Spotify is the biggest on-demand music streaming service worldwide with a reported 140 million monthly active users, as of June 2017. But what makes the company truly stand out from a technological standpoint is its innovative use of artificial intelligence (AI), machine learning (ML), and Big Data for business success. The company has recently taken another giant leap forward by upgrading its existing tech and service capabilities through various acquisitions. All this success will pay off handsomely: Spotify is expected to soon hold what many expect will be the biggest IPO of 2018.
Spotify uses data to its advantage
Spotify derives its strength primarily from its ever-increasing user base. When a company has millions of people tuning in at all times, they are bound to enjoy access to an overwhelming amount of data. Most of the intel conveys the kind of device being used to access the music service, the location of the listeners, and the most played songs.
Considering how every aspect of the organization utilizes data to make important decisions, Spotify can easily be classified as a data-driven business. More and more data points are being acquired by the service on a daily basis, and this data is fed to the business machines and algorithms with the intention of deriving insights and playing music that influences the user experience and encourages business growth.
A fantastic example of this would be Spotify’s Discover Weekly service. In its first year alone, this feature amassed 40 million users. And their excitement was valid. After all, it’s not every day that a user receives a customized weekly playlist containing songs they hadn’t listened to before on Spotify. Discover Weekly was positively received by users because it added a new, enjoyable dimension to their listening experience.
Spotify was quick to grasp just how valuable their user data was to musicians (Ice Cube, Eminem, 21 Pilots, all fantastic) as well as their managers. To cash in on that and make the company data accessible to these entities, Spotify created a new app, dubbed “Spotify for Artists.”
This program offered mobile access to business analytics, and it was possible to see all kinds of data, from the most trending playlists to the total number of streams on any given day. So, Spotify for Artists quickly became something akin to Google Analytics, but only for the music industry crowd.
The organization has continued to update this service since its launch earlier in the year. Initially available only in Web format, a mobile app is now available for download. The reason? Musicians can now access all the data from the comfort of their tour bus.
Moreover, the geographical location information plays a major role in the way musicians, their managers, and teams plan their tours. Spotify has also become a platform for musical artists to connect with their listeners by posting their personal playlists and updating their bios. Moreover, the streaming service provides a greater amount of control when it comes to the online presence of the artist, like choosing the “artist’s pick.”
All these efforts on the part of Spotify to empower musicians have made the company an industry darling. In the process, the artists have also become less suspicious of the organization and its motives. Another vital Spotify program is Fans First, which utilizes digital intel to determine the most ardent fans of a particular artist and set them up with remarkable offers.
How Spotify improves its service with the help of technology
Niland, an AI startup, was the fourth acquisition made by Spotify in 2017. The organization plans on using its machine learning and API-based technology to offer better recommendations and search options to their customers. In the end, the company wants to help users discover music that appeals to their tastes. That song sung by Louie in “Remember the Titans” did not appeal to many people, that is for sure! That scene went a little too far! But let’s get back on track.
Mediachain Labs, the blockchain data solution service, was acquired by Spotify earlier in 2017 to better match royalty payments to musicians. The company wants to use Mediachain’s decentralized database to create solutions that can connect licensing agreements and artists with their respective songs on the Spotify database.
It is also interesting that the music streaming company chose to obtain content recommendation provider, MightyTV, as well as Sonalytic, the UK-based audio detection technology creators, in 2017.
What the future holds?
Spotify has proved time and again that it is only beginning to push the boundaries of this music-data admixture. For starters, the company poached one of the world’s leading experts on the application of AI in the pop music industry, Francois Pachet, from Sony in July 2017. Currently holding the title of Director of Spotify Creator Technology Research Lab, he was apparently brought in to develop tools that would help artists with their creative process.
But a lot of people believe that this is only the tip of the iceberg. Nobody ropes in an AI music scientist and doesn’t use him to break new ground, namely make music composed by AI that would do away with the concepts of labels and artists. However, representatives from Spotify have vehemently denied all this speculation.
Would humans go ga-ga over a computer singing sensation? Doubt it! That would be strange.
But even if they do go ahead with this plan, it won’t be the first time the company launched an AI project – earlier in 2017, the company released AI Duet to facilitate musical duets between computers and listeners. The company also resorts to creative techniques for humanizing data, like the global advertising campaign that used the company’s accumulated data to highlight many of the weird user habits in 2016.
While it is not exactly clear how Spotify will continue its innovative streak in the future, one thing’s for sure — it is going to be interesting. And a lot of interesting parties will be watching the company’s every move.
Being pioneers in the fields of technology and music, the business is going to have various learning experiences as well as failures. But that should not deter them from using AI, ML, and Big Data to promote success. Not only will they gain valuable experience from these situations, but the rest of the world will too.