Predictive analytics is a growing trend in insurance advertising, but many in our industry are still learning what it is and how to use it most effectively.

Executive Summary

If you know someone is not going to buy a policy from you, why throw out the opportunity to earn revenue by serving an ad to another carrier? In this article, Steve Yi, co-founder and CEO of MediaAlpha, a tech company that uses data science to help businesses optimize customer acquisition, describes this seemingly counterintuitive, untapped opportunity for insurance carriers and explains how marketers can leverage predictive analytics to increase monetization of their traffic. Serving competitive ads to users who might qualify as high-risk or out of your geographical reach opens up a highly effective, zero-risk revenue stream that can be used to offset your digital marketing costs and increase profits, he explains.

One of the big advantages of the ongoing shift to digital is that it gives insurance carriers a treasure trove of valuable new information about the consumers who visit their websites. With the right reporting tools in place, carriers can learn a great deal about these shoppers: where they’re located, which digital channels they arrived from, and whether they requested a quote or purchased a policy, among other details. With predictive analytics, carriers can use this information to make smarter decisions about how they engage these shoppers.

When carriers use predictive analytics, they build an algorithmic model that analyzes their historical data and predicts the behavior of the consumers they will interact with in the future. For instance, if a carrier’s model identifies that a certain group of website visitors is especially likely to purchase a policy, it might predict that future consumers who share the same demographic attributes will convert at a similar rate. Based on this information, carriers can make informed choices about the best ways to tailor their site experience to the needs of these high-value consumers.

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