There are lots of serious ways to apply Big Data. To optimize business processes. Find better sales leads. And refine your brand to better connect with target customers. In other words, the kinds of goals that excite business executives.
But recently a group of researchers at Penn State University (PSU) decided to take Big Data to the world of high fashion, to see if they could identify emerging trends in a fickle market of clashing aesthetics — and big egos.
“We were drawn to the question of whether or not we could really trace a hidden network of influence in fashion design,” explains said Heng Xu, associate professor of information sciences and technology at PSU, in a news article.
The answer? Yes, they could.
To create a map of designer influence, Xu and her team started by building a database of keywords and phrases from 6,629 runway reviews from Style.com—formerly an online site of Vogue Magazine, a leading fashion publication. The reviews covered the work of 816 designers spanning 30 seasons from 2000 to 2014.
Then they took all the input and built a system that ranks designers, effectively creating a map of influences and relationships. To test their system, the researchers compared their own results against a list of designers mentioned by leading fashion commentators. The lists matched up remarkably well—especially considering that fashion design and trend-spotting are more art than science.
Xu and her colleagues succeeded in using Big Fashion Data to move from simple information-gathering to generating actionable insights. This lays the platform for the tantalizing prospect of making strong predictions. With informed guesses about what looks will be hot at the beginning of each season, companies across the fashion industry could match fashion-forward customer with trending products at the right price point. We’re talking about serious agility in a market known for constant churn. And that’s a formula any business executive can get excited about.
Image credit: Art Comments