Like.fm

YC-Backed Like.fm Is A Social Network For Tracking Songs

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Recently funded by Y Combinator, Like.fm is a way to keep track of and share what music you’re playing. Right now the service uses a Chrome, Firefox and Safari extension to automatically track what you’re listening to on YouTube, Pandora, Rdio, Meemix, Grooveshark and Earbits and a desktop client to track what you’re listening to on Winamp, iTunes, MediaMonkey or Windows Media Player.

Founder Chris Chen says that its emphasis on song tracking is what separates the Like.fm from streaming services like Last.fm and music buying networks like Apple’s Ping (which he describes as “a step above adding share buttons to the iTunes store.”) says Chen “Like.fm isn’t meant to be a destination music site, it’s meant to be a place to find songs that you like. It’s not meant to be a Pandora but a compliment to it, it’s a place for sound discovery, where you go and listen to music.”

At the moment very barebones and work-in-progress (there’s a lot of “Coming Soon” on the site) Like.fm uses Facebook Connect to automatically follow your Facebook friends on the service.  Through the Top Played chart on your Dashboard the service allows you to track the songs most played by people you followed and lets you play songs by linking to the corresponding video on YouTube (if it exists).

On a Like.fm profile you can view a Summary of the top songs a user has listened to, their entire song History or the songs they’ve set up to listen to in the Queue. Users can also easily download all their play history.

Aside from letting you comment on songs and manually share/recommend links, the service also lets you set up Auto-Share to Facebook, Twitter and Last.fm for songs that you rate at four or five stars on iTunes or Windows Media Player (Chen says that in-app rating should be coming in the next couple of weeks).

Chen hopes to eventually add more robust recommendation features like Songs You May Like, based on stuff your friends have listened to that you haven’t heard. He also hopes to build a mobile version soon and add better data visualizations like custom charts of your chronological music listening history, “I’d like to create charts of the YC Class, and what days they listen to music the most. You can guess what time people sleep by the music they play, with the YC class I’m guessing it’s probably around 5am.” That sounds about right.