AI DRIVEN AND DATA DRIVEN MARKETING STRATEGIES AS PREDICTORS OF BRAND ENGAGEMENT: THE MEDIATING ROLE OF CONSUMER PREFERENCES AND BEHAVIOUR IN THE UK E COMMERCE INDUSTRY
DOI:
https://doi.org/10.18623/rvd.v23.5822Keywords:
AI-Driven Marketing, Data-Driven Marketing, Brand Engagement, Consumer Preferences, Behavioral Patterns, Fashion RetailAbstract
In the digital age, AI-driven and data-driven marketing strategies have transformed consumer-brand interactions, yet their impact on brand engagement remains underexplored, particularly in fashion retail. This study investigates how AI-powered personalization, predictive recommendations, and chatbots, alongside data-driven segmentation and historical analysis, influence cognitive, emotional, and behavioral engagement among UK online fashion consumers. A quantitative survey was conducted with 350 participants, and reliability, validity, and structural equation modeling analyses were performed. Findings reveal that both AI- and data-driven marketing strategies significantly enhance brand engagement, with consumer preferences and behavioral patterns serving as critical mediators. The results highlight that effective marketing requires not only technological sophistication but also an understanding of the psychological and behavioral mechanisms driving consumer interactions. This study addresses the “quantitative illusion of understanding” by bridging strategic inputs with consumer experiences, providing practical insights for fashion retailers seeking to foster authentic engagement. Implications for theory and practice are discussed, and directions for future research, including cross-industry studies, longitudinal analysis, and ethical considerations in hyper-personalized marketing, are proposed.
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