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How to Use Analytics to Design Winning Health Insurance Products

Many new product or service concepts, including health insurance, can be configured in hundreds of thousands (and even millions) of ways. This is because most concepts are made up of multiple attributes and levels that must be perfectly combined and offered at just the right price before they will succeed.

In today's highly competitive health insurance marketplace, advanced analytics (conjoint, etc.), along with automated search algorithms and segment-specific offers, give insurance companies a real advantage when launching new insurance products.

Special Report: Using Advanced Conjoint to Design Winning Health Insurance Products

To demonstrate the significant benefits of advanced conjoint analysis, we released a special report based on our national study among 373 adults in the United States. These health insurance consumers were asked to configure their ideal health plan based on a variety of options. Our example report reveals four important benefits of using Adaptive Choice-Based Conjoint (ACBC) when designing health plans:

  1. Know the Importance of Features: ACBC is the most reliable method for learning which features are most important to consumers.
  2. Predict Your Market Share: ACBC show you the impact of product design and/or price on market share vs. your competitors.
  3. Customize for Each Segment: ACBC allows you to identify choice-based segments, design products for each segment, and target them using demographics.
  4. Optimize Your Product & Price: Using ACBC, you can optimize your product design and pricing with the help of simulators and genetic search algorithms.

Inside the Special Report

Inside the 14-page, easy to read document (Powerpoint presentation style), the special report touches on the following key points:

  • Importance of Features: Consumer preferences for features, including premiums, deductibles, optional benefits, brands, co-pays, sources of insurance, prescriptions and more.
  • Importance of Brand: Consumer preferences for hypothetical products (and price points) from United Health Care (UHC), Blue Cross Blue Shield (BCBS), Humana and Kaiser Permanente.
  • Market Share Scenarios: How to estimate market share by competitor/brand for any given product configuration and price scenario.
  • Choice-Based Segments: How to develop choice-based segments that enable you to optimize products and prices for specific customer groups.
  • Effect of Premiums on Share: How to forecast likely share at various price points for premiums.
  • Simulators & Search Algorithms: How to use simulators and automated search algorithms to help you identify the very best product and price configurations in your state and among your target customer segments.

Click the button below to get your complimentary copy of the special report.

 Download the Conjoint Special Report

Contact us to provide a walkthrough of this report. Many of the conjoint examples are better understood when they are presented and discussed during a conference call.

David W. Wilson
David W. Wilson
David W. Wilson

David Wilson has over 25 years of experience helping leading companies improve their marketing results using digital marketing, direct marketing, database marketing, consumer data, predictive analytics and marketing research.