3 Tips for Getting the Most Out of Predictive Experiences

Best practices for maximizing the value of every website visitor with Predictive Experiences

These tactics will help you get the most out of your predictive experiences in the insurance vertical.

Recently, we’ve been writing about how insurance carriers can earn tens of millions of dollars in new revenue annually by using Predictive Experiences to tailor the consumer shopping journey to each website visitor, based on how likely each shopper is to purchase a policy.

When you use predictive analytics to build an algorithmic model, you’re able to analyze your past conversion data to predict with great confidence how likely each site visitor is to bind. You can then use these predictions to deliver customized, Predictive Experiences designed to generate the most revenue possible from each visitor. For instance, if a consumer is highly unlikely to bind, you might decide to show them alternative offers for other brands that are owned by your parent company—or to monetize them by showing listings for carriers outside your family of brands.

Like anything, maximizing your performance with Predictive Experiences takes a little bit of planning and practice. Here are three best practices for getting the absolute most out of your predictive model.

1. Make decisions based on your actual customer base, rather than an ideal one

A common mistake carriers make when they’re first getting started is to confuse their desired customers with the ones they actually have. For instance, insurance brands sometimes decide not to show listings to the consumers they think of as their target customers, even if the data reveals that these shoppers don’t actually convert all that often. As a result, carriers leave listings revenue or referrals to sister carriers on the table by allowing unlikely customers to leave their websites without having the chance to click on other offers.

You can correct for this error by making sure your predictive models are based on your conversion data—and by making sure that everyone involved in your decision-making understands and trusts the models. This way, you’ll be able to generate significant revenue from shoppers who are unlikely to buy your policies, even if some of those shoppers are among your perceived ideal customer base.

2. Send email listings to lapsed shoppers

Let’s say you have an unlikely shopper whom you show a set of alternative offers alongside your own quote. What if they don’t click on either the listings or the quote? There’s a good chance they’re still going to be in-market for a policy after leaving your page—and if you’re smart, you can still monetize them.

One effective option is to send these shoppers an email that displays additional listings for other carriers who might have what they’re looking for. Once you give your sister brands or outside carriers the information that the consumer shared when they filled out the quote form on your site, they’ll be in a strong position to show the shopper an offer for a product that meets their needs. In the process, you’ll generate new revenue with each external click or sister-brand policy sale.

3. Extend Predictive Experiences beyond your click campaigns

While the examples we’ve outlined here are primarily related to the consumers who visit your website through click advertising campaigns, the principles of Predictive Experiences are extensible across your marketing efforts. That is, you can use the same strategies in thinking about how you tailor the consumer experience to shoppers who request a quote via a phone call or those who you contact after purchasing a lead. For instance, if you get a call from a shopper who appears unlikely to bind after you run their information to provide a quote, you might try transferring them to another carrier inside your corporate umbrella.

Want to learn more about Predictive Experiences? Check out our whitepaper.

These are just a few of the ways insurance carriers can earn more revenue from the in-market insurance shoppers who are already on their websites. In our Predictive Experiences whitepaper, we dive deep into how predictive models work and all the different ways you can use them to deliver customized shopping experiences that generate the greatest ROI from every site visitor.

If you have any questions about how you can use Predictive Experiences to take your own customer acquisition to the next level, we’d be more than happy to speak with you. Reach out to your MediaAlpha account manager to find a time to talk, or schedule a meeting with us on our website.

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