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Op-Ed | Data Alone Can’t Decode the Fashion Consumer

Data-driven algorithms alone can't unravel fashion consumers’ buying behaviour — but neither can humans, argues Tracy Sun of Poshmark.
Street style at Seoul Fashion Week | Photo: Hugo Lee
  • Tracy Sun

SAN FRANCISCO, United States — As another fashion month has come and gone, it's clearer than ever that our sartorial psyche and shopping behaviours are as close to our phones and computers as our fingers are. We can express our personal style, discover new brands and buy items with just a few swipes. And e-commerce — which, by 2018, is expected to generate $86 billion in sales of apparel and accessories in the US alone — is playing a critical role in shaping the fashion industry at large.

We’ve seen apps like Uber, Airbnb and Postmates transform the transportation, hospitality and food industries in ways that were previously considered unimaginable. There’s no doubt that mobile commerce and data-driven personalisation will transform the fashion industry too — and soon.

The challenge will be how we understand and interpret the data this creates. Historically, discovering and purchasing fashion has been an offline, people-powered experience and technology companies are only at the beginning of being able to understand how to replicate this online.

Data is the new black

People are the backbone of the fashion industry. A unique point of view, creativity and other attributes that (currently) can't be reproduced by robots have always been part of the process of fashion. Gucci sends nouveau Renaissance dresses down the runway and, overnight, millions of shoppers want garments with prints, bows and lace. A chic Insta-celebrity wears combat boots and, instantly, a new trend is born. And while social media has enabled brands to somewhat bypass traditional magazines to speak to their customers directly, editors and stylists still decide what to serve up to their readers as the next "it" bag or shoe du jour.

However, with the explosion of information from e-commerce sites, social media, blogs, real-time runway reports and more, fashion trends are now a big data problem. What people are liking, wearing, and interested in buying is all over the Internet. This not only gives brands and retailers greater insight into their customers, but also involves customers in the creation of trends. Trends are no longer dictated down from a few elite figures in the fashion world; they are the result of a more democratic, participatory process.

In e-commerce, data is also being used to aid personalisation and product discovery, by delivering more accurate product recommendations. Retailers can build discovery algorithms based on each shopper’s purchasing behaviour, the items in their shopping cart, or items they have searched for or liked. If a shopper searches online for a 70s-inspired fringe leather jacket, a fashion company can use that data trail to better understand what other products she might like. If she's liked Nasty Gal or Revolve on social media, she may be open to discovering similar brands, such as Style Mafia or Reformation.

Adding this level of personalisation has a significant impact. Thirty-five percent of what consumers purchase on Amazon comes from product recommendations based on algorithms, according to McKinsey & Co. At Poshmark, we process more than 10 million data points per day — from likes, comments and shares to listings, searches and sales — combining social and commerce data to introduce shoppers to new people, brands and personalised product recommendations, resulting in a shopping experience where a sale is made every 5 seconds on the app.

Can robots define style?

There is no doubt that data has the potential to create powerful online shopping experiences. But — and this is a big “but” — what happens to the parts of fashion that cannot be computed?

The fact is, fashion is intensely personal. Our clothing choices reflect a tremendous amount about who we are, how we perceive ourselves, and how we want the world to see us. Clothes can serve as a security blanket, a suit of armour, and a source of confidence, and each fashion purchase is the result of complicated, nuanced and often unconscious factors.

Sure, most of us have a general style and brand affinities that can be tracked by data. But who has never bought something wildly out of character because, for whatever reason, you just love it? Perhaps you saw a woman walking down the street in an outfit that caught your eye. Maybe you recently began a new chapter of your life and want your clothes to reflect that.

So much more than just online searches go into our fashion choices, and it's difficult for data to capture the whole picture. Fashion is emotional and romantic. Women look to one another for style inspiration and get introduced to new brands through friends. In a study by financial services firm Synchrony Financial, 82 percent of millennial respondents said word-of-mouth is a key influencer to their purchase decisions. Algorithms can help brands drive purchasing decisions, but they can't replace the people-driven discovery process that plays a major role in deciding what people buy.

Algorithms alone are not enough, but then again, neither are humans.  Fashion companies must leverage both data and people to create an unbeatable social commerce experience that delivers the excitement, emotion, and nuance of fashion for the digital era.

Tracy Sun is the co-founder and vice president of merchandising as Poshmark, a social app for buying and selling new and second-hand fashion.

The views expressed in Op-Ed pieces are those of the author and do not necessarily reflect the views of The Business of Fashion.

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