Spotify is testing a new feature that gives users more control over the music recommendations they receive.
The company has started rolling out a beta version that allows Spotify Premium users in New Zealand to directly view and adjust their Taste Profile.
The Taste Profile is the system Spotify uses to understand what kind of music a listener enjoys. It analyzes listening habits, favorite artists, and trends in what someone plays over time. With this new test feature, users can now see those insights and make changes if the recommendations are not quite right.
For example, if the algorithm keeps recommending a certain artist or genre that a user is no longer interested in, they can simply tell Spotify to reduce those suggestions. The feature can be accessed by tapping the profile icon and choosing the Taste Profile option in the sidebar menu.
Spotify also shows small insights about listening patterns. In one example shared by the company, the profile notes that a user is starting to explore 1990s alternative rock. These insights help listeners understand how their habits influence the music they are recommended.
At the bottom of the Taste Profile page there is a section called “Tell us more.” Here users can type requests to adjust what they want to hear more or less of. Someone could ask for more hip hop tracks, fewer songs from a certain genre, or even music suited for specific activities such as marathon training. Spotify then updates recommendations based on those inputs.
This idea is similar to Spotify’s Prompted Playlists feature, which uses a chatbot-style prompt to build playlists based on what a user describes.
Spotify is also improving podcast discovery. The Following Feed for podcasts now includes filters so listeners can sort episodes more easily. Users can choose to view only unplayed episodes, episodes they have already started, or even just video podcasts.
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Together, these updates show Spotify moving toward giving listeners more direct control over the algorithms that shape their listening experience. Instead of the system quietly deciding what to recommend, users can now guide it more clearly.
