Mapping the Landscape of Social Media Engagement Metrics and Purchase Intention: A Bibliometric Analysis and Future Research Agenda

Abstract

While the study of social media and its metrics, such as likes, shares, comments, and sentiment score, has been important in determining consumer purchase intention, especially in the retail industry in the context of urban millennials, the literature is scattered. The study uses bibliometric analysis of over 1,200 documents indexed in Scopus (2010–2025), to map the publication trends, thematic clusters, influential authors/journals, and research gaps for engaging with purchase models such as TAM and ELM. Through the use of VOSviewer and Bibliometrix, we can establish five main clusters: metric validation, platform-specific engagement (e.g., Instagram Reels), influencer effects, behavioural outcomes, and cross-cultural dynamics (with China/US leading outputs). Results show that it has grown exponentially after 2020, h-index leaders such as Dwivedi and Ismagilova, and areas not yet explored such as the implementation of AI-based metrics in emerging markets, such as India. Theoretical implications involve a new conceptual model that combines engagement funnels with intention predictors, while managerial implications highlight the need for retailers to focus more on interactive metrics than vanity metrics. Limitations are English-only focus, future plans are mixed methods validation (Odisha-style regional retail).