In recent years, a growing number of insurance carriers have turned to data science to monetize their non-converting website visitors. These carriers are using predictive analytics to build algorithmic models that can analyze their historical consumer data and predict how likely each shopper is to purchase a policy after arriving on the website. If the shopper is predicted to be unlikely to buy, the carrier can monetize them by showing alternative listings for other carriers on the quote page.
This strategy has opened an impactful new revenue stream for carriers, with some insurance brands earning revenues equivalent to 20% to 30% of their overall digital marketing costs—in some cases tens of millions of dollars annually. Some carriers are holding onto this revenue as profit, while others are reinvesting it in customer acquisition by using it to expand their marketing budgets. Either way, the new revenue is making a big difference.
In a recent article for Digital Insurance, our co-founder and CEO Steve Yi explained how insurance carriers can employ and optimize this strategy to maximize the value of every consumer action. In it, he discusses why carriers are choosing predictive analytics, how they’re able to avoid undermining their policy sales, and how they show the right user experience to each site visitor.