By Shazia Rashid
20th April 2017

Since the birth of music streaming services like Spotify the way we listen to music has changed; we can now access millions of songs in one place and easily discover new bands. In 2014 Spotify teamed up with The Echo Nest to drive data intelligence and real time analytics to their users, changing the way music is discovered.

Big data plays a huge part in the songs Spotify recommends to each user; by collecting all the data they have on a user they are able to make these recommendations personalised. The data being collected is not just from a user’s profile and playlists but what music they actually listen to most often. This large database also means that those users who don’t create playlists can still get personalised recommendations based on the activity from others.

Spotify are also using data from their service and users to give up-to-date real time analytics to listeners. When on an artist’s profile the listener can see where they are most popular and where in the world their music is streamed the most. Spotify even used this data to predict the Grammy Award winners in 2013, and in the end they made 4 out 6 correct predictions!

But the data is not just driving what the users see and hear; last month Spotify announced a new tool for artists. ‘Spotify Fan Insights’ collates the data they have on users into a dashboard for the artists to see, allowing them to see data and information on the people who are listening to their music the most.

As more users sign up to Spotify and more songs are added the data being collected is only going to grow, I think it will be interesting to see how else big data can be used to change the way I listen to music.

Big Data & Music

How do you think big data improves the way you listen to music? I’d love to hear your thoughts in the comments below

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This blog was originally published on LinkedIn. To read the original article click here

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