SaaS Customer Churn Prediction Machine Learning Pipeline

Design a comprehensive Python-based machine learning pipeline to predict customer churn for a B2B SaaS platform. Utilize pandas for data preprocessing, scikit-learn for model training, and create a Flask microservice that accepts customer interaction data and returns churn probability with 85%+ accuracy. Include feature engineering for behavioral metrics like login frequency, feature usage, and support ticket volumes. Implement cross-validation and model interpretability using SHAP values to explain churn factors to product management.