Customer Relationship Management (CRM) systems have evolved significantly by integrating machine learning (ML) techniques, transforming how businesses understand, predict, and respond to customer behavior. This comprehensive review examines the current landscape of ML applications in CRM, analyzing key techniques, application areas, challenges, and future directions based on recent literature from 2019 to 2025. Our analysis reveals that ML techniques in CRM span from traditional classification and clustering methods to advanced deep learning, natural language processing, and reinforcement learning approaches. Key application areas include churn prediction, customer lifetime value estimation, personalization, sentiment analysis, and customer segmentation. While significant progress has been made, challenges remain in model interpretability, bias mitigation, and production scalability. This review provides insights into emerging trends such as domain-aware language models, graph neural networks, and ethical AI considerations in CRM implementations
Godwin Abugbilla (Wed,) studied this question.