Impact of Digital Fashion Shows on Consumer Engagement with Fashion Brands in Nigeria

Purpose: The aim of the study was to analyze the impact of digital fashion shows on consumer engagement with fashion brands in Nigeria. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Digital fashion shows have significantly enhanced consumer engagement with fashion brands in Nigeria by offering a dynamic, accessible online experience. These virtual events have allowed brands to reach a broader audience, increasing their visibility and facilitating direct interaction with consumers. Real-time feedback during these shows has enabled brands to fine-tune their marketing strategies and product offerings to align with consumer preferences. The use of augmented reality technologies has further personalized the shopping experience, leading to increased consumer interest and brand loyalty. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM), uses and gratifications theory (UGT) & engagement theory may be used to anchor future studies on impact of digital fashion shows on consumer engagement with fashion brands in Nigeria. Fashion brands should leverage a combination of VR, AR, and live-streaming to create more engaging and immersive experiences. By investing in these technologies and incorporating high-quality digital content, brands can enhance consumer interaction and foster deeper emotional connections. Policymakers and industry bodies can work together to establish standards for digital content, technology integration, and consumer privacy protection, which will enhance the overall consumer experience and build trust in digital fashion shows.