How the Fashion Industry Uses Big Data

While predicting the next trend is important in the fashion industry, more designers and clothing producers are turning to business analytics and technology tools to inform their design pipeline choices. Customers respond not only to social marketing influences regarding what is trendy, but they also return to brands whose quality and prices reflect their own preferences. Collecting and analyzing data in this way is becoming more critical for the modern fashion designer and retailer.

Big Data Is in Style

Historically, customer data in this regard has been soft and poorly collected. Now, with modern business analytics tools, designers can capture data sets that give them insight into the market penetration rate of a specific trend, the longevity of the trend and the variability of the prices and styles within that trend. As big data figures more prominently into fashion, designers and retailers can more accurately predict and adapt to changing market patterns.

Customizing Markets

Business intelligence tools can provide historical graphs of the height of skirt hemlines or the narrowness of pant legs. Data modeling tools can chart customer preferences for color choices based on geographical location, seasonal purchasing, and other localized metrics that can help retailers customize their offerings for various markets. Jackets with dark blue and electric green colors will sell more effectively in the Pacific Northwest, due to the proximity of the Seattle Seahawks, versus markets in Arizona or New Mexico, for example.

Predicting the Future

All markets are cyclical, and the fashion market is no different. Analysis of data over time can help designers and retailers predict upcoming trends. Given the length of the production pipeline for any retail season, it is important for designers to have reasonably accurate forecasts of pending trends so that they do not design for a trend that does not come to fruition. Production agility, paired with insightful business analytics, enables successful designers to appear prescient with their new lines. In fact, this foresight adds to the mystique and desirability of their brands.

Real-Time Data Is on the Way

As retailers and designers collect more big data in fashion, they will gain insight into other aspects of customer interaction with various brands that will help them more aggressively and competitively manage pricing models, markdown schedules, inventory planning and seasonal availability. As data approaches real-time availability, retailers can determine the effectiveness of advertising campaigns across print, online and social media channels. While understanding the desirability of a given brand may remain somewhat elusive, modern business intelligence tools can provide other concrete insights into the customers’ interactions with a brand. How often customers return to a brand; how much they are willing to pay for a brand; how readily they share their purchases with their social networking circles: designers and retailers can use all of this data to build lifetime models of brands’ success in the market. With this intelligence, designers can more accurately predict a given product’s market before they even commit it to the production pipeline.

Learn more about the University of Tennessee Chattanooga online MBA with Business Analytics Concentration program.


Sources:

http://apparel.edgl.com/news/The-Fashion-Industry-Finds-a-Crystal-Ball-in-Data-Analytics88372

http://fortune.com/2014/09/22/fashion-industry-big-data-analytics/

http://radar.oreilly.com/2015/09/big-data-is-changing-the-face-of-fashion.html


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