Big data has turned "fashion forecasting" from an art into a science. Is that a good thing?
In recent years, retailers have increasingly embraced big data instead of simply relying on the intuitive sense of fashion designers and buyers. Stores that have leftover inventory or are out of stock on bestselling items now look to real-time data and analytics to ensure that supply and demand are aligned.
Users—including brands like Gap, Target, Gilt Groupe, and several U.K. High Street brands—pay upwards of $2,500 a month to access a suite of dashboards that show what products are currently on the market, how much they’re selling for, and how quickly the items are selling out.
“We crawl the web in the way that Google crawls the web,” says Watts. In addition to looking at retail websites, Editd’s software also monitors social media and fashion blogs to determine what’s trending. It can take into account local and regional dialects—that “jersey” has a different meaning in South Africa—and the data are refreshed every 24 hours.
Retailers have always had business-intelligence tools but most, from streetwear to luxury, don’t provide real-time information on the entire industry.
For an industry that generates $1 trillion annually, intuition still has its place.
This post originally appeared on Quartz, an Atlantic partner site.
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