If you follow fashion — and maybe if you don’t — you probably know that Victoria’s Secret annual fashion show delivered its biggest rating ever Tuesday night, and even ranked as the evening’s highest-rated show.
The special, which aired at 10 p.m., was seen by 10.3 million viewers and scored a huge 4.6 rating among adults 18-49 — up 35 from last year. That’s the show’s biggest audience since 2002 and its largest rating during its nine-year history.
With so many people interested in fashion (wishful thinking?), I decided to investigate whether technology can predict next season’s top fashions.
That’s also the question my former colleague, Rob Mitchell, asked recently.
And the answer: yes . . . but maybe with a slight caveat.
Before I delve deeper into predictive analytics and fashion, let me be completely honest—I’m not really that into fashion. I’m happy buying my clothes at a local thrift store that donates part of its profits to help find missing children. My adult son, on the other hand—if it’s not Gucci, Prada, Armani, Versace or Dolce & Gabbana, forget about it.
So I had to chuckle when I saw the title of Mitchell’s blog: Predictive analytics vs Prada. His message, however, is nothing to laugh at.
“[P]redictive analytics can look at all of the characteristics that make up a style—from fit to color—and, based on historical trending on those attributes, predict the success of a new fashion,” Mitchell says. Then add in a dash of social media, which can help by allowing for real-time interactions with so-called fashion experts or predictors—and voila, you’ll have a pretty good idea about the next big thing in fashion.
But that little caveat I mentioned—people.
While analytics can track things like quantities and distribution strategies of previous products in order to determine the hot new style(s) for next year, it can’t really predict why someone will buy something—mainly because there’s really nothing to predict, Leslie Ghize, senior vice president with fashion consultancy The Doneger Group, tells Mitchell.
Well, people have free will and that’s something technology just can’t capture, Ghize says.
Typically, fashion trends are set by a few influential designers like Miuccia Prada. People think: if it’s good enough for Prada then it’s good enough for me. And technology never enters into that equation.
But times—and people—have changed, Mitchell points out.
Now “fashion-conscious consumers take their cues from the Internet and their peers through social networks,” he says. “They have a world view that’s much broader than the marching orders that traditionally have come through fashion runways and retailers.”
That means predictive analytics—especially as it intersects with social media—can certainly influence future fashion trends, Mitchell adds. And maybe companies in the fashion industry that make better use of predictive analytics will buck tradition and accurately forecast what consumers want to buy, not what designers want them to buy.
Gina Ashe (@g_ashe), CEO of social shopping site Krush, says her company can predict future fashion trends. Krush, which lets users view and rate not-yet-released action sports clothing and equipment, is now going to offer reports to businesses that predict what styles will be big sellers this coming spring. Businesses can use the data from Krush to make key decisions such as how much of certain items to manufacture.
Just as Mitchell predicted: Krush is a company that understands the importance of using predictive analytics along with social media in the fashion industry.
But FYI Krush: You’ll be doing those busy execs at your customer companies a huge favor if you present your reports in easy-to-use, simple-to-share dashboards.
Remember, to be useful, the data must not only be accurate, it also has to be clearly represented so users can navigate it, talk about it with colleagues and make informed business decisions—often in a split second.
That’s exactly what a dashboard will do—get the right information to the right people at the right time so they can make the right business decisions. And the right dashboard will do it in an easy-to-use, intuitive and, well . . . engaging fashion.
To learn more join Spotfire’s webcast on Predictive Analytics.
Spotfire Blogging Team