Complex Customer Lifetime Value Predictive Model

Develop a comprehensive Python script that calculates customer lifetime value (CLV) using advanced probabilistic modeling. Incorporate multiple data sources including transactional history, behavioral metrics, and demographic information. Implement a Bayesian survival analysis approach that accounts for customer churn probability, integrating machine learning techniques to predict future revenue potential. The model should handle sparse datasets, provide confidence intervals, and generate both point estimates and probabilistic forecasts.