Leveraging Customer Analytics to Increase Profitability – A Leading Insurance Firm
One of our customers – a leading insurer is a global insurance company serving more than 50 million people worldwide.– had a challenge. Over 43% of their millions of customers who purchased policies in previous years had allowed them to lapse. It was not easy to sell the policy again to the same customers. Customer acquisition cost is significantly higher than the customer retention cost in general, and it was impacting the bottom-line of the client significantly. Our client wanted to understand customer behavior, identify at-risk customers, and come up with early intervention strategies to retain the customers.
The Expedien team helped the client by building a “Customer Analytics” solution that helped them identifying its customers, who were most at risk of canceling their policies, or not renewing, and also insights into why. Once at-risk customers were identified, the client was able to come up with an early intervention strategy and developed specialized scripts and incentives to use in interactions with these policyholders. Customer Analytics solution also helped insurer’s agents understand a prospect’s risk level from the beginning of the sales process by comparing their profiles to those of existing customers and came up with proactive intervention accordingly. Among the insights, the analytics revealed that least interaction with an agent and no or very few medical examination indicate a substantially higher risk of lapsing. Another insight was that the customers who insurer didn’t update on policy benefits periodically were at higher risk of canceling or lapsing the policy.These insights helped the client’s customer engagement and outreach efforts tremendously, allowing them to communicate more productively, and confidently with their policyholders.
Key Challenges
- Large and poor quality customer data residing in multiple legacy systems
- Poor or No actionable insight into customers’ wants and need and hence lack of effective customer engagement/li>
- Customer acquisition cost is significantly higher than the customer retention cost
- Problems with claims management, denials, and increased customer dissatisfaction
- Loss of existing customers
Benefits
- 4% increase in premium revenues in one year
- 6% of customers lost in the previous year were recovered
- 140 % return on investment within the first year
- Retention of 18% more customers than previous years anticipated next year
Implementation Highlights
- A “Customer Analytics” solution was built integrating customer, policy, claims, social media, call center/agent interaction data for 6+ million of the client’s customers
- We used historical data, and current data to predict the customers by segments such as age, income, ethnicity, geography, gender and so on, who may be at a high risk of lapsing or canceling
- Built repeatable and reusable data quality routines and master data solution to cleanse the data and provide a single view of customer related data