EXAMINING THE EFFECT OF AI-POWERED PERSONALIZATION ON CUSTOMER LOYALTY: A META-ANALYSIS OF E-COMMERCE STUDIES

Abstract

This systematic review explores the evolving intersection between artificial intelligence (AI)-powered personalization and customer loyalty within digital commerce ecosystems. As e-commerce platforms increasingly deploy AI technologies to tailor user experiences, understanding the mechanisms through which personalization fosters loyalty has become both a strategic and scholarly imperative. Drawing on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this study critically analyzed 52 peer-reviewed articles published between 2012 and 2025, spanning disciplines such as marketing, information systems, computer science, and consumer psychology. The review synthesized findings from both experimental and observational studies, incorporating diverse methodologies including structural equation modeling, log-file analytics, and meta-analytic techniques. The results confirm that AI-driven personalization significantly enhances both transactional and emotional dimensions of customer loyalty, especially when implemented through deep learning algorithms, hybrid recommender systems, and real-time behavioral adaptation. Psychological factors such as perceived relevance, trust, emotional bonding, and user satisfaction emerged as crucial mediators in the personalization–loyalty relationship. Additionally, ethical considerations—such as algorithmic transparency, data privacy compliance, and user control—were found to directly influence trust and long-term platform engagement. The review also highlights the importance of contextual and lifecycle-aware personalization, as well as the need for cultural sensitivity and localization when implementing personalization strategies across global markets. This study contributes to the literature by offering a multi-dimensional framework that integrates technological, psychological, ethical, and cultural perspectives on personalization. It challenges the notion of personalization as a static marketing tool and repositions it as a dynamic, systemic strategy for fostering sustainable customer relationships. Key recommendations include the implementation of adaptive personalization systems, integration of ethical design, and the promotion of cross-functional collaboration. The findings offer valuable insights for researchers, platform developers, and marketers aiming to design intelligent, user-centric personalization systems that enhance loyalty in competitive digital environments.