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Build a Customer Churn Model

HardMachine Learning00:00
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Problem

Scenario

You are building a churn prediction model for a subscription wellness business. The retention team wants to identify customers who are likely to stop booking services or cancel their membership soon, so they can target outreach and offers before that happens.

Question

How would you build a predictive model for customer churn?

Dataset

Size·240K customer-month snapshots, 62 featuresTarget·Churn within the next 30 daysFeatures·Behavioral, billing, engagement, support, and profile featuresMissing data·Moderate in engagement and support fieldsClass balance·8.7% churn

Success Metrics

  • AUC-ROC for ranking quality
  • PR AUC for imbalanced performance
  • Recall at fixed precision for retention team capacity