How AI help Spotify for Picking Next Tune?

AI, ML, NLP have been playing a major in personalizing the content being delivered to the audience, and Spotify is one the leading innovators in deploying the same. Today, Spotify is the world’s most popular audio streaming subscription services with 320 million users – that included 144m subscribers across 92 markets. Since, the time of the launch, with AI in Spotify has been able to use their vast amount of data, analytical capabilities and AI tools to create a competitive advantage and a superior user experience. Discover, manage and share over 60 million tracks – that includes more than 1.9 million podcast titles, for free. Spotify has transformed music listening forever since the time of its launch in 2008. 

Why Data is the magic Ingredient for Audio/Video Streaming Success - Spotify uses a combination of different data aggregation and sorting methods to create their unique and powerful recommendation model – which is powered by Machine Learning. With millions and millions of users listening to music every minute of the day – brands like Spotify accumulate a mountain of implicit customer data comprised of song preferences, keyword preferences, playlist data, geographic location of listeners, most used devices and more. 

Data drives decisions across each and every department at Spotify. This data is used to train Spotify algorithms which hypothesize relevant insights both from content on the platform and from online conversations about music and artists – as well as from customer data and use this to enhance the user experience.

For instance, Discover Weekly – which has reached 40 million people in the first year it was introduced. Machine learning enables the recommendations to improve over a period of time. On every Monday, each and every users are presented with a customized list of thirty songs. Not only it keeps users returning but also enables greater exposure for artists – who users might not even search for organically.

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