How Spotify Beat Apple, Amazon, and Google Using Machine Learning - Technology and Operations Management (2024)

In an era in which Apple, Amazon, and Google are dominating the technology world, Spotify has succeeded in besting all of them in the music streaming industry. The question is then, how is Spotify able to fend off its major competitors, who are much more established in the technology industry?

In an era in which Apple, Amazon, and Google are dominating the technology world, Spotify has succeeded in besting all of them in the music streaming industry. Spotify also helped reverse the decade-long secular decline in the global recorded music industry, which declined from $25.2 billion in 1999 to $14.2 billion in 2014[1]. Since 2014, that decline has reversed following the explosive growth of the music streaming industry which grew to $6.6 billion in 2017 to represent 38% of the global recorded music industry[2].

Figure 1 – Global Recorded Music Industry Revenues [Source: IFPI]

The rapid growth in the music streaming industry was driven by Spotify, a global leader with ~42% market share and €4.1 billion revenue in 2017[3]. This was a major feat by Spotify, whose major competitors include technology titans like Apple, Amazon, and Google. Apple Music, Spotify’s nearest competitor, only has approximately half the global subscriber base and market share as those of Spotify[4]. The question is then, how is Spotify able to fend off its major competitors, who are much more established in the technology industry?

One key offering by Spotify is to provide users with machine-generated playlists like Discover Weekly, a personalized playlist with weekly updates. This allows Spotify to differentiate itself, as users who are attracted to these auto-generated playlists choose Spotify over Apple, Amazon, and Google. Machine-generated playlists now represent 31% of all listening activities on Spotify, compared to less than 20% just two years ago, attesting to increasing popularity of such playlists to users[5].

Figure 2 – Spotify’s “Made For You” Playlists and Discover Weekly Playlist [Source: Author]

Spotify primarily uses three machine learning techniques to create tailored playlists[6]:

1. Collaborative Filtering: Using user’s streaming history, Spotify recommends songs that different users with a similar streaming history have listened to
2. Natural Language Processing: Spotify also navigates the Internet and scans for any text data to gather more information about songs
3. Raw Audio Models: Finally, Spotify analyzes the actual audio of songs to identify similar tracks in terms of their sounds. This is especially helpful in analyzing new songs that may not have enough streaming data

Playlists generated by machine learning have become the core of Spotify. Christine Hung, Head of Data Solutions at Spotify, has noted that Spotify has become more than a music streaming service to “a very important platform for [users] to discover something new.[7]”

Arguably, Apple, Amazon, and Google have better machine learning technologies than Spotify, but Spotify’s first-mover advantage and its vast data of streaming history have helped the company remain competitive. To maintain its edge, Spotify should continue to develop its in-house machine learning capabilities and obtain new technologies through acquisitions. “Spotify Machine Learning Day” in July 2018 with experts in machine learning as well as Spotify’s acquisition of a music AI startup Niland in May 2017 are good examples of how Spotify stays ahead of the learning curve. Spotify could even consider partnering with one of the three competitors. The partnership could combine Spotify’s best-in-class machine learning technologies with the competitor’s wide digital distribution network to form a music streaming powerhouse.

One additional way for Spotify to quickly improve its recommendation capabilities is to ask users directly for their preference in music. Currently, Spotify’s recommendation is based on users’ implicit feedback such as stream counts. Users’ explicit feedback, however, can serve as a more accurate indicator of what users want and can significantly improve Spotify’s machine-generated recommendations.

Even though machine learning has been a competitive moat for Spotify, the competitors are catching up fast. How can Spotify better leverage its machine learning technologies to keep the lead in this industry? Spotify has already ventured out to AI-generated music with hiring of François Pachet in 2017, “the world’s foremost scientist in the field of AI-assisted music creation,” but are there any other ways Spotify can use machine learning to offer new services[8]? Also, in what potential areas can machine learning be used for Spotify to engage with the artists directly who would like to place their songs on Spotify?

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[1] International Federation of the Phonographic Industry, “Global Music Report 2018: State of the Industry”, https://www.ifpi.org/downloads/GMR2018.pdf, accessed November 2018.

[2] International Federation of the Phonographic Industry, “Global Music Report 2018: State of the Industry”, https://www.ifpi.org/downloads/GMR2018.pdf, accessed November 2018.

[3] Spotify Technology S. A, March 2018 IPO Prospectus, http://d18rn0p25nwr6d.cloudfront.net/CIK-0001639920/f9537bde-f9af-4553-b0bd-e7421f1f5074.pdf, accessed November 2018.

[4] Morgan Stanley, “Spotify Technology: House Band at a Big Party – Reiterate OW,” May 18, 2018, via Thomson Reuters/Investext, accessed November 2018.

[5] Spotify Technology S. A, March 2018 IPO Prospectus, http://d18rn0p25nwr6d.cloudfront.net/CIK-0001639920/f9537bde-f9af-4553-b0bd-e7421f1f5074.pdf, accessed November 2018.

[6] Sophia Ciocca, “How Does Spotify Know You So Well?,” Medium, October 10, 2017, https://medium.com/s/story/spotifys-discover-weekly-how-machine-learning-finds-your-new-music-19a41ab76efe, accessed November 2018.

[7] O’Reilly Media, “Machine Learning at Spotify: You are What You Stream,” December 7, 2017, https://www.oreilly.com/ideas/machine-learning-at-spotify-you-are-what-you-stream, accessed November 2018.

[8] Music Business Worldwide, “SPOTIFY’S SCIENTIST: ARTIFICIAL INTELLIGENCE SHOULD BE EMBRACED, NOT FEARED, BY THE MUSIC BUSINESS,” January 22, 2018, https://www.musicbusinessworldwide.com/spotifys-scientist-artificial-intelligence-should-be-embraced-not-feared-by-the-music-business/, accessed November 2018.