Published on August 5, 2019
Competition in Medicare and Medicare Advantage markets continues to intensify – particularly for mid-sized regional carriers facing national players. To sustain profitable operations and achieve strategic growth, health plans must discover and satisfy the complex and varied preferences of current and potential members. In other words, they must engage members in order to retain them, and they must know what product features and benefits are most likely to entice prospects who are shopping for new options.
However, most health plans still lack the infrastructure and capabilities to access and manage timely, accurate, and cost-effective consumer data. Beyond clinical and claims data, they may not even know what kind of data matters or what’s truly possible when the right approaches are implemented.
Our latest white paper addresses this knowledge gap by describing two different but complementary data sets: Carrot Health’s “AEP Winners and Losers” dashboard and Deft Research’s “Shoppers and Switchers” survey. Analytics from Carrot Health are built on data points pertaining to 250 million U.S. adults, over 5,000 different consumer variables, and over 70 different sources, while Deft collects primary research data (and builds historical trend data) through customer surveys. Although both methodologies have their strengths, big data and primary survey data can work together to offer a deep and robust understanding of consumer motives and priorities, as well as accurate predictions of both national and local market trends.
In combination, these two sources dramatically improve the ability of a health plan to understand consumer preferences, optimize marketing, and enhance member engagement. Here’s how Deft Research CEO Randy Herman describes the combined benefit: “Big data gives you a deeper understanding of the individual consumer, while survey data provides critical insights into what that consumer thinks and believes. In today’s competitive environment, health plans need both perspectives to thrive.” Together, big data and primary survey data dramatically lift health plans’ ability to discern and predict attitudes, behaviors, risk factors, preferences, and costs… which can help them sharpen strategies for plan design, product development, marketing, engagement, and growth.
Health plan design and precision marketing
When it comes to plan design, for example, every market in the country presents a different challenge for a health plan. Customers likely to choose a specific plan, offering, or benefit in one market may not be inclined to do so elsewhere. They may choose to move between carriers, select Medicare Advantage over traditional Medicare, and exercise a preference for different plan types, such as PPOs or HMOs, or for certain supplemental benefits over others. The right data approach enables health plans to make strategic decisions about where they can grow most effectively and determine which populations and segments are the best fit for current and future offerings.
Marketing and audience segmentation (which allows for precise message targeting) plays a key role here. Deft research shows not only member preferences for plan benefits but also their awareness of benefits. Many consumers used supplemental benefits as a critical part of their due diligence in switching plans. Interestingly, however, a large percentage of switchers did not actually know when their current plans offered a particular benefit. As a result, some appear to have unwittingly switched to plans with the same benefits thinking they were getting something new. For health plans, this sort of outcome speaks clearly to the importance of improved messaging in marketing campaigns. Big data with primary survey data can inform these improvements and optimize engagement outreach.
Click here to access the white paper: Know Thy Customer: How Health Plans Can Combine Big Data Analytics and Primary Survey Data to Revolutionize Market Understanding. It contains valuable details about how the combination of big data and primary survey data can improve both plan design and marketing efficiency, end insurer reliance on one-size-fits-all data sets and help health plans compete at the top of their game.