Spotify – The game changer
Spotify is a Swedish music streaming company that launched 8 years ago and has since then exponentially grown; in March 2011 there were 1 million users but by August of the following year, the company had 15 million users. The service now has 100 million active monthly users, 40 million of which are paying subscribers. Such results would have been impossible without data analytics.
Spotify’s database comprises 20 million songs and around 2 billion playlists have been created. Users create 600 Gigabyte of data per day and consequently, 28 Petabytes of storage across 5000 production servers, dispersed in 4 data centres across the world. Contrary to Walmart (on which we wrote a piece, accessible here), Spotify decided in 2016 to move its infrastructure from its servers to Google Cloud’s platform.
The company has been data driven from day one in order to provide the most personified service possible. Music is suggested based on what the user has been listening to, but also to what other users who have the same tastes have been listening to. Complex algorithms come into play for Spotify to deliver a “Discover Weekly” service; a list of songs 30 songs, tailored for each user. To come up with this very personal playlist, Spotify looks at what you are listening and what others with similar taste are listening to. A profile of your listening habits is created, and correlated with that of others, to finally provide you with songs you have not listened to but may like. In terms of data analytics, the situation is a bit more complicated. The playlist is improved as you listen to more music, because Spotify’s computers use “deep learning” to refine its suggestions.
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