Advanced Customer Segmentation Using Probabilistic Machine Learning

Design a comprehensive customer segmentation framework that uses probabilistic clustering techniques like Gaussian Mixture Models and Dirichlet Process Mixtures. Develop a modular approach that can dynamically adjust cluster parameters based on evolving customer behavior data. Include a methodology for handling sparse and high-dimensional customer feature spaces, with specific attention to interpretability and actionable insights for cross-functional teams.