Recently, a small group of insurance carriers have turned to a rather unorthodox strategy for earning incremental revenue and offsetting their customer acquisition costs: They’re showing their competitors’ ads on their own websites.
At first blush, this strategy may sound counterintuitive. After all, it means carriers are making it easier for their own website visitors to find and purchase policies from their competitors.
But due to advances in data science, these carriers are able to use predictive analytics to determine how likely each site visitor is to purchase a policy from them. By analyzing their historical conversion data and identifying the specific attributes of consumers who are most likely to bind, carriers can build a model to predict future behavior. If a carrier’s predictive model suggests a consumer is highly unlikely to bind, they can serve comparison ads from other carriers in addition to a quote. By doing so, carriers can monetize a greater portion of their audience and make back some of the money they spend bringing non-converting shoppers to their website.
This is not just hypothetical. Several forward-thinking carriers are already using this strategy to generate incremental revenue—in some cases up to 20% to 30% of their digital marketing costs. They can then keep their new revenue as pure profit, or re-invest it into the top of the funnel to scale their customer acquisition efforts.
If you’re still uncertain as to how all this works, here’s a little more insight into how predictive analytics is helping insurance carriers maximize the value of every consumer interaction.
Most website visitors don’t convert
From TV branding campaigns to performance marketing, leading carriers spend hundreds of millions of dollars each year driving consumers to their websites to request a quote and hopefully purchase a policy. While typically only a single-digit percentage of those consumers will wind up converting, the rest of a carrier’s website visitors can still be extremely valuable.
Think of it this way: The people who arrive at a carrier’s quote page are in-market shoppers who have already spent the time filling out a lengthy quote form. In other words, this audience gives insurance carriers what is effectively the holy grail of digital publishing—a large group of website visitors that have both signaled their intent to purchase a product and given the website operator valuable demographic data. So it makes sense that insurance carriers would have the opportunity to sell ads the same way publishers do.
Now, some brands are starting to capitalize this opportunity by thinking of themselves as publishers in addition to insurance carriers. Of course, these carriers wouldn’t sell ads on their websites if they thought it would undercut their own core business. But by using their predictive models, they can confidently estimate the likelihood that each shopper will buy a policy. This way, they can choose which consumers to show ads to, and which ones to only show a quote.
Carriers can offer a range of ad experiences
Above all else, predictive analytics gives carriers the information they need to tailor their monetization strategy to each site visitor. Through their models, carriers can sort consumers into groups based on their likelihood to bind and adjust the user experience accordingly.
In some instances, the calculus is fairly straightforward. Every insurance carrier gets website visitors that it is unable to quote—either because the consumer lives in a state where the carrier doesn’t write policies, or because the insurer only covers standard or non-standard shoppers and the consumer is not a match. Since the insurance brand can’t show these users a quote, it might as well show a prominent ad in a visible location where the shopper is likely to click on it.
Other cases require a little more nuance. Rather than viewing quote page ads as a switch to be turned on or off, insurance brands are most successful when they offer different kinds of ad experiences. For example, if an insurance brand’s predictive modeling identifies a certain category of consumer as eligible to purchase a policy but especially unlikely to do so, it might choose to display a prominent click ad right beside its own quote. If the consumer is somewhat likely to bind, the carrier might show a prominent quote and a smaller ad lower down the page. And if the consumer is highly likely to bind, the carrier might not show them an ad at all.
Predictive analytics gives carriers a big leg up
As carriers continue shifting budget to digital customer acquisition, the marketplace for attracting new consumers will only become more competitive. This means advertisers are becoming increasingly willing to pay top dollar to reach their most valuable consumers. In this sort of climate, a strategy that recoups 20%-30% of a carrier’s digital marketing costs is an opportunity that insurance brands can’t ignore.
The future of digital customer acquisition will be won by the carriers who are able to use data science to squeeze the most value out of every consumer interaction. If an insurance brand isn’t using predictive analytics to intelligently monetize its website audience, it’s going to fall behind the carriers that are.
