{"id":31449,"date":"2018-11-13T12:43:39","date_gmt":"2018-11-13T17:43:39","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/"},"modified":"2018-11-13T13:09:40","modified_gmt":"2018-11-13T18:09:40","slug":"spotify-machine-learning-as-recommendation-engine-and-musical-composer","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/","title":{"rendered":"Spotify: Machine Learning as Recommendation Engine and Musical Composer?"},"content":{"rendered":"

The Music Streaming Industry & Personalization<\/strong><\/h3>\n

The music streaming industry has grown rapidly over the past few years and in 2017, surpassed 100M paying subscribers worldwide. As it has grown, the industry has also become highly competitive. The most popular paid streaming services are Spotify, Apple Music, Deezer, Rhapsody, Google Play and Tidal.[i]<\/sup><\/a> Apple Music has approached Spotify\u2019s lead and in May 2018, reported that it had 50M subscribers (paying and on trials)[ii]<\/sup><\/a>.<\/p>\n

With more musical content accessible online than ever before, Spotify must compete to keep users (and in turn brands and advertisers) engaged with and paying for its platform. Core to continued user engagement is a strong recommendation and personalization engine powered by data and machine learning \u2013\u00a0satisfied listeners will find the right song for each moment throughout the day. Spotify has invested heavily in both capabilities and to win in the space they will need to continue to innovate.<\/p>\n

\"\"<\/a>
Source: Financial Times<\/a>\u00a0, “How Streaming Saved The Music Industry”<\/figcaption><\/figure>\n

Spotify\u2019s Investment in Machine Learning <\/strong><\/h3>\n

Spotify recognized early on that to keep listeners engaged at scale, they needed to use machine learning to personalize recommendations for listeners. In 2014, Spotify acquired EchoNest, a \u201cmusic intelligence company\u201d[iii]<\/sup><\/a> that many of its competitors used in their recommendation engines. Specifically, EchoNest uses machine listening software to analyze songs (including features such as tempo, pitch, vocals, and energy) and crawls the web to index descriptions and reviews of music. The software then combines this information to make recommendations based on both how the music sounds and how it is being reviewed externally.[iv]<\/sup><\/a><\/p>\n

Since, Spotify has continued to focus on machine-learning powered personalization. They have made additional acquisitions to increase their technical capabilities such as Mighty TV, Niland, Sonalytic and SoundTrap.[v]<\/sup><\/a> As of December 2017, the company logged 150 billion user events daily — including actions such as playing, skipping, following or upvoting a song — and personalized content with algorithms that took into account over 40 different parameters such as user demographics, past listening behavior, time of day and location.[vi]<\/sup><\/a> Over 31% of all listening on the platform is now through Spotify\u2019s playlists, including machine-generated playlists such as \u201cDiscover Weekly,\u201d \u201cDaily Mix\u201d and \u201cRelease Radar.\u201d[vii]<\/sup><\/a> Through continued investment in data collection and machine learning, Spotify has differentiated its platform through a seamless music discovery process.<\/p>\n

\"\"<\/a><\/p>\n

Longer term, Spotify has begun working to use all of the data it has gathered on listener habits not only to recommend hit music, but to create it as well. In coverage of their 2018 Machine Learning Day, the company advertised exploring \u201chow to generate coherent music.\u201d[viii]<\/sup><\/a> AI Scientist Francois Pachet leads this charge and runs Spotify\u2019s \u201cCreator Technology Research Lab\u201d in Paris.[ix]<\/sup><\/a> This entirely new form of content development would enabled Spotify not only to better engage listeners with more hits, but also to decrease the significant impact of artist royalties on the bottom line.<\/p>\n

Competition, Backlash and Recommendations <\/strong><\/h3>\n

Even in their cutting-edge investment to use machine learning capabilities to compose songs, Spotify faces competition. Through Project Magenta, Google has also focused on machine learning capabilities to generate music along with other forms of art.[x]<\/sup><\/a> As such, Spotify must continue to invest heavily in this research to stay ahead in product development.<\/p>\n

However, as it invests in these capabilities, Spotify must also be careful not to alienate either side of its platform \u2013\u00a0listeners or artists. Listeners have not always responded positively to the data collection required for Spotify\u2019s algorithms. In 2015, the company released updated privacy terms that indicated access to personal data on users\u2019 phones and the CEO, Daniel Elk, had to apologize publicly.[xi]<\/sup><\/a> Spotify also risks alienating artists on the platform as it pursues an alternate and competitive path to content generation.<\/p>\n

To maintain its relationship with artists and stay true to its mission to \u201cunlock the potential of human creativity\u201d[xii]<\/sup><\/a> Spotify should focus its investment on algorithms that co-create music with artists and inform rather than supplant the creative process. Pachet has hinted at a focus in this direction and said that he is building \u201ccompanions and collaborators.\u201d[xiii]<\/a> To maintain trust with listeners, Spotify should transparently share data practices and when possible, include listeners in the data collection processes through tooling such as \u201cLine-In\u201d that enables users to suggest metadata for a song while listening.[xiv]<\/sup><\/a><\/p>\n

Key Questions Moving Forward <\/strong><\/h3>\n

As Spotify scales, they will need to grapple with the long-term ramifications of combining art and science and to consider if at any point their investment in machine learning has gone too far. Does human curation still play any role in music selection and do we need human musicians in the creation process? Further, if and when does collection of listener data cross a line \u2013 can tracking a listeners\u2019 every move step past product innovation to become a form of privacy invasion?<\/p>\n

Word Count: 788<\/p>\n

 <\/p>\n

[i]<\/sup><\/a> Anna Nicolaou, \u201cHow Streaming Saved The Music Industry,\u201d Financial Times<\/em>, January 16, 2017, https:\/\/www.ft.com\/content\/cd99b95e-d8ba-11e6-944b-e7eb37a6aa8e<\/a><\/u>, accessed November 2018.<\/p>\n

[ii]<\/sup><\/a> Anna Nicolaou, \u201cApple Slices Into Spotify\u2019s Lead In US Music Market,\u201d Financial Times<\/em>, July 9, 2018, https:\/\/www.ft.com\/content\/ef2be1bc-809f-11e8-bc55-50daf11b720d<\/a><\/u>, accessed November 2018.<\/p>\n

[iii]<\/sup><\/a> Darrell Etherington, \u201cSpotify Acquires Echo Nest, Gaining Control Of The Music DNA Company That Powers Its Rivals,\u201d TechCrunch, <\/em>March 6, 2014, https:\/\/techcrunch.com\/2014\/03\/06\/spotify-acquires-the-echo-nest\/<\/a><\/u>, accessed November 2018.<\/p>\n

[iv]<\/sup><\/a> Jim Lucchese, Competing with Data and Analytics, interviewed by Sam Ransbotham, MIT Sloan Management Review<\/em>, February 24, 2015, https:\/\/sloanreview.mit.edu\/article\/analytics-in-e-major\/<\/a><\/u>, accessed November 2018.<\/p>\n

[v]<\/sup><\/a> Spotify Technology S.A., Form F-1 Registration Statement (filed February 28, 2018), p.104, from SEC EDGAR, https:\/\/www.sec.gov\/Archives\/edgar\/data\/1639920\/000119312518063434\/d494294df1.htm<\/a><\/u>, accessed November 2018.<\/p>\n

[vi]<\/sup><\/a>Spotify Technology S.A., Form F-1 Registration Statement (filed February 28, 2018), p.15, from SEC EDGAR, https:\/\/www.sec.gov\/Archives\/edgar\/data\/1639920\/000119312518063434\/d494294df1.htm<\/a><\/u>, accessed November 2018.<\/p>\n

[vii]<\/sup><\/a> Ibid., 98.<\/p>\n

[viii]<\/sup><\/a> Nicola Bortignon, \u201cSpotify ML Day \u2013\u00a0Coverage,\u201d Spotify Labs<\/em>,\u00a0 August 22nd, 2018, https:\/\/labs.spotify.com\/2018\/08\/22\/spotify-ml-day-coverage\/<\/a><\/u>, accessed November 2018.<\/p>\n

[ix]<\/sup><\/a> Kevin Maney, \u201cSpotify, IBM and Google Using AI to Make Human Musicians Extinct?,\u201d\u00a0Newsweek<\/em>, February 2, 2018, https:\/\/www.newsweek.com\/artificial-intelligence-changing-music-799794<\/a><\/u>, accessed November 2018.<\/p>\n

[x]<\/sup><\/a> Cade Metz, \u201cHow A.I. Is Creating Building Blocks to Reshape Music and Art,\u201d New York Times<\/em>, August 14, 2017, https:\/\/www.nytimes.com\/2017\/08\/14\/arts\/design\/google-how-ai-creates-new-music-and-new-artists-project-magenta.html<\/a><\/u>, accessed November 2018.<\/p>\n

[xi]<\/sup><\/a> Hayley Tsukayama, \u201cSpotify Apologizes for its News Privacy Policy,\u201d The Washington Post<\/em>, August 21, 2015, https:\/\/www.washingtonpost.com\/news\/the-switch\/wp\/2015\/08\/21\/spotify-apologizes-for-its-newest-privacy-policy\/<\/a><\/u>, accessed November 2018.<\/p>\n

[xii]<\/sup><\/a> Spotify Technology S.A., Form F-1 Registration Statement (filed February 28, 2018), p.1, from SEC EDGAR, https:\/\/www.sec.gov\/Archives\/edgar\/data\/1639920\/000119312518063434\/d494294df1.htm<\/a><\/u>, accessed November 2018.<\/p>\n

[xiii]<\/a> Kevin Maney, \u201cSpotify, IBM and Google Using AI to Make Human Musicians Extinct?,\u201d\u00a0Newsweek<\/em>, February 2, 2018, https:\/\/www.newsweek.com\/artificial-intelligence-changing-music-799794<\/a><\/u>, accessed November 2018.<\/p>\n

[xiv]<\/sup><\/a> Janko Roettgers, “Spotify Enlists Its Users to Add Music Metadata,”\u00a0Variety<\/em>, March 12, 2018, https:\/\/variety.com\/2018\/digital\/news\/spotify-line-in-music-metadata-1202723757\/<\/a><\/u>, accessed November 2018.<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Spotify has invested heavily in machine learning capabilities to power its recommendation and personalization engines in a competitive streaming environment. Is this a competitive advantage the company can maintain?<\/p>\n","protected":false},"author":11742,"featured_media":31453,"comment_status":"open","ping_status":"closed","template":"","categories":[298,4247,2641,346,249,2738],"class_list":["post-31449","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-big-data","category-data-privacy","category-digital-streaming","category-machine-learning","category-music","category-spotify","hck-taxonomy-organization-spotify","hck-taxonomy-industry-music","hck-taxonomy-country-sweden"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"\nSpotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Spotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"Spotify has invested heavily in machine learning capabilities to power its recommendation and personalization engines in a competitive streaming environment. Is this a competitive advantage the company can maintain?\" \/>\n<meta property=\"og:url\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/\" \/>\n<meta property=\"og:site_name\" content=\"Technology and Operations Management\" \/>\n<meta property=\"article:modified_time\" content=\"2018-11-13T18:09:40+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Screen-Shot-2018-11-13-at-12.37.34-PM.png\" \/>\n\t<meta property=\"og:image:width\" content=\"927\" \/>\n\t<meta property=\"og:image:height\" content=\"228\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/\",\"name\":\"Spotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Screen-Shot-2018-11-13-at-12.37.34-PM.png\",\"datePublished\":\"2018-11-13T17:43:39+00:00\",\"dateModified\":\"2018-11-13T18:09:40+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/#primaryimage\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Screen-Shot-2018-11-13-at-12.37.34-PM.png\",\"contentUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Screen-Shot-2018-11-13-at-12.37.34-PM.png\",\"width\":927,\"height\":228},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Submissions\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Spotify: Machine Learning as Recommendation Engine and Musical Composer?\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\",\"name\":\"Technology and Operations Management\",\"description\":\"MBA Student Perspectives\",\"potentialAction\":[{\"@type\":\"性视界Action\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Spotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/","og_locale":"en_US","og_type":"article","og_title":"Spotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management","og_description":"Spotify has invested heavily in machine learning capabilities to power its recommendation and personalization engines in a competitive streaming environment. Is this a competitive advantage the company can maintain?","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/","og_site_name":"Technology and Operations Management","article_modified_time":"2018-11-13T18:09:40+00:00","og_image":[{"width":927,"height":228,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Screen-Shot-2018-11-13-at-12.37.34-PM.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"6 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/","name":"Spotify: Machine Learning as Recommendation Engine and Musical Composer? - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Screen-Shot-2018-11-13-at-12.37.34-PM.png","datePublished":"2018-11-13T17:43:39+00:00","dateModified":"2018-11-13T18:09:40+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Screen-Shot-2018-11-13-at-12.37.34-PM.png","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Screen-Shot-2018-11-13-at-12.37.34-PM.png","width":927,"height":228},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/spotify-machine-learning-as-recommendation-engine-and-musical-composer\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/d3.harvard.edu\/platform-rctom\/"},{"@type":"ListItem","position":2,"name":"Submissions","item":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/"},{"@type":"ListItem","position":3,"name":"Spotify: Machine Learning as Recommendation Engine and Musical Composer?"}]},{"@type":"WebSite","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website","url":"https:\/\/d3.harvard.edu\/platform-rctom\/","name":"Technology and Operations Management","description":"MBA Student Perspectives","potentialAction":[{"@type":"性视界Action","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/d3.harvard.edu\/platform-rctom\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/31449","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/users\/11742"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=31449"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/31449\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/31453"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=31449"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=31449"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}