Would you trust your Spotify playlist to pick out your clothes?


Eison Triple Thread (ETT), a fashion startup based in San Francisco, has created an app that picks clothing for users based on their Spotify listening habits. 

ETT's Fits app, underpinned by artificial intelligence, is able to channel users' Spotify history to pick clothing from its collection. It is more than just recommending clothes because users listen to certain artists, they also take a short quiz to provide information about their profession and skin tone, which is used to inform suggestions on styles and clothing colours.

The app then proceeds to sift through the users' Spotify data, matching music genres and favourite artists with styles. After this, the user goes on to signify which outfits they like or dislike using happy and sad emojis. Finally, the user is presented with outfits that ETT believes will reflect their personality and personal style.

Jason Eison, Founder of ETT, believes Spotify data is more useful for personalising recommendations than other options found on shopping websites - such as using previous purchases to cross-sell or up-sell additional products.

Speaking to Racked, Jason Eison said “It’s a unique take on the recommendation engine that everybody else is using because you can infer a lot from people’s music choices. We start with Spotify information to understand the emotions behind your style choice, and we’ll eventually get the looks that fit you best.”




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