How Facebook Ads Use Predictive Churn Scoring

In this episode, Lucas and Luna dive into how Facebook advertisers use predictive churn scoring to identify users likely to stop engaging before they disappear. They break down the mechanics: training a model on behavioral signals like declining session frequency, shrinking time-in-app, and reduced ad interactions, then feeding that score into Custom Audiences for targeted win-back campaigns. Lucas cites a case where a subscription meal-kit brand reduced churn by 18 percent by serving high-churn users a re-engagement offer within 48 hours of their score crossing the threshold. Luna questions the risk of over-targeting low-propensity users and whether the approach works for non-subscription businesses like e-commerce. The episode also covers how iOS 14 has made churn scoring harder by limiting conversion events, and the workaround of using aggregated event measurement with modeled churn proxies. A practical look at a retention tactic that flips Facebook from an acquisition engine into a loyalty tool. #PredictiveChurnScoring #FacebookAds #RetentionMarketing #CustomerChurn #WinBackCampaigns #MachineLearning #CustomAudiences #iOS14 #AggregatedEventMeasurement #SubscriptionBusiness #Ecommerce #AdTargeting #MarketingStrategy #Meta #ChurnPrediction #Marketing #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo