Spotify Uses Reinforcement Learning For Their Recommenders To Build Sticky User Habits

Spotify aims to balance short-term rewards and long-term success for users. While it is important to provide immediate gratification when a user opens the app, solely recommending familiar content that was listened to previously can become monotonous and lead to user fatigue. To prevent this, Spotify combines familiar recommendations with new discoveries to enrich the user experience and promote long-term growth. By establishing new habits like listening to podcasts on specific days, users are more likely to remain engaged and satisfied with the platform. Although these new recommendations may initially have a lower click-through rate, they contribute to cumulative rewards and encourage users to continue returning to Spotify over time. This approach aligns with the principles of reinforcement learning, where the focus is not only on the next reward, but also on the overall accumulation of rewards in the future.