![]() ![]() Audio: Models that analyze the raw audio files.Ĭollaborative filtering is a key component of many recommendation engines today (Netflix, Amazon).Natural Language Processing (“NLP”): Models that scan the internet and analyze text about Spotify’s catalog.Collaborative Filtering (“CF”): Models that analyze your behavior and compare it to other users’ behaviors.The Discover Weekly engine uses three main types of recommendation models simultaneously. Įvery week, Spotify generates a new playlist for each subscriber called “Discover Weekly”, a personalized list of 30 songs that fit that user’s taste profile. None were more important than the purchase of Echo Nest, a data-analytics startup that revolutionized the way music recommendations were generated by mixing the best strategies used by other services, creating a unique discovery engine that has increased Spotify’s differentiation. In order to improve its product capabilities, Spotify has made several strategic acquisitions since 2014. Pathways to Just Digital Future Watch this tech inequality series featuring scholars, practitioners, & activists ĭiscover Weekly: How Spotify uses machine learning to recommend music Today, across both its curated and machine generated playlists such as Discover Weekly and Rap Caviar, Spotify recommended over 30% of overall listening in 2017, up from less than 20% in 2015, providing a highly personalized listening experience. Using machine learning, Spotify has created a virtuous circle in which increased user engagement and scale drive larger data sets, data in turn drives improved recommendations and discovery and, finally, discovery drives differentiation. Given the limited content exclusivity (most platforms have licenses for the same song catalogs) and non-existent overlap in subscriber bases, user experience and technology are critical differentiating factors among streaming services. How song recommendations are impacting the music industry today The ever-increasing proportion of music that is recommended to consumers has implications beyond simply improving the user experience: it is helping shift the balance of power in the music industry from traditional record labels to distribution platforms. The company has successfully differentiated itself from other streaming platforms by using machine learning to fuel its superior music discovery and recommendation algorithms. The service commands a ~60% market share and provides 157 million monthly active users (“MAUs”) and 71 million paying subscribers access to a music catalog of over 35 million songs. Founded in 2006, Spotify has grown to become the world’s largest music streaming platform. ![]()
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