For this health and life insurance company, direct mail was a go-to channel for acquisition. However, it struggled to find enough qualified prospects to scale the success of the program. They challenged Alliant to produce an audience of prospects incremental to their existing data sources – and capable of achieving aggressive KPI goals.

When packaging prospect audiences for direct mail targeting, standard practice is to start with a baseline of consumers who have recently responded to direct mail offers. While recency and response channel are indeed powerful predictors, Alliant needed to innovate a different approach to uncover a new stream of prospects beyond what they were getting from other providers. The solution was social.

The Alliant data scientists harvested consumers that follow health & Medicare brands on social media, including the insurance company's account and those of competitive brands. They mapped the followers to Alliant's prospect database and identified prospects that most resemble the harvested audience using a look-alike model. Lastly, they scored the audience with an optimization model to predict those most likely to respond through direct mail.

Alliant produced a new source of prospects and drove a CPA (cost per acquisition) that was 68% better than campaign average. Pleased with the results, the insurance marketer now considers Alliant a key source for data innovation and audience targeting solutions across campaigns.