Healthcare payor saves
$6M with Acxiom predictive retention model
How predictive modeling helped a healthcare payor identify at-risk members, reduce attrition, and improve retention ROI.
Members have various options and evolving needs, and a policy cancellation is rarely due to a single reason. Such decisions are usually based on a combination of factors, requiring comprehensive member and historical analysis to identify reliable triggers and insights to positively influence those members designated to be at risk.
the solve
How we helped
Acxiom developed a predictive retention model that ranks members by risk level, enabling proactive outreach to those at highest risk. Our analytics experts integrated third-party data with client records to enrich member insights in a privacy-compliant environment. As a result, the payor was empowered to take timely, targeted action to retain those most likely to churn.
$6M
in savings
214%
campaign ROIIncrease
This program saved the payor $6 million by retaining at-risk members and more than doubled the campaign ROI achieved by reaching the right members at the right time, before the decision was made to cancel a policy.
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