You Can Now Search Asos’ 85,000 Products With a Single Photo

Anyone who has ever shopped at the high-street e-tailer Asos has faced the daunting task of sifting through its overwhelming 85,000-plus-item inventory (5,000 are added weekly). Not only is there its in-house label, but the online giant plays host to a number of third-party brands ranging from Calvin Klein to Boohoo. Asos evidently understands how taxing and decision-fatigue-inducing the shopping experience can be, because as of today, it has launched a visual search feature — Style Match — through the Asos mobile app, in which consumers can snap a photo or upload an image (click on the camera icon in the search bar), and it will pull up similar products available at Asos.com.

“Inspiration can strike you anywhere and at any time – whether it’s a photo in a magazine, scrolling through an Instagram feed or even on a local street corner,” Andy Berks, Asos’ digital product director, said in a press release. “Now, with just a couple of taps of their mobile device, Asos customers can capture that fleeting moment and … find the item that’s inspired them — or similar — at just the right time.”

Asos Style Match
Asos Style Match on the retailer’s app.
CREDIT: Courtesy

Style Match first rolled out in the U.K. in August 2017 (nearly 80 percent of the retailer’s U.K. traffic and about 70 percent of its sales there come from a mobile device), but it’s now available to all of its 16 million active customers worldwide on both iOS and Android.

“We know this is where our customers are and it’s how they interact with us every day, so we’re always looking for mobile-native ways to make their experience even better,” Berks said. “Ever since Asos was founded [in 2000], we’ve been driven to delight our customers and improve their lives in little ways by using innovation.”

That innovation has manifested in Facebook chatbots to help with holiday shopping, a same-day delivery service in London, a virtual assistant, Ava, to help in product searches and an at-home try-on program, along with its patented AI-powered recommendation engine that uses a smart algorithm to learn shopper preferences over time.

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