Understanding the nexus of personalized marketing on consumer behaviour through artificial intelligence

Abstract

The purpose of this study is to investigate how Artificial Intelligence (AI)driven personalization influences consumer behaviour in digital marketing and understand the relationship between consumer behaviour and AI-driven personalized tactics. Using a mixed-method approach with data from 100 participants, the research tests 14 hypotheses through structural equation Modeling and ANOVA. Findings reveal that time-saving features and feeling valued significantly enhance consumer trust and behaviour al intentions such as platform recommendation and repurchase. However, perceived relevance and historical alignment of AI suggestions do not significantly influence trust, indicating that emotional resonance may outweigh functional personalization. Demographic factors such as gender, age, income, and education have significantly influenced consumer perceptions. At the same time, privacy concerns have negatively influenced trust. The study highlights the need for ethical data practices and user-centered AI strategy to foster engagement and trust. AI personalization must balance technological precision with emotional and ethical considerations to effectively shape consumer behaviour and marketing success in data-driven environments.