AI-Powered E-Marketing Strategies and Their Influence on Consumer Purchase Decisions in Digital Shopping: Evidence from South India

Abstract

Artificial intelligence (AI)-enabled customer e-marketing has driven the overall growth in digital commerce and has changed how consumers enjoy their shopping experience globally. This paper explores how modern applications of AI in marketing practices, like personalization, recommendation engines, and dynamic interaction tool participations, impact the consumer purchasing behaviour in the South Indian region where digital consumption rates are growing rapidly. Using 380 respondents, an Exploratory Factor Analysis (EFA) was used to determine the constructs of the perceptions on the basis of which it shapes consumer perceptions. The findings identified five important factors: AI strategies, trust, convenience, engagement and purchase decisions. Of these, trust and convenience were key to the establishment of consumer confidence and engagement revealed itself to become more of a brand deepening enabler. The results indicate that AI can be used to promote not only the practical dimensions of enjoying shopping, in terms of efficiency and convenience, but also affect positive emotional and relational connection between consumers and online service providers. This paper aids both theoretical and practical discussions by filling a research gap on the adoption of AI-powered marketing in South India, a culturally diverse and an economically savvy region. Theoretically, the study confirms a multidimensional model of association between interventions of AI and the consumer behavioural outcomes, and practically, it provides effective suggestions to e-commerce companies to maximize their online capabilities. Personalization, developing trust, and interactive elements can be successfully combined in order to help online retailers influence purchase intentions and lifelong loyalty. The paper closes by stating that AI-driven e-marketing plans are a disrupter in online purchasing and urges additional studies that utilize confirmatory studies and cross-regional research to establish better generalizability.