How AI start-up Choosy speeds up fast fashion while cutting waste out of the equation – but will it avoid ‘China copy’ tag?
Choosy brings big data into fashion, using AI to spot trends on social media, with customers delivered items based on the results in under two weeks. As CEO Jessie Zeng explains, since everything is made-to-order, no clothes are wasted
There is an episode of Doraemon where the robotic cat uses a wand to get products shown on the TV. The latest toy, that new dress – anything a person wanted could be obtained by pointing the wand at the object displayed on the screen.
New York-based retailer Choosy is like Doraemon’s gadget for womenswear.
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Imagine scrolling through Instagram and seeing an outfit that you like. Up until now, you tap the photo and see if the brands are tagged. You then hop over to the brand’s online store and buy the item – or in the case of shopping tags, buy directly through Instagram.
Jessie Zeng, the 26-year-old CEO of Choosy, wants you to stop doing that. Born in China, Zeng moved to the US for high school, later studying at the Massachusetts Institute of Technology. She then worked at Citigroup before starting her self-described “on-demand social shopping platform” with former Citi bankers Sharon Qian and Mo Zhou. In May, the company announced that it had raised US$5.4 million in funding from investors.
With Choosy shoppers tag Instagram photos of clothes they like – worn by anyone from celebrities to their friends – with #GetChoosy and hope the item will start trending. Then, using a combination of in-house “style scouts” and artificial intelligence (AI) – which scans for the #GetChoosy tags as well as other Instagram items that are generating interest – Choosy identifies the top-trending items, designs its own items based on the styles, and drops five new products twice a week on its site for customers to buy.
