At A Glance
Healthcare marketing now runs across mixed-identity conditions, where authenticated data, contextual signals, and aggregated measurement all show up in the same campaign. Pharma brands need infrastructure that keeps DTC and HCP identity separate and still connects fragmented signals across activation, privacy, and measurement. Experian acts as an independent, privacy-first identity, data, and workflow layer for pharma marketers, designed specifically for this operating environment.Originally published in Digiday
Key takeaways
- Pharma campaigns now span environments with very different identity conditions, from strong addressability to contextual only signals, which makes coordination a core infrastructure challenge.
- Privacy and compliance rules require DTC (patient) and HCP (healthcare professional) data to stay in separate, non-overlapping workflows at every stage.
- Experian’s identity and workflow layer governs DTC tokenized matching and HCP deterministic National Provider Identifier (NPI) resolution as two distinct processes, never one merged identity path.
- Partner-enabled measurement connects exposure data to outcomes like script lift and qualified HCP engagement through trusted partners including IQVIA Digital, PurpleLab, and OptimizeRx.
A pharmaceutical brand launching a campaign today might rely on authenticated data in one environment, contextual signals in another, and aggregated measurement somewhere else entirely. That’s the reality of healthcare marketing right now, and most brands are still building the operational model to match it.
In a mixed-identity ecosystem, performance comes from the ability to coordinate multiple signal types across activation, privacy, and measurement workflows. Accuracy and scale depend on knowing which approach fits which environment and having the infrastructure to execute across all of them.
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
Healthcare campaigns run across different signal conditions
Healthcare campaigns now run across environments with very different identity conditions, from fully addressable channels to contextual only placements. Digital advertising has long assumed that better identity leads to better targeting, frequency management, orchestration, and measurement, but healthcare has always operated with more constraints than most categories. Those constraints are becoming impossible to ignore as budgets move into connected TV (CTV), point-of-care, publisher-direct, programmatic and retail media-adjacent environments.
That shift changes the operating model. Marketers now have to manage audience strategy, supply quality and performance across channels that don’t support the same level of addressability, interoperability, or measurement visibility. In some environments, identity is strong and can support targeting and measurement. In others, identity is limited or unavailable, and marketers have to rely on contextual or aggregated signals. Managing across both environments is now a core infrastructure challenge for healthcare marketers, and it’s one that requires a deliberate strategy rather than a channel-by-channel patch.
Privacy risk is a media infrastructure issue
Privacy risk in healthcare marketing now shapes how campaigns get built and run from the ground up, extending well beyond compliance into media infrastructure itself. Tighter privacy and compliance expectations mean audience construction, exposure management, and outcomes analysis all get more complex once tracking is restricted.
Data can’t move freely across partners or workflows, and DTC and HCP data environments need to stay isolated from one another. This is especially true in pharma, where the stakes of a compliance misstep extend well beyond a campaign. This creates a more demanding operating model. Healthcare marketers have to balance identity-based and privacy-forward approaches while maintaining reach, relevance, and accountability. That balance requires governance that’s built into the infrastructure, not layered on top of it after the fact.
Experian acts as an independent, privacy-first identity, data, and workflow layer for pharma marketers, designed specifically for this operating environment:
These workflows are governed separately by design, with governed onboarding connecting fragmented DTC and HCP signals to activation-ready audiences without collapsing the two identity paths.
The mixed-identity playbook starts with matching the approach to the environment
The right mixed-identity approach depends on what each environment can support and what the campaign is needs to achieve. A pharmaceutical team may want more addressability, a publisher may only offer contextual or cohort signals, and a measurement partner may need exposure data, while platforms limit how identifiers can be shared.
Healthcare marketers need an operating model built for multiple identity conditions, with clear rules for how signals can be connected, activated, and measured without increasing privacy or compliance risk. That may include:
Experian’s infrastructure supports all three modes:
The missing layer in pharma marketing. Watch our Q&A
Supply quality is a prerequisite for measurement
Supply quality determines whether measurement in a mixed-identity environment can be trusted. When tracking and addressability vary across channels, advertisers need confidence that impressions ran in the right environments and under the right conditions before they can trust any downstream outcomes.
This is especially true in CTV and programmatic, where campaigns span fragmented supply paths, publishers, devices, and partners. Outcomes like script lift or provider engagement are only meaningful if the underlying exposure is reliable and well understood. In healthcare, this also ties directly to brand suitability and disclosure control. Curated supply, publisher-direct deals and placement-level transparency help campaigns run in appropriate environments and give measurement a more defensible foundation.
Clean rooms and tokenization support this, but their effectiveness depends on governance, interoperability, and whether insights can move cleanly across partners and workflows. Partner-enabled measurement, connecting exposure data to outcomes through trusted partners including IQVIA Digital, PurpleLab, and OptimizeRx, is structured in two steps:
- Link activation and measurement IDs without collapsing them into an open identity environment
- Produce aggregated, defensible outcomes including script lift, qualified HCP engagement, and verified delivery
Mixed-identity is the operating reality, and infrastructure is how you manage it
Mixed-identity is now the operating reality for healthcare marketing, not a temporary phase to work around. Performance depends on working across environments where identity is sometimes strong and sometimes limited by design. Healthcare marketers don’t need to pick a single identity approach and apply it everywhere. Building infrastructure that connects deterministic identity, tokenized matching, and contextual signals, keeping compliance, operational flexibility, and trust intact at every step, is what separates the brands managing this well from the ones still patching it channel by channel.
Talk to our team about your healthcare identity strategy
Whether you’re running DTC, HCP, or both, our team can help you build an infrastructure that works across identity environments. Let’s connect.
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
Mixed-identity means a healthcare campaign relies on more than one type of signal at once, such as authenticated data in one channel, contextual data in another, and aggregated measurement in a third. Pharma brands increasingly need infrastructure that coordinates all of these signal types together instead of treating each channel as a separate problem.
Experian keeps DTC and HCP identity in distinct, non-overlapping workflows so patient data and healthcare professional data never combine. DTC activation runs on high-fidelity tokenized matching, and HCP activation relies on deterministic National Provider Identifier (NPI) resolution using verified attributes like specialty and practice location.
Supply quality matters because outcomes like script lift or provider engagement only mean something if the underlying ad exposure is reliable. Curated supply, publisher-direct deals, and placement-level transparency give healthcare marketers a more defensible foundation before they trust any downstream measurement result.
Partner-enabled measurement connects exposure data to outcomes through trusted third parties such as IQVIA Digital, PurpleLab, and OptimizeRx, without merging activation and measurement identifiers into one open identity environment. The result is aggregated, defensible outcomes like script lift, qualified HCP engagement, and verified delivery.
Healthcare marketers don’t have to choose one approach over the other, since most campaigns already run across both conditions at the same time. Building infrastructure that connects deterministic identity, tokenized matching, and contextual signals is what allows a campaign to stay compliant while still reaching the right audience.
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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. 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