This study investigates how four dimensions of AI-driven personalization influence long-term customer retention among urban e-commerce users in Bengaluru, Karnataka. Data were collected from 320 online shoppers through a structured 22-item questionnaire and analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modelling (SEM). The findings reveal that AI recommendation quality, personalized communication, dynamic pricing personalization, and user experience personalization significantly enhance customer engagement, which subsequently acts as the strongest predictor of customer retention. AI recommendation quality and personalized communication also demonstrate significant direct effects on retention, while customer engagement partially mediates these relationships. The study contributes to the personalization and retention literature by disaggregating personalization into distinct constructs and validating customer engagement as a critical mediating mechanism within an emerging-market context. The findings provide practical insights for e-commerce firms seeking to improve retention outcomes through more effective personalization strategies...
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