Business Objective
Our client, a leading provider of life insurance and annuity plans in the US, wanted to evaluate the possibility of positioning the supplemental health insurance plans as a loss leader to drive additional enrolments and higher customer lifetime value (LTV). More specifically, the client wanted to:
- Understand the impact of lowering prices on new enrollments
- Optimize pricing strategy across jurisdictions and plans to maximize lifetime value while maintaining a healthy portfolio (considering the downstream morbidity and claims experience)
Challenges
- Competitor price that significantly impacts enrollment was not reliably available for every product segment
- Additionally, there was no information available on future competitor prices
Solution Methodology
- Considered a variety of internal and external data to understand the impact of various price points on enrollment and customer LTV
– Internal — premiums, other products purchased, claims, interactions
– External — demographics, chronic conditions incidence rate, competitor pricing - Developed models to forecast competitor prices for the future
- Created segments considering age, state, plan, gender to align with the client’s pricing strategy
- Developed price elasticity models to measure the impact of price changes on enrollments
- Identified key factors from the model such as premium change, client competitive index and positioning, GDP, and other macroeconomic factors
- Computed impact on supplemental product LTV for different levels of discount by applying VNB (Value of New Business) framework as a proxy for LTV
- Suggested optimal price strategy for each segment that maximized value
– Optimization was performed using expected enrollments, impact on supplemental LTV, and expected LTV from cross-sells at different levels of discount - Created a python-based scenario planner tool to enable active evaluation of price changes on LTV and portfolio health
Business Impact
- Significantly shorter time-to-market for any price change decisions as the impact can be easily simulated at the overall portfolio or segment level
