How CMOs Use Silent Subscriber Data to Predict Churn - Churn prediction - The CMO Podcast with Fexingo

Topics in this episode

Churn prediction customer retention silent subscriber data engagement entropy mckinsey 2025 study

Episode notes

Episode 107 of The CMO Podcast explores a counterintuitive marketing insight: the most dangerous customer isn't the one who complains - it's the one who goes quiet. Hosts Lucas and Luna dig into a 2025 McKinsey study that found silent subscribers - those who stop opening emails, stop engaging with push notifications, and stop logging in - are 3.7 times more likely to churn within 60 days than customers who actively unsubscribe. They walk through how Unilever's personal care division used this behavioral signal to build a predictive model that cut churn by 22% in six months, and why CMOs are now hiring data scientists to monitor 'engagement entropy' rather than just survey scores. Lucas challenges the conventional wisdom that silence equals satisfaction, and Luna shares a cautionary tale from a fintech startup that ignored the quiet signals until it was too late. This episode is essential listening for any marketing leader who wants to identify at-risk customers before they vanish without a trace.

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