Fashion Apps Strut the Catwalk in Bid for Venture Capital

Fashion-centric startups show games, image recognition and other technologies at Tel Aviv event hosted by Google Israel.

The rapidly expanding field of fashion technology intersected with venture capital on Wednesday, as five Israeli startups showed their efforts to help clothing producers and retailers sell more and help consumers look better in what they buy.

In an event sponsored by the Israel Fash & Tech MeetUp group and held at Google Israel’s offices, the companies’ representatives did flash five-minute presentations followed by Q&A sessions conducted by a panel of technology investors and professionals.

Two of the five – Fashioholic and Snapget – were chosen to receive a package of consulting and marketing services as well as a free-of-charge place at Axis Tel Aviv, a March 18-19 event designed to connect startups and investors. Fashioholic was chosen by the panel and Snapget by the attending audience.

The investors attending and judging the firms made clear that this was a field in which they were ready to put money down.

“Looking at the retail industry and the fashion industry in the U.K., they are desperate for new solutions and new technology, whether it’s online, whether it’s in-store, they’re really interested in the things coming out of Israel. So I’m looking forward to seeing the solutions we’ll have tonight,” said Naomi Krieger Carmy, director at UK Israel Tech Hub, a venture based at the British Embassy in Tel Aviv and designed to connect British and Israeli companies.

Fashioholic develops what it calls serious mobile games designed to introduce consumers to offerings from particular brands or retailers. Since consumers spend a great deal of time playing games on mobile devices, the company seeks to enable merchants to engage them while they play.

One game, for example, calls on consumers to guess which of two fashion items is the more or less expensive. “What we’ve seen in this game is that the most loved items … are the ones that [consumers] guess incorrectly because they’re pleasantly surprised to find affordable merchandise that looks very expensive,” said Amit Manna, the startup’s co-founder.

Through the game, merchants can, for example, determine how consumers perceive the relative value of items and can more accurately price their wares and target promotions, he said. The site is www.fashioholic.com.

As for Snapget, have you ever seen someone wearing a clothing item that you just had to have? If you see, say, a pair of particularly nice shoes, take a shot of them with your smartphone and Snapget’s app will immediately tell you where to buy that exact pair or a similar one, co-founder Danny Shir told the audience.

Shir said that if you see a pair of shoes on a social media site or in a store and they’re priced way above budget, Snapget’s app can help you find a similar pair that’s in your price range.

Through proprietary image-recognition technology, he says, “We turn every single image into a shopping opportunity.” he says. The site is www.snapgetapp.com.

The other three companies were:

* Rightune customizes music playlists for websites to create what it calls emotional connections to customers, keeping them shopping longer and ultimately increasing revenues. Rightune tracks customers’ reactions to the music, regularly revising the playlists. It learns, for example, which music works best at which times of day, and provides real-time reports to the site owners.

* Stylit employs a team of stylists to provide customers with free personalized styling ideas. Users fill out questionnaires, providing data like how much they want to spend, their taste in clothes and their body type. Stylit sends ideas to the consumers, who can buy them with a click. Users also rate the ideas, which enables the company’s system to better learn what styles each customer prefers.

* Zeekit’s browser plug-in enables users to upload pictures of themselves, click on clothing and immediately see themselves wearing the items. They can then quickly change the items to different colors and patterns to see what works best. The system recommends the proper sizes and shows the users where the items fit and don’t.

Anna Morein