Digital Influence: Consumer Behavior And Brand Dynamics In Fashion

Abstract

This thesis investigates how digital marketing shapes consumer behavior and firm performance in fashion through a qualitative, multiple–case study of Gucci (luxury) and ASOS (fast fashion). Using secondary data (peer-reviewed studies, industry reports, company materials) and descriptive analysis of publicly reported indicators (social metrics, revenue trends, conversion effects), the study compares channel mixes (social/influencer, email/CRM, SEO/SEM), experiential tools (AR/VR), and data-driven personalization. Findings show that Gucci’s blend of immersive storytelling, influencer strategy, and AR try-ons coincided with a rise in revenue from €3.9B (2015) to >€9.6B (2019) alongside follower growth from ~10M to >40M on Instagram; AR footwear try-ons were associated with conversion lifts of up to 300%. ASOS’s multi-channel personalization (segmentation, recommendations, app notifications) contributed to material revenue uplifts (e.g., ~$77.5M in one year), a 19% YoY rise to ~£3.26B, and rapid community growth, illustrating the commercial impact of data-centric execution at scale. The cross-case synthesis concludes that digital is not monolithic: for luxury, narrative depth and experiential media (AR/VR) best amplify perceived value and loyalty; for fast fashion, operational agility and mass personalization drive frequency and conversion. Managerially, brands should (i) align channel strategy to positioning, (ii) invest in privacy-aware data infrastructure and omnichannel orchestration, and (iii) treat AR/VR and creator ecosystems as performance levers, not mere brand theater. The study offers a practical framework linking tactic, consumer response, and business outcome, and outlines avenues for future research on causal measurement and long-horizon loyalty effects.