IMPACT OF AI-DRIVEN PERSONALIZED MARKETING ON CONSUMER BUYING BEHAVIOUR IN THE E-COMMERCE SECTOR

Abstract

The rapid integration of artificial intelligence (AI) in the e-commerce sector has transformed how firms engage with consumers, particularly through personalized marketing strategies such as recommendation systems, dynamic content, targeted advertising, and AI-enabled chatbots. This study examines the impact of AI-driven personalized marketing on consumer buying behavior, focusing on how personalization influences perceived relevance, trust, purchase intention, and overall satisfaction. A comprehensive review of recent literature highlights that effective AI personalization enhances consumer engagement and significantly increases purchase intention by reducing search effort and presenting contextually relevant product suggestions. However, the study also identifies critical moderating factors, including privacy concerns, perceived intrusiveness, and transparency in data use, which can weaken or reverse personalization’s positive effects. The proposed conceptual model suggests that perceived relevance and trust mediate the relationship between personalization and buying behavior, while privacy concerns moderate these effects. The findings underscore the need for e-commerce firms to balance personalization performance with ethical data practices, clear communication, and user control to maximize consumer acceptance and long-term loyalty. This research provides theoretical insights and practical implications for marketers, platform designers, and policymakers striving to optimize AI-driven customer experiences in digital commerce.