Churn prediction uses AI to identify customers at risk of canceling before they actually churn. This enables proactive retention efforts. Signals used for prediction: - Engagement decline - Support ticket history - Payment issues - Product usage patterns - Communication response rates - Time since last activity Interventions for at-risk customers: - Proactive outreach - Special offers - Product education - Account health check-ins - Feature highlighting Benefits: - 20-30% improvement in retention rates - Focus resources on high-value saves - Early intervention effectiveness