New startup Neatsy is using AI machine learning to help you find a sneaker that fits your foot perfectly. Its app takes advantage of the iPhone’s depth-sensing selfie camera by using it to scan your foot to capture a 3D model of it. Then, its algorithm will offer up sneaker recommendations it predicts will be a perfect fit.
Neatsy’s app fills a much-needed void that will make customers and shoe companies happier. Customers will be more likely to find a sneaker that fits correctly, thus eliminating the need to return it for a different size. And companies won’t have to field as many returns or continue eating the costs that accompany free returns.
Since the app relies on the iPhone’s front-facing FaceID camera, it’s only available to iOS users as a soft launch at the moment (though it’s slated to officially launch in December). The app is also currently limited to sneakers, rather than all shoe types, and can only provide a good fit across few brands like Jordan Air, Nike, Adidas, and Puma. However, as the app grows its database and hones its algorithms, it’ll likely expand to more shoe types and brands, as there is certainly a need for it.
The app proved successful in commercial pilot tests earlier this year, on a 140-person focus group. It demonstrated a 2.7x reduction in size-based sneaker return rates along with a 1.9x reduction in overall sneaker returns.
Footwear giant Zappos claims that customers purchasing its more expensive footwear items typically return about 50% of their purchases. Satista noted that U.S. return delivery cost businesses $350 billion in 2017, and that the figure is likely to rise to $550 billion by the end of 2020. Needless to say, an app that can help curb returns is welcome technology.
Founded in March 2019, Neatsy has raised roughly $400K in pre-seed funding from angel investors for its app, which is now available in the United States, Canada, UK, Spain, France, Netherlands, Italy, and Russia. It has also secured a U.S. patent for its 3D scanning technology and sneaker recommendations.
This post was written by Suzanne Humphries and was first posted to www.reviewgeek.com
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