Purpose – This paper analyzes how Artificial Intelligence (AI) and Machine Learning (ML) are involved in the creation of personalized digital marketing campaigns and measures their impact on consumer perceptions, trust, and intentions to buy. Through consumer responses analysis, the study points out engagement/loyalty effects of data-driven personalization strategies in the digital market. Design/methodology/approach The method used was a quantitative survey aimed at 455 Pakistani digital consumers who are active. An ordered questionnaire with close-ended questions was used to measure demographics, online shopping, and AI/ML awareness, personalized advertising exposure, and attitude toward effectiveness, trust, and purchase intentions. Descriptive and inferential statistics, such as frequencies, percentages and the measures of central tendency were used to analyze the data and reveal some major patterns and associations. Findings – The findings showed that consumers had a high level of awareness of AI/ML technologies and most of them indicated that they have seen personalized advertisements relatively often. The majority of respondents also thought that personalized campaigns made them more attentive, relevant, and generally shopping were more enjoyable, and they also saved their time. The trust increased significantly when transparency was applied in the use of the data, yet the issue of privacy remained. Moreover, more than three-quarters of the participants reported that the concept of personalized marketing must have a positive impact on buying behavior, interactions with AI-powered brands, and the willing to purchase again, which can be discussed as a strong positive factor in determining consumer intentions. Originality/value – The research makes a contribution to the existing field of knowledge about digital marketing since it gives empirical proof regarding the influencing power of AI and ML-based personalization in the context of a developing country. Its results highlight the two-fold aspect of personalization used to improve consumer experiences and increase privacy concerns, which provide practical information to marketers, policymakers, and digital platforms focused on creating responsible and consumer-centric strategies.
Afzal et al. (Sat,) studied this question.