AI-powered personalized advertising and purchase intention in Vietnam’s digital landscape: The role of trust, relevance, and usefulness

As AI-powered personalized advertising becomes increasingly prevalent in the digital marketplace, understanding its influence on consumer purchase intention is essential. This study investigates the impact of perceived personalization on purchase intention, with a particular focus on the mediating roles of perceived relevance, perceived trust, and perceived usefulness. Utilizing a quantitative research design, data were collected from 402 users of digital platforms in Vietnam who have encountered AI-driven personalized advertisements. The proposed research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships among key variables. The findings reveal that perceived personalization significantly enhances both perceived relevance and perceived usefulness, highlighting the effectiveness of tailored advertising in increasing consumer engagement. Although perceived personalization does not directly influence trust, it indirectly fosters trust by enhancing the perceived relevance and usefulness of personalized content, indicating that trust must be cultivated through perceived value rather than personalization efforts alone. Furthermore, perceived relevance, trust, and usefulness are confirmed as significant drivers of purchase intention, underscoring their critical roles in successful personalized marketing strategies. This research contributes to the theoretical understanding of consumer responses to AI-powered personalized advertising by integrating key perceptual factors influencing purchase behavior. From a practical perspective, the findings offer valuable guidance for businesses seeking to enhance personalization strategies by prioritizing relevance, usefulness, and trust-building initiatives.