Big Data & The Music Industry
1000 Songs in your pocket. This sentence should ring a bell for every music- or technology enthusiast. With these words, Steve Jobs introduced the world to the first iPod in 2001.  Some say though, that it wasn’t the iPod but iTunes that has changed the way we consume music. Suddenly it was possible to buy and download any song and conveniently add it to your music library. At least as big was the leap to the next level of evolution in the music industry, the streaming of music. Spotify was founded in 2008, but it was not until 2011 that Spotify surpassed the limit of 1 Million users.  In early 2018, Spotify reported 83 million paying subscribers and more than 180 million users.  Just a week ago on 18th of July 2018 German newspapers reported that for the first time, streaming generates more revenue than CD sales. 
One can say with certainty that Spotify changed the way we listen to music. But in what way? First, we can listen to whatever song we want whenever we want. Second, we no longer listen to specific songs, we listen to playlists. Based on the behavior of 180 Million users, Spotify has access to an enormous amount of data (big data) to tell what kind of people like to listen to what kind of music at what kind of location at what time, … and so on. And we are just getting started. When I bought a washing machine two years ago on Amazon, the next weeks I was confronted with washing machine advertisements all across the internet. Similar to this, in the beginning, whenever one listens to a specific genre, Spotify suggested playlists from that genre. This was often correct, but it does not do justice to the great data available to Spotify. With the acquisition of the AI startup “Niland” in 2017, Spotify will use artificial intelligence to use the huge amount of data to make even better suggestions and personalized playlists for their users. 
In addition to the possibility to personalize the music experience, Big Data opens the possibility to predict the success of songs. Shazam, a company that detects the song played to the app uses their data to predict songs that will become successful. The prediction comes from the combination of the number of recognitions and the ratings of the songs. Predicting the next big hit has already been done in 2015 by the University of Antwerp in Belgium. The researchers tested 3.500 Top 10 songs from the past and analyzed their characteristics to find successful song patterns. They tried to find these patterns in new songs and were able to make a surprisingly accurate prediction if those songs will become Top 10 Hits. 
The music industry is one of many industries that can benefit from big data and data analytics. As Data Science is a relatively young science, we are just getting started to find possibilities to use that data. There are many uncertainties and security concerns for the future but I am confident that, used in the right way, Big Data and Data Science can be a very helpful tool for the future.
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