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Research Paper | Commerce and Economic Studies | Volume 15 Issue 5, May 2026 | Pages: 1327 - 1334 | India
Smart E-Commerce: A Reinforcement Learning Framework for Optimizing Customer Retention Strategies
Abstract: In the highly competitive and dynamic e-commerce landscape, it has become a critical issue for businesses to retain customers. The acquisition of new clients is essential but retaining existing ones can often be more cost-effective and equally important to any business's success, especially in terms of revenue, customer lifetime value (CLV), and long-term brand loyalty. In order to optimize customer retention techniques for e-commerce platforms, this review paper looks at artificial intelligence (AI), specifically reinforcement learning (RL). This study presents and discusses key benefits and drawbacks of implementing intelligent retention technologies, using a summary of key research on customer retention concepts, AI applications, and RL-based frameworks. The study explores the fundamental concepts of reinforcement learning (RL), including Markov Decision Processes (MDPs), state encoding, action space and reward functions, and discuss potential adjustments to capture complex consumer interactions. The following applications are explored to demonstrate the value of RL in implementing proactive, data-driven strategies that help maximize long-term client value: adaptive engagement interventions, dynamic pricing, and personalized recommendations. The paper also discusses the ethical issues of privacy, bias, and transparency in AI-driven retention frameworks, as well as new trends like Deep RL and Multi-Agent RL and their possible economic implications. The study concludes with recommendations for future research in this field, such as explainable AI, hybrid RL models, integration of multiple channels, and privacy-preserving approaches, to enhance the effectiveness and reliability of customer retention systems.
Keywords: E-Commerce, Customer Retention, Reinforcement Learning, Artificial Intelligence, Personalized Marketing
How to Cite?: Neha Bishnoi, "Smart E-Commerce: A Reinforcement Learning Framework for Optimizing Customer Retention Strategies", Volume 15 Issue 5, May 2026, International Journal of Science and Research (IJSR), Pages: 1327-1334, https://www.ijsr.net/getabstract.php?paperid=SR26521075254, DOI: https://dx.dx.doi.org/10.21275/SR26521075254