When SoundCloud Go launched earlier this year, the streaming service said its 125m tracks were a big competitive advantage.
Yet they also presented a big challenge in how listeners would find their way to the needles in SoundCloud’s digital haystack, with the company lacking the kind of playlist-curating editorial team that has become core to rivals like Spotify and Apple Music.
Yesterday, SoundCloud revealed part of its answer to that challenge. No, not an editorial team. The service is launching a feature called Suggested Tracks, which will live within a new ‘Discover’ tab on SoundCloud’s website homescreen, while it’ll be accessed by tapping in the search box in its mobile apps.
“Suggested Tracks makes use of our state-of-the-art machine learning algorithm to deliver fresh new music and audio suggestions based on your likes and plays on SoundCloud,” is how the company described it.
It’s a step in the right direction, but there’s more potential. Until now, discovery for SoundCloud has generally focused around two areas. First, the openness of its platform: the fact that people can encounter tracks embedded on music blogs or (more recently) playing within tweets.
Second, there’s the ‘stream’ on SoundCloud itself: a feed of new tracks that have been posted and reposted by the artists and fellow users that you follow. Which relies, of course, on knowing who to follow in the first place.
Unlocking the potential of SoundCloud’s community of early adopters will be as much about using that state-of-the-art machine learning algorithm to connect listeners with one another, and (in the absence of a big editorial team) with the best user-created playlists on the service.
SoundCloud’s co-founders both agreed this was a possibility when Music Ally interviewed them earlier in 2016, so while Suggested Tracks is a welcome step for SoundCloud, we’re sure there’s more to come as the company gets its teeth into the discovery challenges of its mammoth catalogue.