How Our Algorithm Works
Segment-Trigger Sensitivity Analysis
We optimize customer segments—using yours or creating new ones—to group similar users. Then analyze how each segment reacts to key triggers like price changes, technical issues, or content updates, forming the foundation for targeted retention.
User-Level Churn Probability Prediction
Our segment-aware ML algorithm analyzes time-series data (daily usage patterns) and static variables (demographics) to generate precise 0-100% churn probability scores for each user, enabling proactive intervention.
Targeted Retention Strategy Execution
Combining churn predictions with segment sensitivities, we deploy personalized retention strategies—tailored packaging, re-onboarding programs, targeted campaigns—optimized to maximize retention for each at-risk customer's unique profile.