measurement function as one connected system instead of three separate handoffs that break down under pressure. As healthcare marketing gets more competitive, regulated, and measurable, that connected system is what keeps campaigns from starting over each time.
A connected view of DTC and HCP audiences in healthcare, with the proper guardrails in place, is a strategic decision about how your brand wants to compete. The technology and the partner ecosystem exist to make it real. The question is whether your marketing organization is structured to take advantage of it.
Ready to build a connected healthcare identity strategy?
Our team works with pharma brands to align identity, audience, and measurement across DTC and HCP programs. If you’re ready to close the gap between data and outcomes, let’s talk.
About the author
Kevin Dunn
Chief Revenue Officer, Experian
Kevin Dunn joins Experian Marketing Services with more than 20 years of leadership experience across marketing and advertising technology, most recently serving as Senior Vice President of Brands and Agencies at LiveRamp. In that role, he led growth across retail, CPG, travel, hospitality, financial services, and healthcare, overseeing new business, account expansion, and channel partnerships.
Kevin is known for building cohesive, accountable teams and leading with optimism, clarity, and a strong sense of shared purpose. His leadership philosophy centers on empowering people, driving positive outcomes for clients and fostering a culture where teams can grow, take smart risks, and succeed together.
FAQs
Most pharma brands can’t connect a CTV ad exposure to a prescribing decision because their DTC and HCP data runs through three or four disconnected environments: consumer data, claims and NPI records, agency media reporting, and downstream analytics. Each handoff between those systems introduces potential data loss, and those losses add up across a campaign flight, leaving brands with channel-level reporting instead of a connected view of what actually moved prescribing behavior.
Building a connected identity strategy doesn’t mean combining DTC and HCP data into one data set. Healthcare data environments carry strict governance requirements, so DTC and HCP data need to stay separate for both regulatory and strategic reasons. A connected identity strategy links those separate environments through interoperable workflows rather than merging them into one data set.
Experian helps pharma brands connect DTC and HCP measurement without merging their data by running two distinct, governed identity paths: high-fidelity tokenized matching for DTC audiences and deterministic NPI-based resolution for HCP audiences, built on verified professional attributes like specialty and practice location. That structure lets brands measure performance across both audiences while keeping the underlying data separate.
The difference between deterministic and probabilistic matching in healthcare marketing comes down to certainty: probabilistic matching can support large-scale DTC reach where some statistical estimation is acceptable, while HCP targeting calls for certainty that only deterministic matching, typically based on verified NPI data, can provide. As healthcare audiences get more specific, the cost of an unverified match rises, which is why HCP resolution leans deterministic.
If a healthcare marketing team’s audience strategy isn’t translating into activation, the first thing to check is whether those audience segments can actually reach live publisher inventory. A lot of audience development happens in a spreadsheet or analytics tool and then stalls at activation because the IDs never connect to real media. Experian’s Audience Engine builds audience creation, onboarding, and activation into one workflow, backed by a marketplace of 19+ verified health data partners.
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Are there data quality standards that Webbula establishes for consumer data, and how do you ensure your sources and methods meet these standards consistently? Webbula’s data is aggregated from over 110 trusted and authenticated sources, including publishers, data partners, social media, and more. The data collected comes directly from consumers who self-report information through surveys and other methods. We apply our hygiene filters to mitigate fraud and accurately score the data. Data Collection: The data collected comes directly from consumers who self-report information through surveys, questionnaires, transactions, and sign-ups. This ensures that brands display ads to audiences based on self-identified, cross-channel behaviors, not modeled assumptions. Hygiene Solutions: Webbula applies multi-method hygiene solutions to mitigate fraud and accurately score the data before onboarding, ensuring that all data meets the highest quality standards. Examples of Data Sources: Questionnaires: Self-reported data through surveys, offer submissions, and telemarketing. Transactions: Deterministic data from aftermarket parts, online purchases or services, and more. Sign-ups: Individually linked data from information entered through sweepstakes, infomercials, newsletters, and forms. What differentiates Webbula’s data from other data providers in the market? Can you explain the unique value proposition that Webbula offers in terms of data depth and breadth? Due to our extensive experience in data cleansing, we provide the most accurate data within the programmatic ecosystem. TruthSet, the leading programmatic accuracy measurement company, has ranked Webbula as having the highest number of top attributes compared to other data providers with 150M+ HEMs. Additionally, Publicis Groupe and Neutronian further validate Webbula’s data quality, underscoring its position as a leader in the industry. 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Success stories Can you share success stories where advertisers saw significant campaign improvements using Webbula’s data? What were the key factors that contributed to these successes? Our success is measured by client feedback and increased client spend. Webbula has helped several key advertisers achieve six-figure monthly thresholds by providing the most accurate data to meet campaign KPIs. Clients consistently return to use our data, validating our belief that “the proof is in the pudding.” Thanks for the interview. Any recommendations for our readers if they want to learn more? For those interested in learning more about Webbula, reach out for a personalized consultation. Contact us Latest posts
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