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Taking Social Media Analytics to Fashion Week

Written on
Feb 3, 2012 
Author
Trevor Davis  |

ADOTAS – Fashion Week is about to descend upon New York City in a burst of swirling colors, bold new styles and weighty prognostications about what’s “in” and what’s “out.” These eight days in February are crucial. Retail buyers will make decisions that determine what men and women wear – and not just in the precincts of high society, but on Main Street, U.S.A.

Admit it — wouldn’t it be great to have an inkling ahead of time what the hot styles will be?

You could, of course, phone your favorite designer and ask him or her to give you a sneak peak. But if you are not on friendly terms with any designers, you could find your answer online. It’s possible – if you know where to look.

The explosion of social media in recent years, coupled with the rise of advanced analytics technology, has made it possible to forecast any number of trends. This isn’t just for fun – companies are starting to use the burgeoning field of social media analytics to make important business decisions.

Let’s say the head buyer at a major retailer wants a better idea of where fashions are heading. First, he could use sophisticated software to sift through massive amounts of online data to look at the universe of people who discuss fashion online. Starting with literally thousands of people, the powerful algorithms would narrow the list down to a small number of influential bloggers who are extremely passionate and knowledgeable about fashion.

The software would specifically home in on social media mavens who sit at the center of huge social networks and have many followers. Why is this important? A recent IBM inquiry into footwear styles illustrates this point nicely. Using analytics, we looked at the universe of people who discuss shoes online, ultimately identifying a dozen “fashoenistas:” folks who blog and Tweet, do podcasts, etc., about shoes.

We discovered that these bloggers aren’t traditional experts – they don’t work in the footwear industry. But they are incredibly knowledgeable about shoes — that’s why they’re so popular. They might spend countless hours shoe shopping and invest considerable amounts of money in footwear. They read everything they can find on the topic. They often have friends in the industry. They think about shoes far more than most people.

An analysis of what these fashoenistas wrote online from 2008 to 2011 showed that their discussions of increasing heel height peaked towards the end of 2009, and declined after that.  For example, between 2008 and 2009 they wrote consistently about heels from five to eight inches, but by mid 2011 they were writing about the return of the kitten heel and the perfect flat.

The fashoenistas were on to something. While heels on women’s shoes are still high in 2012 — as a visit to any shoe store will confirm – the trend appears to be changing, with lower heels becoming increasingly popular. The advanced insight provided by the fashoenistas is the kind of specific, actionable data that could be used by shoe manufacturers and retailers looking for insight into the kind of shoes to, respectively, manufacture and sell in the coming season.

Similarly, retail buyers could use social media analytics to forecast the most popular color for women’s fashions in a year’s time. Or skirt length. Or trends in makeup.

Nothing is going to replace Fashion Week – it’s a unique extravaganza, an amazing mix of fashion and commerce. But social media analytics can be indispensable in helping retailers understand trends that are yet to be born. It can help them see Fashion Week with new eyes. In a business where even a single misstep can spell disaster, that’s a pretty big deal.

 





Dr. Trevor Davis is a leading consumer products expert and consultant with IBM Global Business Services.

During a career spanning more than two decades, Dr. Davis has worked with a wide variety of enterprises, including companies in the retail, consumer packaged goods, healthcare, beverage and food sectors. In his work, he often uses sophisticated analytics to derive business insight from social media.

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