Sarcouncil Journal of Multidisciplinary

Abstract: This article examines the transformative potential of artificial intelligence in addressing customer churn within online marketplace environments. While traditional retention strategies have relied on retrospective analysis and statistical models with limited predictive accuracy, emerging AI methodologies offer unprecedented early churn detection and prevention capabilities. The article explores the theoretical frameworks underpinning customer lifecycle management in digital environments, contrasting conventional approaches with advanced deep learning applications that identify subtle behavioral patterns preceding disengagement. The article investigates how real-time signal detection systems and algorithmic identification of pre-churn indicators enable personalized intervention strategies deployed at optimal moments in the customer journey. The article addresses technical infrastructure requirements, CRM integration challenges, and ethical considerations essential for responsible deployment. As the field evolves, promising research directions include converging predictive and prescriptive analytics, integrating unstructured customer feedback, and cross-platform behavioral analysis. This comprehensive article demonstrates how AI-driven retention strategies represent an incremental improvement and a paradigm shift in preserving customer relationships and maximizing lifetime value in competitive digital marketplaces.