Predictive Analytics in Customer Relationship Management

This research paper delves into the role of predictive analytics in Customer Relationship Management (CRM), exploring how data, statistical algorithms, and machine learning techniques forecast future customer behaviors, preferences, and potential risks. By integrating predictive analytics, businesses can enhance decision-making, improve customer interactions, and drive strategic management. This study highlights the various applications of predictive analytics in traditional CRM, electronic CRM (eCRM), and social CRM (s-CRM), illustrating its benefits across multiple sectors including healthcare, supply chain management, and marketing. The paper also discusses the theoretical framework underpinning predictive analytics, its implementation challenges, and best practices. Through a review of literature and case studies, the paper underscores the transformative potential of predictive analytics in CRM and its implications for future business strategies [1]–[5].