How MetLife Is Tracking Customer Sentiment With Analytics

May 30, 2018 by Mick Noland

The property/casualty business provides countless examples of initiatives to leverage data and analytics to improve agency relations, new business acquisition, underwriting and rating, and claim outcomes.Executive SummaryWhile the use of predictive analytics is now widespread in underwriting and claims, P/C carriers should not lose sight of the prolonged period between the time the premium is paid and a claim is made. MetLife Auto & Home is using data analytics to detect and address “pain points” in the customer experience, which can improve retention and expand customer relationships.

Executive Summary

While the use of predictive analytics is now widespread in underwriting and claims, P/C carriers should not lose sight of the prolonged period between the time the premium is paid and a claim is made. MetLife Auto & Home is using data analytics to detect and address "pain points" in the customer experience, which can improve retention and expand customer relationships.

Equally important, but often overlooked, has been the use of data analytics to improve the policyholder experience during those (hopefully) extended periods between the payment of premium and the filing of a claim.

Insurance has a unique challenge in this regard. Traditionally, no news has been good news for carrier-customer relations; the fewer transactions there were in a relationship, the more likely it was successful for both parties.

Today, as business becomes ever more digitized, two trends have emerged that may seem contradictory but are in fact complementary: