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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In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in adtech. Today’s interview is with Georgia Campbell, Head of Strategic Partnerships at Kontext. What types of audiences does Kontext provide, and what are some top use cases for these insights in marketing strategies? Kontext leverages its 1st-party, deterministic shopping data to generate real-time online audiences. What sets Kontext apart is our ability to see the entire consumer journey, from shopping interest to intent and purchases, at a SKU-level. This comprehensive visibility allows us to create purchase-based audiences across various consumer verticals, such as frequent online shoppers, consumers shopping for beauty, segments using Mastercard, or Black Friday enthusiasts. Our data engine, built on a foundation of approximately 100 million consumer profiles and over 10 billion full-funnel, real-time shopping events, enables the creation of precise audience segments. This real-time 1st-party shopper data is invaluable for partners aiming to understand and engage with consumers more effectively. Whether a brand wants to activate past shoppers in a specific category or reach new audiences with a propensity to buy, Kontext provides the insights needed to make informed decisions. Some examples of audience types include these (and hundreds more): In-Market Shoppers: Consumers showing high intent to purchase specific categories, like skincare or electronics, based on recent online behavior. Past Purchasers: Shoppers who have made verified purchases within specific time frames, such as beauty products in the last 18 months. Frequent Shoppers: High-frequency buyers identified through repeated purchasing behaviors. Seasonal Shoppers: Consumers active during key shopping seasons, like Black Friday, Mother’s Day, Valentine’s Day, etc Premium Buyers: Shoppers who used a premium CC (eg. Amex) and a higher AOV (average order value) Beauty Buyers: an audience that has indicated intent to purchase beauty products (deterministic past purchasers also avail) By using Kontext data, brands can identify the right audiences across multiple verticals, such as retail, CPG, health & wellness, auto, business, energy & utility, financial, and travel. Additionally, our collaboration with Experian allows further refinement of these audiences through layered data from specialty categories like demographics, lifestyle & interests, mobile location, and TV viewing habits. How is Kontext’s data sourced, and what differentiates it from other data providers? Kontext’s data is unique because it is deterministic, 1st-party, and collected as transactions occur. We capture the entire path-to-purchase, down to the SKU-level product detail, across 100 million consumer profiles and more than 10 billion real-time shopping events. Our proprietary technology, embedded in widgets across our 5 million premium online destinations, tracks the full consumer journey—from reading an article of interest to clicking on our dynamic commerce modules, adding items to cart, and completing purchases. This real-time data collection ensures there is no lag between digital events and their connection to consumer profiles. Unlike other providers, we do not aggregate data from multiple platforms; instead, we focus on building our models and insights based on authentic online consumer behavior. Our data stands out due to its: Deterministic Nature: We capture 1st-party data as transactions occur (all in real time) Full-Funnel Coverage: We capture consumer journeys from awareness to purchase, providing a complete view of consumer behavior. Real-Time Insights: Our data engine processes events in real-time, enabling timely and relevant marketing actions. How does Kontext ensure the accuracy and reliability of its audience data? Kontext ensures accuracy and reliability through our unique technology and direct data sourcing. By not aggregating data from other platforms, we maintain control over the quality and integrity of our insights. Our continuous investment in refining our models around online consumer behavior further enhances the precision of our audience data. What types of brands or verticals might resonate the most with Kontext audiences for activation? Any brand looking to understand and activate online shopping behavior – informed by 1st-party transaction data – will resonate with Kontext audiences. Essentially, any vertical that benefits from understanding real-time shopping behaviors, such as retail, health & wellness, auto, and financial services, will find our data invaluable. We have particularly strong insights in beauty, hair care, health & wellness, and values-based online shopping habits, as well as the food & beverage space. Retail & Consumer Goods: Leveraging shopping behavior data for targeted campaigns. Health & Wellness: Identifying consumers with specific health and wellness interests. Automotive: Targeting potential buyers of electric vehicles or eco-friendly products. Financial Services: Engaging high-value shoppers with premium credit card usage. And many more How does Kontext’s data help advertisers navigate the challenges posed by the deprecation of third-party cookies? As third-party cookies become less reliable, Kontext’s 1st-party data becomes invaluable. Our deterministic data engine, which does not rely on cookies, offers: Direct Consumer Insights: Accurate and consented data directly from consumer interactions. Privacy Compliance: Our data collection methods are fully compliant with privacy regulations, ensuring secure usage. Cross-Device Coverage: We use verified digital identifiers, allowing seamless unification and targeting across multiple devices. What measures does Kontext take to maintain data privacy and compliance, and how does this benefit advertisers? Data privacy and compliance are fundamental to Kontext. We meet or exceed all privacy compliance and security standards, ensuring that our data sourcing and usage are transparent and comply with regulations (CCPA, CPRA, VCDPA, etc). Kontext prioritizes data privacy and compliance through: Consented Data Collection: All data is collected with explicit consumer consent. Robust Security Protocols: Data is encrypted and secured with industry-leading practices. Compliance with Regulations: We adhere to global privacy laws, including GDPR and CCPA. User Control: Consumers have the ability to opt-out and manage their data preferences. Can you share success stories / use-cases where advertisers significantly improved their campaigns using Kontext’s data? To give you a sense of how Kontext data can be applied, here are two use-cases: Beauty Brand Campaign: An agency hoping to activate an audience of beauty purchasers for a Major Beauty Brand could utilize Kontext’s custom audience of high-value beauty product purchasers. By targeting those consumers who had bought similar products in the last 12 months and had an average cart size of over $50, the campaign would significantly increase performance and ROAS. Electric Vehicle Launch: For a major auto manufacturer’s EV launch, Kontext could be used to identify eco-friendly consumers who had not yet purchased an EV but had shown interest in sustainable products. This precise targeting could lead to higher engagement and conversion rates for the campaign. Thanks for the interview. Any recommendations for our readers if they want to learn more? For those interested in learning more about Kontext, reach out for a personalized consultation. Contact us About our expert Georgia Campbell, Head of Strategic Partnerships, Kontext In her current role as Head of Strategic Partnerships at Kontext, Georgia plays a pivotal role in shaping the company’s strategic direction within the data space. With a deep-seated expertise in leveraging data to drive impact for companies, Georgia has been forging key partnerships that enhance the effectiveness and reach of Kontext’s offerings. Georgia comes from a background in emerging technology, where she has been focused on cultivating partnerships and employing data-driven approaches to spearhead market expansion efforts. She started her career in finance, managing investments across equity, debt, and alternative assets at Brown Advisory. In this Q&A, Georgia shares her insights on Kontext’s Onboarding partnership with Experian, offering perspective on how Kontext’s unique insights can unlock new opportunities for advertisers and brands alike. Latest posts
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