Creating Personalized Listening Experiences with Spotify

Conference:  Transform X 2021


Authors:   Oskar Stal


The presentation discusses Spotify's approach to building a more connected and holistic system for content recommendation, utilizing machine learning models and data instrumentation.
  • Spotify is building an encoder system that can encode a user's state into embeddings that are sensitive to actions and changes in satisfaction.
  • They have built a simulator that can simulate user reactions to certain content, which is used to train the recommendation algorithm.
  • A/B testing is used to compare agents trained on good simulators versus less good simulators.
  • Spotify is transitioning to a more farsighted approach to content recommendation, optimizing for long-term fulfilling content diet rather than clicks or streams.
  • They are investing in data instrumentation to understand how users interact with their content and to create reusable data sets.
  • Spotify has shared machine learning models that provide information on user affinities, similarities, and clustering, which are useful for many different features.
  • Machine learning models are created for specific use cases, such as Discover Weekly or search, and optimize for different goals.
Spotify's use of a simulator to train their recommendation algorithm is similar to a chess player training against a chess simulator to improve their game.


Oskar Stal, VP of Personalization at Spotify, shares how Spotify ensures each of their 365 million listeners has a personal and unique experience as they each explore and enjoy the music they love. In this keynote, Oskar shares Spotify's evolution in machine learning from a single recommendation feature that engineers worked on in their spare time, to the wide-scale deployment of multiple personalized content recommendations, for each Spotify user. He shares how Spotify uses numerous sources of data to create a personal experience. Oskar also discusses how Spotify uses reinforcement learning to maximize short- and long-term recommendation objectives to build long-term user engagement. What makes a good content recommendation? How should you optimize recommendations to build a lifetime of loyal membership? How can you use simulation to train better recommendation models? Join this session to learn Spotify uses AI to build personalized listening experiences.