![]() Forerunner Ventures, Innovation Global Factor and XFactor Ventures are among the other investors in this seed round.Ī former investment banker at Citigroup, Zeng recruited her former coworkers Sharon Qian and Mo Zhou to be Choosy’s chief technology officer and chief strategy officer, respectively, and help build the company. ![]() The site goes live on July 24.Ĭhoosy announced Tuesday morning a $5.4 million round of funding led by New Enterprise Associates (NEA). Most of the items are not unique in the marketplace, and they are not copying anything from smaller, independent designers. All items are priced under $100 (free shipping included) and available in sizes 0-20. Users then pre-order any of the items and Choosy will design and manufacture the items in-house within 48 hours, and get them delivered in as little as two weeks. Here’s how it works - each week, a team of “style scouts” will identify the top 10 fashion trends (with the help of social media). Think of it as ultra-fast fashion on-demand. The company can, for example, use its technology to analyze all the leopard-print, V-neck shirts being posted to Instagram and figure out what the optimal design will be for the Choosy customer.Jessie Zeng, 25, is hoping to make the latest female fashion trends accessible and affordable with her new startup Choosy. It scans some 95 million Instagram posts a day to pinpoint the most popular styles. This method gives the company’s merchandising and design teams a lot of data to work with. We’ve trained the data to be able to say that it’s a shirt, it’s leopard print and it has a deep v-neck, and we can share that and all the other trending things picked up by our algorithm that are in the same vein,” she said. “AI technology on computer vision currently is only able to tell things like whether an item is a dress or a shirt. Computer vision technology, which works with AI, is the science behind getting computers to see, identify and process images. ![]() “We’ve built out this computer vision technology to start grouping these outfits together,” said Zeng. Now, as the company has grown and learned more about what customers like and what styles are trending, Choosy is working to improve its technology to make it more efficient. Using that data, along with help from some “style scouts,” or merchandising and design experts on the team, Choosy is designs its next drop. Now, the company uses polls on its Instagram stories. ![]() Previously, customers were encouraged to comment with the hashtag #GetChoosy under Instagram posts featuring pictures of outfits that they love worn by celebrities or influencers. It built a proprietary AI tool to scan Instagram to find what outfits customers like and would want to buy, but for a fraction of the cost.īut there is a human component to it. The company is both China- and New York-based, but manufacturing takes place overseas.Īrtificial intelligence is a big part of how the company figures out what styles are trending, and therefore, what dresses or tops to design and sell. The company’s restock timeline is currently about two weeks, followed by another week to clear customs and reach customers. In those instances, Choosy immediately puts in an order to its manufacturer for more units. The company promotes new products on Instagram to its 121,000 followers and through unpaid partnerships with influencers. For young and new brands, transparency in the delivery process can truly make or break that brand-customer relationship,” said Arpan Podduturi, director of product for Shopify.Ĭhoosy products will often start to sell out on the day they launch. “Delivery promise is extremely important for businesses of any size, because this is the first opportunity an online brand has to build trust and loyalty with their customers. “Then, as it starts to sell out, we will then restock thousands, and then sometimes tens of thousands of units, depending on ,” said Jessie Zeng, co-founder and CEO at Choosy. Now, for each of its monthly drops, it makes 80 units of each item upfront. When Choosy relaunched in November of last year, building up enough inventory ahead of launching a new product was a big focus, to avoid selling out and keeping customers waiting for deliveries for weeks.
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