Churn Root-Cause Attribution Model

This task identifies and quantifies the main drivers of customer churn using predictive modeling and explainability techniques. It not only predicts who is likely to churn but explains why, at both individual and aggregate levels. Strategy teams can then design targeted interventions aligned with the most impactful drivers, such as pricing sensitivity or onboarding gaps. The output bridges advanced ML with actionable business insights.