Personalization and Customer Relationship Management in AI-Powered Business Intelligence

Abstract

The proposed research presents an AI-enhanced CRM framework designed to improve customer segmentation, predictive accuracy, and personalized engagement. Leveraging advanced Recency-Frequency-Monetary (RFM) segmentation, KMeans clustering, and Gradient Boosting, the model achieves a predictive accuracy of 84.3%, outperforming conventional CRM approaches. Additionally, reinforcement learning enables real-time personalization, dynamically adapting to customer behaviors and enhancing engagement, retention, and satisfaction. Comparative analysis with existing literature underscores the model’s superiority in scalability, segmentation granularity, and predictive reliability. This framework offers a robust, data-driven solution for modern CRM, effectively addressing customer needs through tailored interactions.