Google Taps Into Your Life to Personalize its Streaming Music
Google Play Music is turning to big data to curate a personalized music playlist to compete with major competitors like Spotify and Pandora.This article originally appeared on IT World
Google is using the power of big data and machine learning to deliver users the songs they want, when they want them.
Google announced this week it is updating its streaming music service, hopefully helping distinguish Google Play Music from its rivals in the streaming music category.
To do that, it's using its wealth of user data -- what music you have listened to before and what music you keep going back to, along with music you check out on YouTube, and which artists and genres you search for.
Google also is using machine learning to make sense of an array of data, like what time of day it is, if the user is at work or relaxing on a Sunday morning or out running with the dog.
All of that information influences what type of music you might want to listen to -- some old school dance music when you're getting ready to go out or some light classical music on a rainy night before bed -- so the streaming service can figure out what to offer up.
The update will begin rolling out this week.
"To provide even richer music recommendations based on Google's understanding of your world, we've plugged into the contextual tools that power Google products," wrote Elias Roman, Google Play Music's lead product manager, in a blog post. "Your workout music is front and center as you walk into the gym, a sunset soundtrack appears just as the sky goes pink, and tunes for focusing turn up at the library."