THE ROLE OF AI-ENABLED CUSTOMER SEGMENTATION IN DRIVING BRAND PERFORMANCE ON ONLINE RETAIL PLATFORMS

Abstract

This study examines the role of artificial intelligence (AI)–enabled customer segmentation in enhancing brand performance on online retail platforms, addressing how data-driven audience design translates into measurable marketplace outcomes. Using a quantitative, cross-sectional, case-based design, the research analyzes relationships among AI-enabled segmentation capability, personalization quality, customer engagement, data governance strength, and platform-based brand performance, controlling for firm size, category, advertising spend, tenure, and price tier. Data were gathered through structured five-point Likert-scale surveys from 200 brand-side professionals responsible for e-commerce and performance marketing within a focal marketplace ecosystem. Statistical analyses—including reliability and validity tests, Pearson correlations, hierarchical OLS regressions with robust (HC3) errors, and bootstrapped mediation and moderation models—reveal that AI-enabled segmentation capability has a strong positive effect on brand performance (β = .31, p < .001), explaining an additional 10% of variance beyond structural controls. The relationship is partially mediated by personalization quality and customer engagement, with significant indirect effects (AISC → PQ → BP = .09; AISC → CE → BP = .06, 95% CI excluding zero), indicating that improved relevance and deeper interactions are key pathways through which capability drives performance. Moreover, data governance moderates this relationship (β = .14, p < .01), showing that segmentation under stronger consent, access, and quality controls yields steeper performance gains than under weaker governance. Descriptive findings indicate moderate-to-high maturity across firms (AISC M = 3.78; PQ M = 3.58; BP M = 3.62 on a 1–5 scale), with governance showing the widest dispersion (M = 3.36, SD = 0.82). Overall, the results establish that AI-enabled segmentation enhances brand outcomes when supported by experiential excellence and disciplined data stewardship. The study contributes to marketing analytics and dynamic capability theory by demonstrating that segmentation, personalization, engagement, and governance function as interdependent levers of brand performance, and it recommends that firms institutionalize segmentation as a continuously refreshed, governance-anchored process to maximize platform returns.