Big data is changing the face of fashion

How the fashion industry is embracing algorithms, natural language processing, and visual search.


Download Fashioning Data: A 2015 Update, our updated free report exploring data innovations from the fashion industry.

Fashion is an industry that struggles for respect — despite its enormous size globally, it is often viewed as frivolous or unnecessary.

And it’s true — fashion can be spectacularly silly and wildly extraneous. But somewhere between the glitzy, million-dollar runway shows and the ever-shifting hemlines, a very big business can be found. One industry profile of the global textiles, apparel, and luxury goods market reported that fashion had total revenues of $3.05 trillion in 2011, and is projected to create $3.75 trillion in revenues in 2016.

Solutions for a unique business problem

The majority of clothing purchases are made not out of necessity, but out of a desire for self-expression and identity — two remarkably difficult things to quantify and define. Yet, established brands and startups throughout the industry are finding clever ways to use big data to turn fashion into “bits and bytes,” as much as threads and buttons.

In the newly updated O’Reilly report Fashioning Data: A 2015 Update, Data Innovations from the Fashion Industry, we explore applications of big data that carry lessons for industries of all types. Topics range from predictive algorithms to visual search — capturing structured data from photographs — to natural language processing, with specific examples from complex lifecycles and new startups; this report reveals how different companies are merging human input with machine learning.

Using data to drive big sales

Don’t like to shop? Don’t worry. The report encompasses the essence of how fashion brands and startups are using data to drive big sales — and how their techniques relate to what businesses in other industries can do as well.

As we found in our research for the report, one of the things that fashion has always done well is to have two-way conversations with customers. In the report, we interview Eric Colson, who spent six years at Netflix before becoming the chief algorithms officer at Stitch Fix, a personalized online shopping and styling service for women. Colson explains a unique model from the fashion industry:

“Most companies — Google, Yahoo!, Netflix — use what they call ‘inferred attributes’: they guess. We don’t guess; we ask.”

Learn more about the ways in which fashion is making use of big data — download the free report here.

Public domain image on article and category pages via Pixabay.

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