Retention Engine

Predictive User Analytics

Enter a blended matrix score representing user activity. Lower scores typically correlate with a higher statistical risk of cancellation.

Analysis Status

Realtime Statistical Classification

Engine Standby

Provide an engagement score to compute churn vectors.

How This Works (In Simple Words)

This system helps business teams predict whether a customer is about to stop using their product (called "Churn"). Instead of guessing, a backend Logistic Regression model acts like an automated investigator.

  • The Input: You give the system an activity rating from 0 (completely inactive) to 10 (highly active).
  • The Secret Sauce: The mathematical model looks at historical patterns of thousands of past users to find the exact boundary where users typically quit.
  • The Output: It calculates a live Risk Percentage. If the risk is high, product teams can step in, offer a discount, or fix a bug before the customer decides to leave forever.