<![CDATA[Objective: Understanding customer behavior is fundamental to effective market forecasting and personalized service delivery. This paper presents AI-based customer behavior analytics models that leverage deep learning and clustering techniques to segment customers, predict purchasing patterns, and enable personalized marketing strategies. Method: Our multi-layered approach integrates collaborative filtering, sentiment analysis, and sequential pattern mining to create comprehensive customer profiles. Results: Validation using e-commerce datasets shows prediction accuracy improvements of 31% over traditional methods, with personalized recommendations achieving a 24% increase in conversion rates. Novelty: The research contributes to customer relationship management theory and provides actionable insights for businesses seeking to enhance customer engagement through data-driven personalization.]]>
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