GENERATIVE AI IN FASHION RETAIL: DRIVING CUSTOMER ENGAGEMENT THROUGH CONTEXTUAL RECOMMENDATIONS

Paper ID: EIJTEM_2024_11_4_104-113

Author's Name: Shiva Chandrashekher

Volume: 11

Issue: 4

Year: 2024

Page No: 104-113

Abstract:

Fashion recommendation systems have become a pivotal aspect of e-commerce and retail, enhancing user experiences by providing personalized and efficient clothing suggestions. This paper proposes an AI-driven system for clothing data retrieval and analysis to address the challenges of diverse fashion preferences, seasonal trends, and dynamic user demands. The proposed system not only facilitates efficient retrieval of fashion items but also provides insights into emerging trends and user preferences. Experimental results demonstrate its effectiveness in improving recommendation quality, user satisfaction, and engagement. This research paves the way for innovative applications in the fashion industry, bridging the gap between technology and personalized style discovery.

Keywords: Fashion Recommendation, Artificial Intelligence, Clothing Data, Personalization, Trend analysis

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