In Healthcare, Customer Acquisition Is Not Just Marketing

A recent TechCrunch summary of Bloomberg reporting found that many state-run health insurance marketplaces had embedded advertising trackers that sent user activity and application-related information to major technology platforms.

According to the reporting, nearly all of the 20 U.S. state-run health insurance marketplaces shared some resident application information with companies including Google, LinkedIn, Meta, and Snap. In some cases, the information reportedly included sensitive fields such as race, sex, ZIP code, email, phone number, citizenship-related responses, and other enrollment details.

This is not just a privacy story. It is a market signal that the operational and technical tools used to attract, convert, onboard, engage, retain, and expand customers are not neutral infrastructure in healthcare.

In other industries, advertising pixels, analytics tools, CRM systems, intake forms, engagement platforms, and data-sharing integrations may be treated as ordinary commercial infrastructure. In healthcare, those same tools can touch sensitive data, regulated workflows, vulnerable populations, insurance eligibility, government-program participation, and patient or consumer trust.

For healthcare companies, the distinction between consumer-style growth tools and healthcare-grade customer acquisition and engagement systems can affect how customers trust the company, how partners evaluate it, and how buyers ultimately price the business in M&A.

The issue is not simply whether growth tools improve conversion. It is whether they support the trust, controls, and channel credibility required to scale in healthcare.

The healthcare customer acquisition and engagement stack has changed

Healthcare companies have spent the last decade building increasingly data-enabled systems to attract, convert, onboard, engage, retain, and expand customers. These systems help commercial healthcare teams grow faster, reduce friction, reach targeted populations, measure campaign performance, and operate more efficiently.

The stack may include:

• website analytics and landing-page optimization
• ad pixels, conversion trackers, and retargeting tags
• paid search, paid social, programmatic advertising, and affiliate channels
• CRM systems and marketing automation
• call center workflows, lead scoring, and sales routing
• patient intake forms, eligibility checks, and enrollment workflows
• referral management systems and channel-partner workflows
• SMS, email, portal, and app-based engagement tools
• identity resolution, customer data platforms, and data clean rooms
• data warehouses, dashboards, and attribution models
• AI-enabled personalization, routing, intake, or follow-up systems

Why this is also an adtech and martech issue
This is not only a healthcare company issue. It is also a broader Woodside conversation across healthcare, adtech, martech, consent tech, identity tech, analytics, and workflow software.

Healthcare companies are increasingly using advertising, analytics, CRM, intake, and engagement tools to acquire and retain customers. At the same time, adtech and martech vendors are expanding into healthcare, pharma, benefits, employer health, and provider channels.

That overlap creates a more complicated commercial environment. The same capabilities that make a platform valuable in consumer markets - targeting, attribution, identity resolution, personalization, automation, and conversion optimization - may need to operate differently in healthcare.

This matters across several categories:

• healthcare companies using performance marketing, CRM, intake, and engagement tools to scale
• adtech and martech vendors expanding into regulated healthcare channels
• identity, privacy, consent, and clean-room tech platforms serving healthcare or other regulated markets
• analytics and attribution companies helping healthcare customers measure growth while preserving data controls
• patient engagement and workflow companies that sit between marketing, operations, and care delivery
• AI-enabled companies using personalization, routing, content generation, or automated follow-up in healthcare contexts

For companies in these categories, the issue is not whether advertising, analytics, or engagement technology belongs in healthcare. It already does!

The more important question is whether those capabilities are configured, governed, and positioned in a way that healthcare customers, strategic partners, and eventual buyers can trust.

Data trust is becoming part of commercial infrastructure
In healthcare, trust is not only a brand attribute. It is part of the commercial architecture that allows a company to scale.

A company's data practices and customer acquisition and engagement systems affect whether it can:

• sell to enterprise healthcare customers
• partner with payers, providers, pharma, employers, or government programs
• expand from consumer acquisition into institutional channels
• use data for personalization, analytics, AI, benchmarking, or workflow automation
• maintain patient, consumer, and customer confidence
• support cross-sell, referral expansion, and workflow expansion
• integrate into a larger strategic platform
• defend the quality and durability of its revenue

This is why the issue is broader than compliance.

The core question is not simply whether a company has avoided a problem. The core question is whether its operating systems, data flows, vendor relationships, and growth model support durable value creation.

Healthcare companies that can show disciplined data use, clear rights, appropriate consent, controlled vendor relationships, truthful growth practices, and credible governance are better positioned to defend value with buyers and partners than companies that simply show rapid digital acquisition or large datasets. Value accrues to trusted parties.

The mid-market founder problem
Many mid-market healthcare companies are not reckless. They are resourceful.
Founder-owned and bootstrapped companies often build with lean teams, limited capital, practical tools, and a strong bias toward action. They use what works. They move quickly. They prioritize customers, revenue, service delivery, and survival.

That scrappiness can be a strength.

But the systems that help a company grow from early revenue to meaningful scale are not always the systems that support enterprise partnerships, strategic acquisition, or public-company ownership.

A company may have real traction, strong customer relationships, valuable data, and a compelling market position while still relying on informal or under-documented data flows, vendor relationships, marketing practices, or engagement workflows that become harder to defend as the company grows.

This is especially relevant for businesses operating across:

• digital health
• telehealth
• care navigation
• patient acquisition
• benefits and enrollment
• clinical trial recruitment
• healthcare marketplaces
• diagnostics and testing services
• real-world data
• patient engagement
• provider enablement
• pharma services
• AI-enabled healthcare workflows

In these markets, the value of the company often depends on the credibility of the data layer and customer acquisition model underneath the business.

Strategic buyers care because trust affects value creation
Strategic and financial buyers are not only evaluating what a company has built. They are evaluating whether that company can scale inside a larger commercial, regulatory, and reputational environment.

For healthcare acquirers, data trust affects several core value drivers.

1. Integration
   Can the company's systems, data flows, vendor relationships, marketing tools, and operating practices integrate into a larger, compliance-sensitive enterprise environment?
2. Revenue durability
   Are customers likely to stay, expand, and trust the company with more sensitive workflows?
3. Channel expansion
   Can the company move from founder-led sales, DTC acquisition, or narrow campaign-based growth into payer, provider, employer, pharma, or government channels?
4. Data monetization
   Can the company use its data assets for analytics, AI, benchmarking, personalization, or workflow automation without undermining trust?
5. Brand extension
   Will the acquirer be comfortable putting its name, customer relationships, and regulatory posture behind the company's operating model?
6. Platform strategy
   Can the company become part of a broader strategic platform, or is its data infrastructure too fragile, opaque, vendor-dependent, or channel-specific?

The strongest companies will not treat data governance as a back-office compliance function. They will treat it as part of the operating model.

What stronger companies can show
For healthcare companies considering strategic options, capital, partnerships, or eventual M&A, data practices need to be presented as part of the operating model - not as a separate compliance appendix.

The goal is to show that the company understands how customer data is collected, used, shared, protected, and governed - and why those practices support commercial value.

Stronger companies should be able to explain:

• what data is collected at each stage of acquisition, conversion, onboarding, engagement, retention, and expansion
• why the data is collected and how it supports the customer experience or operating model
• where the data is stored and which vendors, APIs, pixels, tags, platforms, or integrations touch it
• what rights, notices, consents, contracts, or customer permissions support its use
• how marketing data is separated from sensitive healthcare data
• how patient, consumer, participant, employee, or provider data is protected
• how policies match actual data flows
• how the company governs new tools, integrations, affiliate channels, and AI use cases
• how the data layer supports future enterprise partnerships, strategic acquisition, or platform expansion

This is not only about reducing risk. It is about increasing buyer, partner, and customer confidence in the company's ability to scale.

The Woodside perspective
In healthcare M&A, trust is not a soft asset. It is part of what buyers underwrite.

For mid-market healthcare, life sciences, diagnostics, healthcare software, marketing technology, advertising technology, analytics, and data-enabled services companies, strategic value increasingly depends on more than revenue growth or technical capability alone.

It depends on whether the business has built the infrastructure required to support durable customer relationships, compliant growth, enterprise adoption, and strategic buyer confidence.

That is especially true for founder-owned companies where much of the value may be embedded in years of customer trust, scientific credibility, proprietary workflows, specialized data, or hard-won commercial relationships.

The companies best positioned going forward will be those that combine commercial scale, technical differentiation, and durable data infrastructure. That connection is becoming a meaningful part of healthcare company value.

Source

TechCrunch summary of Bloomberg investigation: https://techcrunch.com/2026/05/04/us-healthcare-marketplaces-shared-citizenship-and-race-data-with-ad-tech-giants/