The health insurance sector is at a point where, unless insurers know each member like the back of their own hand, they will increasingly struggle with engagement and retention.
Economic pressure is bearing down on consumers as well as insurers. As premiums continue to increase so payors can maintain margins, members will increasingly shop around for the most cost-effective and tailored health plans. That’s the reality across segments:
- One in three ACA Marketplace enrollees say they would shop for a lower-premium plan (i.e. higher deductibles and out-of-pocket costs) if premium tax credits are not extended.
- 20% of members disenroll from commercial insurers each year according to established longitudinal studies.
The key to preventing or even reversing this level of membership erosion is inside each insurer’s data. If your organization is prepared to use that data to enhance member experiences this year, the following strategies can get you moving in the right direction.
Key Takeaways
- Member experience in health insurance is driven by data quality, not touchpoint volume. Even the most advanced engagement tools fail when member, benefits, and claims data are inaccurate or incomplete.
- Poor data directly impacts trust, engagement, and retention. Errors in eligibility, authorizations, or communications create friction that undermines confidence and accelerates member churn.
- Modernizing data does not require replacing core systems. Insurers can improve accuracy and consistency by integrating and orchestrating data across existing platforms.
- AI delivers value only when built on a strong data foundation. High-quality, well-governed data enables personalized, timely, and scalable member engagement.
Start by fixing the data quality problem
Problems with member engagement rarely stem from a lack of touchpoints. Most plans already offer apps, portals, call centers, care managers, and digital communications to deepen their understanding of individual members. In short, they are flush with data. The issue is that data’s accuracy and completeness.
You can see how this plays out in critical functions like claims reimbursement. At least 46% of respondents to an Experian Health survey about their most frequent claims denial issue said that missing or inaccurate data was the most likely cause. Knowing that a claim should be covered but having to fight for authorization because the data is bad can sabotage your member engagement activities.
Care management outreach is another area where data issues pose a problem. Inaccurate contact information, outdated clinical data, or incomplete member profiles can lead to ill-timed or irrelevant communications. When that happens, outreach can feel intrusive rather than supportive, discouraging engagement in the future.
In reality, any stage in candidate engagement can misfire in ways that erode trust and increase member attrition if leadership doesn’t take an active stake in remedying them.
Improving data quality without starting over
For most health insurers, data quality challenges are not the result of a single system failure, but years of incremental growth, acquisitions, regulatory change, and evolving operating models. Replacing core platforms to address these issues is rarely practical, it’s often unnecessary. Leading organizations are improving data quality by modernizing, not resetting existing systems.
The first step is clarifying the most important data for member engagement and the areas most prone to omissions or mistakes. Member identity, eligibility, benefits, claims, and authorizations are areas where data errors most directly affect experience, cost, and compliance. Normalizing these areas first enables faster returns while reducing organizational risk.
Integration and orchestration layers play a critical role as well. By synchronizing data across platforms and resolving discrepancies in near real time, insurers can present a consistent member view even when underlying systems remain unchanged. This allows engagement teams and AI tools to operate from a shared source of truth.
The result is a pragmatic modernization path. Data becomes more accurate, accessible, and trustworthy, enabling automation and AI to deliver value sooner and with less risk.
How innovative healthcare insurers are pairing quality data with AI
In an interview with Becker’s, Craig Kurtzweil, Chief Data and Analytics Officer for UnitedHealthcare, said, “At our core, we’re a data company. There’s a lot of data, and many ways we can use technology.”
They’re not the only healthcare payer that thinks this way. Plenty of leading plans are using well-maintained data to fuel engagement activities. They align data, automation, and AI around precision rather than volume. They focus on helping members navigate the system more effectively, reducing avoidable friction and downstream cost. Here are few instances where payors are leveraging data for engagement.
UnitedHealthcare
UnitedHealth Group’s expanding use of AI highlights how deeply member engagement depends on data quality. The Smart Choice, AI provider-search tool, designed with quality in mind from provider performance ratings in claims data, empowers members to maximize their health benefits. Grounding its AI strategy in strong data governance and continuous data improvement makes interactions feel timely and relevant.
Aetna
The Connecticut-based payor is creating an AI-powered conversational experience across digital channels. Moving beyond chat windows requires the Aetna assistant to use reliable and relevant information from each member or risk answering questions about coverage incorrectly. With the goal of avoiding jargon whenever possible, the assistant must translate complex benefits, eligibility rules, and plan-specific nuances into clear, personalized answers members can actually understand. That level of clarity is only possible when underlying member, benefits, and clinical data are accurate and well-integrated.
Blue Cross Blue Shield of Minnesota
Blue Cross Blue Shield of Minnesota is using AI to simplify how members interact with their health plan through tools like Blue Care Advisor. The digital platform is designed to help members navigate benefits, claims, deductibles, and care options in one place. The conversational Advisor will make personalized recommendations based on health goals, clinical indicators, and cost preferences. As a result, BCBSMN can reduce the cognitive burden members face with their care decisions.
Simplifying your member engagement transformation
Meaningful engagement is built on trust, which requires well-governed data at its core. When insurers get the data foundation right, AI becomes a force multiplier. Navigating plans, coverage, and claims becomes more intuitive. And members feel supported rather than frustrated.
w3r Consulting partners with health insurers to tackle engagement challenges at their source. We help plans improve data quality, integrate fragmented systems, and establish governance models that allow automation and AI to operate reliably at scale. By focusing first on the data that matters most to members, we enable engagement strategies that reduce friction, improve clarity, and drive measurable gains in satisfaction, efficiency, and retention.
Struggling with the member experience in health insurance? w3r Consulting can help implement data and AI best practices to keep members engaged.