AI-Driven Social Media Analytics in Global Branding

Abstract

The advent of social media and artificial intelligence (AI) has changed how B2B companies carry out their branding. This thesis examines how AI-based social media analytics could contribute to brand trust, global brand equity and sustainable brand positioning. Drawing on the Resource-Based View, Stakeholder Theory, and sustainability-oriented institutional approaches, the research develops a hypothesized framework that relates the use of analytics with value co-creation, alignment of stakeholders, and responsible brand management. Quantitative cross-sectional survey was carried out among B2B professionals in marketing, branding, analytics and sustainability occupation fields. The SPSS and the PROCESS macro were used in analyzing the data to evaluate direct, mediating and moderating relationships. The model proposed value creation and stakeholder alignment as mediators, and institutional and cultural conditions as moderators. The findings indicate that AI-driven analytics has only a modest and diffuse influence on branding outcomes. Direct relationships were weak and statistically non-significant, and neither mediation nor moderation effects were supported. Nevertheless, small directional tendencies appeared in relation to sustainability-oriented branding. These results suggest that analytics currently functions as an enabling tool rather than a strong driver of relational or strategic branding outcomes, offering implications for theoretical development, managerial practice, and future research.