Find your style brethren for online-shopping bliss with this Pinterest for fashion

Whether your look is “hipster sprezzatura” or “Harajuku schoolgirl-with-a-twist,” ThreadMatcher is here to help you find what you love and buy it online.

New York City-based startup ThreadMatcher wants to bring you a new shopping experience — a fun way to quickly find clothes and shoes you’ll love. It works a lot like Pinterest, but it’s aimed at helping men and women find people with similar style and linking images to online retailers for instant gratification.

The signup process is quick and painless. You select up to six designers/design brands and up to three style profiles (broad categories such as Vintage, Hipster, Hip Hop, Bohemian, etc.). ThreadMatcher will then automagically follow a few users for you who are similar to you in style and taste. As a result, your feed will instantly be populated with pictures of shoes and outfits you’re likely to love.

From there, you can create your own “closets,” which are like Pinterest boards for your fashion finds. For example, you could make a closet for wedding attire, a closet for Converse you love, or a closet featuring tweed items. ThreadMatcher also creates two starter closets for you: one for items you want, and one for items you already own.

And just like Pinterest, ThreadMatcher has a bookmarklet that lets you “thread” things you find elsewhere on the web. The coolest part of the bookmarklet is that it pulls in the item’s price, brand, and other details, making your closet rich with information as well as style.

“Not only can you store everything you love in one place, but you’ll also keep the excess noise out by seeing only relevant items from users who share your style,” said Kevin St. John, one of ThreadMatcher’s co-founders, in a recent chat with VentureBeat.

“And all products on ThreadMatcher are directly linked to an online retail location, so you are just one click away from bringing an item from your [virtual] closet to your real one.”

Sure, it’s not the most innovative idea on the block, but then again, some of tech’s biggest businesses didn’t start out with radically new premises. Facebook wasn’t the first social network; Google wasn’t the first search engine.

“This could actually be pretty neat if their algorithm is good,” siad Seth Sternberg, a Google+ exec, in his onstage DEMO review of the startup. Noting that he’s not the most fashion-forward guy (his wife dressed him today), he said, “If a site could show me stuff that looks like this clothing, there’s opportunity there.”

“We do not think we can change the way people treat each other or the way people view our world, but we do think we can drastically transform the way both men and women shop for clothing,” said St. John.

“One of the great things about ThreadMatcher is that the whole world wears clothing, so each user has the ability to globally influence style trends. A user in Switzerland could be getting style advice from someone he or she doesn’t know in California.

“In that way, each user is a tastemaker, a stylist, and a trendsetter,” he said.

The startup, founded in January 2012, is just beginning its seed fundraising. The site is still in a closed beta; however, VentureBeat readers can get early access by entering the access code Mercer during signup.

Next steps for product development include product discovery, a kind of search that’s personalized based on a user’s profile data, and price drop alerts, which will let you know if an item in one of your closets has gone on sale.

Here’s an interesting note for you gender studies types: The founders were anticipating a mostly female userbase, but currently there’s a 50/50 split between men and women on the site.

TheadMatcher is one of more than 75 companies chosen by VentureBeat to launch at the DEMO Fall 2012 event taking place this week in Silicon Valley. After we make our selections, the chosen companies pay a fee to present. Our coverage of them remains objective.


VentureBeat is studying mobile marketing automation. Chime in, and we’ll share the data.