The latest dream for merchants wanting to cozy up to shoppers is to truly recognize them as individuals and migrate from a one-size-fits-all mass approach to laser targeting.
It’s a hard shift for established players, but younger, nimble companies are taking big steps in that direction.
Mobile-first merchant Spring today introduced an app on Apple’s app store that delivers a highly tailored experience to shoppers, which will serve up looks appropriate to the individual user’s style, size and price point.
Spring said, “The shopping destination’s advanced proprietary machine learning technology delivers a convenient and curated experience that constantly learns and adapts to browsing and purchase behaviors.”
On the app, users can shop more than 1,500 brands, find new labels by picking out preferred looks and receiving recommendations, manage “dynamic personalization preferences” and give the company feedback on the process.
The company said, “A layer of personalized editorial content based on these explicit and implicit signals will prompt consumer inspiration and discovery.”
Spring has been building bench strength in its effort to remake retail.
It’s executive team now includes chief operating officer Gillian Gorman Round, formerly of Round House, Condé Nast and Lancôme; chief marketing officer Robert Willey, formerly of TaskRabbit, and chief product officer Gannon Hall, who came from Google. The company’s president is Marshall Porter and Alan Tisch leads the firm as chief executive officer.
Spring launched in 2014 with the backing of some of fashion’s most prominent names, including Bernard Arnault, Lew Frankfort and Silas Chou.
The company was early on the mobile trend and committed from the start to serving shoppers on the go so it makes sense that it is making a move now to personalization.
Some of the buzziest companies, such as Silicon Valley’s box concept Stitch Fix, are working to treat shoppers as individuals. Stitch Fix sends a curated selection of goods to shoppers, who can try on looks at home and keep what they like. The service has gained steam in part because it is reflective of what its users want and, with the help of artificial intelligence, is always learning more to better match style and shopper.
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