Advanced Customer Lifetime Value Predictive Model

Design a comprehensive Python script using machine learning techniques to predict customer lifetime value (CLV) for an e-commerce platform. Integrate multiple data sources including transaction history, website interactions, and demographic data. Implement feature engineering techniques to handle categorical variables, create interaction features, and use ensemble methods like XGBoost or Random Forest. Include cross-validation with stratified k-fold, calculate feature importance, and develop a deployment-ready prediction pipeline with model interpretability using SHAP values.