The Amazing Ways Spotify Uses Big Data, AI And Machine Learning To Drive Business Success

The Amazing Ways Spotify Uses Big Data, AI And Machine Learning To Drive Business Success

Spotify, the largest on-demand music service in the world, has a history of pushing technological boundaries and using big data, artificial intelligence and machine learning to drive success. The digital music company with more than 100 million users has been busy this year enhancing its service and tech capabilities through several acquisitions. Industry watch dogs predict the company will launch an IPO in 2018.

Data: Powerful By-product of Streaming Music

When you have tens of millions of people listening to music every minute of the day, you have access to an extraordinary amount of intel that includes what songs get the most play time, to where listeners are tuning in from and even what device they are using to access the service. There’s no doubt Spotify is a data-driven company and it uses the data in every part of the organisation to drive decisions. As the service continues to acquire data points, it’s using that information to train the algorithms and machines to listen to music and extrapolate insights that impact its business and the experience of listeners.

One example is the Discover Weekly feature on Spotify that reached 40 million people in its first year. Every user gets a personalised playlist every week from Spotify of music that they have not heard before on the service, but that will be something the listener is expected to enjoy—a modern-day version of a best friend creating a personalised mix tape.

Spotify for Artists

In an effort to make its mountains of data available to musicians and their managers, Spotify just launched the Spotify for Artists app that provides mobile access to analytics—everything from which playlists are generating new fans to how many streams they are getting overall. Think Google Analytics for musicians. It was originally launched in a web version earlier this year, but the mobile app allows musicians to access the info from the tour bus and the geographic streaming data can be instrumental to musicians and their teams to plan tours more effectively. Artists also have more control over their presence on Spotify including selecting the “artist’s pick,” and they can update their bios and post playlists.

This is just the latest initiative from Spotify to make a concerted effort to empower artists and make them less sceptical of the company. Fans First is another Spotify programme that uses data to find an artist’s most passionate fans and target them with special offers.

Spotify Acquires Technology Firms to Enhance Service

With the acquisition of Niland, the fourth acquisition for 2017, Spotify will use the API-based product and machine learning to provide its users with better search and recommendations to help them discover music they will like.

Earlier this year, Spotify acquired the blockchain startup Mediachain Labs to help develop solutions via a decentralised database to better connect artists and licensing agreements with the tracks on Spotify’s service. MightyTV, a content recommendation service, and audio detection startup Sonalytic were also acquired this year.

What’s Next for Spotify?

When news broke that Francois Pachet, a French scientist and expert on music composed by AI, joined the Spotify team to “focus on making tools to help artists in their creative process,” not everyone believed that’s ALL that he’d do. You can just imagine how a leader in AI (Artificial Intelligence) might use his expertise to turn the tables at Spotify to make AI-composed music that would push out artists and their labels. So far, Spotify denies that this will be the case even though this isn’t the first AI feature they launched—AI Duet released earlier this year where listeners could create a duet with a computer.

We can also expect the company to continue to humanise data in creative ways like it did when it used its vast amounts of data to launch a global ad campaign that highlighted some of the more bizarre user habits of 2016. Headlines included “Dear person who played ‘Sorry’ 42 times on Valentine’s Day, what did you do?” and “Dear 3,749 people who streamed ‘It's the End of the World as We Know It’ the day of the Brexit vote, hang in there.”

As Spotify learned in 2015, its community will respond if it feels like it’s taking too many liberties with data. After introducing large-scale changes to its privacy policy, users let the company know they were angry by cancelling subscriptions and taking to social media to express their dismay. This prompted Spotify CEO Daniel Ek to apologise for unclear communication and made it clear any access to personal data would only occur with the permission of the individual.

We might not know today where Spotify will innovate next, but we will be watching. As innovators they will encounter learning experiences and even failures as they use big data, AI and machine learning to drive success. Those are experiences we can all learn from.



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Written by

Bernard Marr

Bernard Marr is a bestselling author, keynote speaker, and advisor to companies and governments. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topics of intelligent business performance for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation have millions of readers.

 

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