AI Workflow: AI Churn Prevention

AI Churn Prevention identifies customers at risk of leaving before they cancel, giving your team time to intervene with targeted retention actions. The workflow ingests signals from multiple sources — product usage declining, support ticket frequency increasing, login frequency dropping, payment failures occurring, and stakeholder engagement waning. AI builds a churn probability score for each customer that updates daily, typically identifying at-risk accounts 30-60 days before cancellation. When a customer's churn score crosses a threshold, automated workflows trigger — from personalized re-engagement emails to customer success manager alerts with specific context about what changed. Companies using AI churn prediction reduce churn by 15-30% through timely, data-driven intervention rather than reactive save attempts. ShipSquad implements this by connecting your product analytics (Amplitude or Mixpanel) and CRM data to AI prediction models, configuring risk score thresholds that trigger different intervention levels, and building automated playbooks that combine AI-generated outreach with human touchpoints for high-value accounts.