January 29, 2013, 11:23 AM —
Ever wonder how online music services like Spotify come up with their recommendations for what songs or artists you’ll like or generate playlists based on a single tune? Turns out it’s quite a complex nut to crack (shocking, right?). One company that’s powering the recommendations behind an increasing number of popular music services has provided a glimpse into the black box that is music recommendation.
The Echo Nest is a company started in 2005 and headquartered in Massachusetts that currently supplies the recommendation engine for a number of popular music services such as Spotify, Rdio and iHeartRadio. They also provide an API that developers can use to tap into their detailed collection of music and artist data that they collect and generate, that’s used by, among others, the BBC and MTV. Recently, one of the Echo Nest’s founders, Brian Whitman, wrote in detail about music recommendation and the Echo Nest’s unique approach to the problem. It’s a fascinating read.
Whitman writes that the Echo Nest's approach to music recommendation is based on the principle of “care and scale.” Scale means they want to be able to know about as many artists and songs as possible in order to be able to recommend new ones to people. Care means the recommendation is useful for the listener and musician, and not just a third party vendor (e.g., Amazon).
“Care is a layer of quality assurance, editing and sanity checks, real-world usage and analysis and, well, care, on top of any systematic results,” Whitman writes. “Without both care and scale you’ve got a system that a listener can’t trust and that musician can’t use to find new fans.”