Healthcare organizations have invested heavily in digital engagement over the past decade. Patient portals. CRM platforms. Campaign automation. Consumer data platforms. And yet, personalization in healthcare still feels stuck.
Outreach is often generic. Preventive care reminders go unopened. Screening campaigns underperform. Value based care programs struggle to engage the very patients they are designed to support.
I hear a version of the same frustration from health system and life sciences leaders. Their engagement stack keeps expanding, but their impact on the patient experience remains limited.
While many healthcare organizations have abundant data, most have an identity and context gap.
Personalization stalls when identity never moves beyond the EHR
A diagnosis tells you what care is needed, but it doesn’t tell you how to reach someone, when they are most receptive, or what barriers might prevent follow-through.
When identity stops at the electronic health record (EHR), engagement becomes a series of educated guesses about a real person’s needs, preferences, and circumstances.
Patients don’t live inside the EHR
Consider how most preventive outreach works today. A patient leaves the hospital with instructions and a recommended follow-up appointment, and the system triggers a standard sequence of reminders.
The intent is right. The execution is usually constrained by missing context.
- Will they see the message in the channel you chose?
- Is a caregiver involved in coordinating next steps?
- Is the barrier logistics, or clarity on what to do next?
These factors determine whether follow-up happens. They also determine whether “personalization” actually feels personal, or just automated.
In other industries, personalization advanced by connecting transactional data with behavioral and household context. In healthcare, those signals remain separate to protect patient data, often resulting in a disconnect between strong clinical insights and effective patient engagement.
Connecting the dots is the hard part
There’s a common narrative that healthcare needs more data to improve personalization. In practice, the bigger challenge is connecting what you already have in a way teams can trust. Identity, preference, household context, and engagement history often live in different systems, and they rarely resolve cleanly to a usable profile.
A privacy-safe identity foundation changes that. When organizations can link records across sources with strong match discipline, governance, and tokenization, they can turn fragmented data into more relevant decisions without exposing more than is necessary.
Watch our Q&A with Cristin Liberatore from IQVIA Digital on healthcare marketing
How we approach this at Experian
At Experian, this is the lens we use:
What privacy-safe identity makes possible in regulated patient engagement
In regulated categories, accuracy, governance, and privacy are non-negotiable. That’s why I push teams to think about identity as infrastructure, because people move, households change, and preferences shift.
At Experian, that infrastructure includes:
- Marketing Attributes and Enrichment: Adding context to first-party data so planning and decisioning reflect the person you’re trying to reach.
- Offline and Digital Graphs: Connect identity across touchpoints so experiences stay consistent as people move between channels.
- First-Party Onboarding and data marketplace: Activate consented consumer and patient data across digital environments in a privacy-safe way. Our data marketplace extends that strategy with third-party partner segments, improving your personalization efforts to encourage a more proactive approach to healthcare.
- Curated Deals: Support upper-funnel awareness by aligning audience insight with higher-quality inventory in environments that can improve visibility, context, and campaign efficiency.
Watch our healthcare marketing panel from CES 2026
Identity must come first in healthcare marketing
Healthcare personalization has plateaued because engagement strategies have stayed too narrow and disconnected from the realities that shape follow-through.
The next phase of healthcare engagement will be defined by organizations that treat identity and additional patient context as the foundation for decisioning, activation, and measurement. When identity connects to real-world context through privacy-safe, governed, and tokenized practices, outreach becomes more relevant, easier to receive, and easier to act on.
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.
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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 Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
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