When you land on the homepage of K/Lab, the private-label brand recently launched by the department store Kohl’s, it appears like any other fashion website—but there’s a difference: The featured fashions—which currently include a velvet shift dress (on sale for $38.50) and a sheer long sleeve midi dress printed with stars (on sale for $43.50)—are there because of data. Data told the brand that velvet and stars are what customers want.

K/Lab, which launched last week on kohls.com and in 21 Kohl’s stores nationwide, is the retailer’s answer to capturing millennial women shoppers. It’s also an opportunity for it to explore a new form of fast fashion: All of K/Lab’s designs, fabric patterns and materials are driven by social data. 

“So much data exists,” said Arthur Lewis, evp of product development for Kohl’s New York Design Office. “[The key] is understanding the data, understanding how to utilize it and, most importantly, knowing what it’s useful for,” he said.

To get there, Kohl’s appointed a data scientist, now a crucial member of K/Lab’s three-person team—their job is to scan social platforms, follow bloggers and see what’s popular among their followers, and analyze customer behavior. They then aggregate the information for K/Lab’s style curator, who works with a product planner to finalize what items will be created. Finally, the retailer outsources the actual designing and production of the clothes—in whole, it makes for a 13-week turnaround period. New items—including tops, jackets, dresses, jumpsuits and skirts—are introduced each week, and each is priced between $28 and $78.

“It’s unique that we start with data first. Many [retailers] start with a concept first, then gather data. We allow the data to lead us to the concept,” said Lewis. For its launch collection, the concept included velvet and stars.

Data is the industry’s buzzword of the moment, but some brands are struggling to collect it, understand it, and then connect the dots between data points and marketing strategies, for example. For brands born in the digital age, data is a part of their DNA—but for older, more established brands, internal silos, set organizational structures and a lack of data knowledge among staff are often challenges. 

“The fact that it’s data-sourced means that it’s what shoppers are looking at, obsessing over, sharing and coveting right at this moment,” said Erwin Penland’s chief planning officer Jessica Navas, who added that K/Lab is effectively a Petri dish for the brand. “They can test designs in market and identify winners in real time, which can then be incorporated into their other, more established line.”

Going after a millennial consumer is a reflection of a wider trend of department stores going after younger consumers to get them in store and spending. Neiman Marcus recently partnered with rental company Rent the Runway by making way for its store-in-store—its hope is that consumers will stick around and purchase something from the main floor after renting. In addition, Bergdorf Goodman partnered with streetwear label Kith in an effort to target a demographic that doesn’t typically step foot in a traditional department store.

Using data gathered from social media platforms to create relatively cheap fast-fashion items puts Kohl’s in a good spot to compete with other department stores and online platforms—as well as the likes of H&M and Forever 21, which are all vying for millennials’ dollars, said Marshal Cohen, the chief industry analyst of retail at research firm NPD.

The lower price point and styles are key for the consumers it’s targeting. “They’re looking to wear it and get rid of it when the trend is done. They’re not looking for an investment, they’re looking to build a wardrobe,” Cohen said about fast-fashion consumers.

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