clock menu more-arrow no yes mobile

Filed under:

This Menswear Startup Will Recommend Clothes Based on Your Spotify Data

Eison Triple Thread thinks men will be drawn to their favorite artists’ styles.

Eison Triple Threads

Racked is no longer publishing. Thank you to everyone who read our work over the years. The archives will remain available here; for new stories, head over to Vox.com, where our staff is covering consumer culture for The Goods by Vox. You can also see what we’re up to by signing up here.

It’s no surprise that shoppers’ taste in music is an excellent way to understand them — there’s an entire industry dedicated to figuring out what should play inside stores to get people to spend money.

Now, one menswear CEO in San Francisco wants to take the psychology of music a step further and suggest clothing for men based on their music preference.

Julian Eison is the founder of Eison Triple Thread, which sells custom luxury menswear. The company has been around since 2016, has a store in San Francisco’s Union Square, and counts NBA players Steph Curry and Damian Jones as fans. This week, it’s debuting an app that will recommend clothes from its collection based on users’ Spotify data.

“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,” Eison tells Racked. “We start with Spotify information to understand the emotions behind your style choice, and we’ll eventually get the looks that fit you best.”

Once users download the app, called FITS, they log in to their Spotify account, which gives ETT their listening data, since Spotify’s API is open for developers. (ETT is not working directly with Spotify, although Eison says the two companies have had “conversations.”) They are then prompted to take a lifestyle quiz, which will provide the company with information like what type of field they work in as well as their skin color. Eison says these types of information are important because “we can’t recommend you a suit if you work in a creative field, and we know different colors look better on different skin tones.”

Eison Triple Thread

From there, ETT’s algorithm sifts through a user’s Spotify data and pairs music genres and favorite artists with styles. The user then looks through these suggested outfits, denoting likes and dislikes with happy and sad emojis. Finally, he’s served up ETT pieces that Eison says will properly reflect his personality as well as personal style. And because all the company’s menswear is made to measure, users can further customize each product, like choosing color pairings or materials.

When ETT hit the market two years ago, its initial boast was that it used innovative 3D body imaging technology from a company called Body Labs to create made-to-measure clothes. Eison was optimistic — until Body Labs was acquired by Amazon. He realized the company was better off looking for a different way to discover style preferences than taking on the e-commerce giant.

The root of Eison’s idea for using listener data to determine style is the assumption that music lovers want to dress like their favorite musicians. Eison points to the industry of festival music fashion, and how brands cashed in by reflecting the aesthetic of a music event like Coachella and the big acts that perform there. While that business model mimics the shopping behavior of the masses, Eison believes it can get even more granular.

“A guy who was born between 1984 and 1988, likes hip-hop, and works in tech in San Francisco will probably like clothing that’s on trend, and so we’ll feed him looks based on that demographic and see what he responds to,” he explains. “If someone else likes upbeat music, was born in the ’80s, and listens to music from that time, we can gauge that his style is probably similar to Joey [from Friends]. People who listen to ’60s music like the Beatles will have suggestions like high-rise jeans and corduroy.”

Eison says people who listen to Drake will likely be served photos of streetwear, like fitted tees and velour sweatpants, while Lionel Richie listeners could be fed images of red ribbed sweaters and blue jeans.

He sees this type of service as a way to help men who struggle with finding their personal style, without having to go down the sometimes-impersonal route of subscription boxes. Of course, Eison adds, the system isn’t as simple as “Drake wears this, so buy that.” “While it’s one thing to extrapolate the obvious, we are looking at the deeper analysis such as cadence, tempo, mood, emotion, and how this pairs with lifestyle, occupation, and daily use,” he says.

Eison says this type of thinking comes from his fashion roots: His ninth-grade trigonometry teacher taught him how to sew, and he spent much of his high school days buying rolls of fake Gucci material from eBay and sewing it onto jeans, emulating styles he saw in Jay-Z music videos from the early aughts.

On some level, this makes sense. There’s an ongoing list of ways Kanye West’s sartorial decisions have affected his fan base (and his wife’s), while hip-hop artists in general have had colossal effects on fashion for decades. Many K-pop enthusiasts, too, emulate the sartorial choices of their favorite groups, as do country music fans.

But of course, the logic doesn’t hold up all the time. I listen to Haim, and while I consider all three sisters to be style icons (have you seen their outfits in Want You Back?!), I also have plenty of Grateful Dead and Phish playlists cued up on Spotify; I don’t necessarily subscribe to the eclectic style of either fan group. This approach relies on the assumption that there’s a correlation between someone’s music preferences and their style, but for many people, both areas of taste are constantly evolving; for others, one is stagnant while the other matures. Regardless, they just don’t always match up.

Eison maintains that the FITS app is able to add some nuance to the process, however, because the algorithm makes more fine-tuned recommendations the more it’s interacted with. “This is a more advanced way to recommend things to shoppers than by just saying, ‘Hey, someone bought this five minutes ago, you should too!’” he says.

ETT’s clothes aren’t exactly cheap — suits start at $500 and cap out at $1,000, and shirts are $149. But Eison says that his menswear, which is custom-made from measurements customers supply, are manufactured in the same factories in China as luxury brands including Tom Ford, Zenya, Balenciaga, and Gucci.

After he left his previous job in private equity in 2015, Eison says, he spent a year traveling around China and literally knocked on doors.

“I don’t think people were used to seeing a black guy in Shanghai looking to do business, and especially one that knew all about fashion patterns and supply chain, and so they immediately were like, ‘Who are you and what’s up?’” he says with a laugh. “But I am just a damn hustler and I said, ‘Hey, I got a dollar, do you want to do business? Because I have an idea to compete with the luxury part of the market with mid-tier prices.’”

Eison plans to raise funding for ETT in the fall, and wants to expand into casual clothing like streetwear. He admits the brand doesn’t exactly have name recognition or a big social media presence just yet, but Eison believes mining music preference data for fashion can eventually lead to future opportunities, like working with artists or music venues to sell tour merch.

It might be a long shot, but as he points out, “the music crowd is a segment of people who evangelize.” And so long as the Carters keep dropping music videos with fashion that make fans go wild, it could very well mean people will line up.