3 Ways to Maximize the Value of Your Most Likely Customers

Predictive analytics helps you identify which of your website visitors are most likely to convert. Here’s how to get even more out of them.

Insurance carriers can use Predictive Experiences to maximize the value of their most likely customers.

By using a data-science technique known as predictive analytics, several leading carriers are confidently predicting the likelihood that each one of their website visitors will purchase a policy. Using these calculations, they’re able to show consumers a customized, Predictive Experience that enables them to generate the greatest possible ROI from each website visit.

For instance, these insurance carriers have been able to monetize shoppers who are unlikely to purchase a policy by referring them to one of their sister brands or showing them paid click listings for other carriers who might be better positioned to serve them.

However, there’s also a major opportunity for carriers to get even more value out of the consumers who are likely to purchase a policy. Here are three ways to maximize your return from these shoppers.

1. Offer your most likely customers bundled policies

If there’s a high likelihood that a certain group of consumers will purchase a policy after they arrive on your website, it’s best to make sure you’re maximizing the revenue you earn from them.

One good way to do this is by offering these shoppers the option to purchase a bundled policy that allows you to earn greater monthly premiums and deepen your relationship with the customer. Another option is to build a model that predicts how likely certain shoppers are to purchase a bundled policy versus buying only one kind of insurance from you.

2. Use your bind propensity data to inform your customer acquisition strategy

Another way to get more out of high-performing consumer groups is by bringing more of these shoppers to your website. That is, you can adjust your customer acquisition strategy to raise your bids for consumers who are likely to convert.

The one tricky piece of this is that you might not know as much about the consumer when you’re bidding on them as you do once they’ve filled out the quote form with their demographic information, driving history, and household data. However, this problem can be alleviated if you have a data passing integration that allows you to receive the information a consumer filled out on the site that referred them to you.

3. Give your bind propensity data to your underwriting team

If there’s a segment of your audience that is converting at a much higher rate than anyone else, it might be worth taking a look at these outliers and trying to figure out why this is the case.

One possibility is that you’re offering these shoppers quotes that are much, much lower than what they’re seeing elsewhere in the market. If this is the case, you might decide to pass these insights to your underwriting department. These policies could potentially generate more revenue if you raised their rates, and they may in fact represent adverse selection of risk that is not being properly priced.

Read our whitepaper to learn more about how Predictive Experiences can level up your customer acquisition

These are just a few of the ways insurance carriers are using Predictive Experiences to earn millions of dollars in new annual revenue. With the right predictive model, you’ll be able to make all kinds of intelligent decisions that enable you to optimize your customer acquisition and maximize your ROI from every website visitor.

If you’d like to learn more about how you can use Predictive Experiences to upgrade your customer acquisition, our whitepaper has the answers you’re looking for. In it, you’ll learn how predictive models work, how to improve ROI with Predictive Experiences, and how to apply best practices to make your performance even stronger.

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