Advanced Customer Churn Prediction with Machine Learning

Develop a comprehensive churn prediction model for a SaaS company using a multi-stage approach. Integrate historical usage data, customer support interactions, billing history, and product engagement metrics. Implement feature engineering techniques including time-based decay, interaction complexity scoring, and behavioral clustering. Use XGBoost for predictive modeling and create an interpretable dashboard showing individual customer churn probabilities with confidence intervals.