Automated Customer Segmentation with Machine Learning Pipeline

Design a comprehensive Python script using pandas, scikit-learn, and numpy that automatically segments customer data into distinct clusters using K-Means and hierarchical clustering. The script must handle missing data, perform feature scaling, determine optimal cluster count using silhouette analysis, and generate a detailed report with visualization comparing cluster characteristics. Include error handling for different dataset structures and provide a modular approach that can be easily integrated into existing data infrastructure.