Reinventing Fashion Business: Big Data Analytics

Sibichan K. Mathew (), Shelly Rathee () and Michael Burns
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Sibichan K. Mathew: National Institute of Fashion Technology
Shelly Rathee: Villanova University
Michael Burns: Villanova University

A chapter in Fashion Marketing, 2025, pp 325-358 from Springer

Abstract: Abstract The rapid rate of technological change over the past decades has created myriad opportunities for industries to capitalize on insights garnered from Big Data tools, and the fashion industry is no exception. This chapter aims to equip fashion marketing managers and retailers with the appropriate framework to guide selling practices that leverage the day-to-day data available from each transaction and customer experience to maximize both sales and customer satisfaction. We propose a three-pronged approach first analyzing consumer trends in fashion, then identifying customers specific to the fashion industry and applying the proper segmentation, and, finally, discussing tactics to raise sales through cross-selling and upselling opportunities that leverage customer loyalty. Operating in a continually evolving and evermore competitive space, fashion marketing managers must recognize the significance of Big Data, its purpose in business, and the opportunity that proper analytics can unlock. Only companies that prioritize this framework of analyzing trends, identifying their key customers, and effectively cross-sell or upsell to raise sales, revenues, and profitability will continue to prosper in the increasingly saturated fashion market.

Keywords: Fashion trends; Customer identification; Text analytics; Image analytics; Segmentation analysis; Positioning analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-82571-2_12

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