AI-Driven Customer Analytics and Personalized Marketing: Examining Customer Experience, Loyalty and Purchase Intention In Digital Markets

Abstract

The present study investigates how AI-driven customer analytics and personalised marketing influence customer experience, customer loyalty and purchase intention in digital markets, applying a Stimulus-Organism-Response framework extended with privacy concerns as a boundary condition. Data were drawn from a quantitative survey of respondents recruited through online panels; indicator reliability, convergent validity, discriminant validity and a series of nested regression models were estimated. Results show that AI-driven personalisation has a strong positive effect on customer experience (β = 0.492, p < .001) and that experience, in turn, is the strongest single predictor of purchase intention (β = 0.245, p < .001). Customer loyalty carries a substantial additional effect on purchase intention (β = 0.233, p < .001) and mediates approximately one fifth of the total CX→PI relationship. Privacy concerns exert a small but significant negative effect on purchase intention (β = −0.099, p < .05) without moderating the personalisation path (interaction β = 0.003, n.s.). The model explains 28.8 % of the variance in purchase intention. Findings suggest that the business value of AI-driven personalisation lies primarily in improving the customer experience, which then cascades into loyalty and purchase decisions. Theoretical, managerial and policy implications are discussed.