Közzétéve: 2016. jan. 20. szerda

Weave’s professional networking app now uses AI for matchmaking


Finding a way to meet someone in a professional setting can be a difficult task — you can go to a party or conference and try to connect with someone, but there’s no guarantee that it’s who you wanted to meet. For CEO Brian Ma and his team, this was something they sought to fix with their service Weave. Today the company has pivoted from the “Tinder for LinkedIn” model to one that uses artificial intelligence to provide curated introductions each week.

“Traditional networking takes work,” said Ma. “Most people don’t do it simply because they don’t have time to hunt for the perfect connection or opportunity. Weave brings people to you. We make networking so easy, there’s no excuse not to do it.”


“We realized we needed to simplify the entire networking experience (including the logistics) for people to actually get out of their building to meet someone new,” he continued. “By removing both swiping and chatting, we’ve [increased the retention rates ten times] of the previous Weave app. The new ‘AI-based Matchmaking’ experience requires no swiping, no small talk, and no scheduling ping-pong. We do everything for you.”

With the new Weave, users will be matched up based on their preferences: Are you looking to meet founders, investors, designers, developers, product managers, sales, marketing, or just people in general? From there, using your LinkedIn profile and other data you’ve provided, each Monday the system will provide you with names of individuals it thinks you should be paired up with. You then let it know whether you want to connect with them or not. If yes, it’ll spend the week coordinating schedules to find a time to meet on Fridays. You’ll meet with your connection and then report back to Weave about whether it was a success or not.

The company uses a variety of signals to determine who you’re matched with, based on your profile, preferences, how you’ve rated your previous matches, and feedback. “We use an ensemble of methods, but the core of it is a collaborative filtering algorithm that looks at your match’s similarity with people you’ve previously rated along with a weighted score based on how well your match’s profile matches your stated preference.”

weave-user-landingPivoting to something that’s more reliant on artificial intelligence will give Weave a leg up against others in the space like Treatings and CoffeeMe. There are plenty of apps that help you network, but finding the right person to meet can be a bit more difficult. While you’re swiping on someone’s LinkedIn profile, it’s up to you to determine whether it’ll be a good fit. However, with the use of AI, Weave will be able to utilize other data you’re not privy to in order to better assess potential pairings.

Currently the service is invite-only, so the quality of pairings should be pretty good. It’s also geared towards those in the tech space, and Weave’s demographics are largely skewed towards that. The company said that 80 percent of its users work in tech, but there are others in finance, health care, education, film and video production. What’s more, 70 percent of all users have senior-level positions. “Members primarily use Weave to share knowledge, exchange information, and learn from each other about cutting edge products to use in their respective jobs,” the firm explained.

Weave doesn’t require installation of a mobile app to use it, although one is in its future. “We opted to start with just web and email because it allowed us to iterate, test, and learn ten times faster,” Ma said. “[There’s] no need to wait around for the app approval process. We’ve tested more than 50 experiments in the past six months versus just 1 to 2 experiments per month when we were building our previous mobile app.”

Ma said that Weave’s first attempt made over 250,000 matches from 12 million swipes. Approximately 2,000 matches are still being made weekly in cities like San Francisco, New York, Seattle, and London, as well as in Japan. It has raised more than $ 2 million in funding from Y Combinator, Index Ventures, Vulcan Capital, Eastlink Ventures, and others.


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