Spotify is testing a new personalization feature that allows listeners to directly edit the data behind their music recommendations. The feature, called “Taste Profile,” gives users more control over how Spotify’s algorithm interprets their listening habits and suggests new music.
The update was announced during the SXSW conference by Spotify co-CEO Gustav Söderström and is currently rolling out in beta to Premium users in New Zealand, with broader availability expected in the future.
What the Taste Profile Feature Does
Spotify’s Taste Profile is essentially the platform’s internal model of a user’s musical preferences. It is built from signals such as songs played, tracks skipped, playlists saved, and listening patterns over time. This data powers key features including Discover Weekly, Daily Mix playlists, and Spotify Wrapped.
The new feature allows users to review and modify this profile directly for the first time. Instead of relying only on listening behavior to influence recommendations, listeners can actively adjust the algorithm that drives their feed through a new conversational dashboard.
Users can request more of certain genres or moods, reduce specific types of music in their feed, or refine their recommendations through natural language prompts. For example, a user could type “more high-energy hip-hop for the gym” or “less mainstream pop,” and the system will retrain its model to update the homepage in real time.
Addressing Common Recommendation Problems
The feature is partly designed to solve a common frustration among Spotify users. Shared accounts, background playlists, or one-off listening sessions can sometimes distort recommendations.
For example, sleep sounds, children’s songs, or music played for specific occasions can unintentionally influence a user’s algorithm. By allowing listeners to edit their Taste Profile, Spotify hopes to ensure that recommendations more accurately reflect a user’s real preferences rather than accidental data “noise.”
The move builds on earlier personalization tools introduced by Spotify. In recent years, the company has allowed users to exclude specific tracks or playlists from their Taste Profile, but this update offers a much more direct, “under the hood” level of agency.
Part of Spotify’s Push Toward AI-Driven Personalization
The Taste Profile editing feature reflects Spotify’s broader strategy to deepen personalization across the platform. Streaming services increasingly rely on recommendation systems to help users navigate massive music catalogs that now contain tens of millions of tracks.
By giving listeners direct input into these systems, Spotify is experimenting with a hybrid model where algorithms still analyze behavior but users can actively guide the results. This follows the launch of Prompted Playlists earlier in 2026, which uses generative AI to create mixes based on text descriptions. While Prompted Playlists build something new, Taste Profile focuses on correcting the existing model.
What It Means for Artists and Discovery
For artists, recommendation algorithms remain one of the most important discovery engines in streaming. Playlists like Discover Weekly and Release Radar regularly introduce listeners to new music based on Taste Profile signals.
Allowing users to refine these signals could lead to more accurate recommendations and potentially improve discovery for artists whose music closely matches listener preferences. It places a higher premium on accurate metadata, as the AI will rely on how music is tagged to match it with explicit user requests.
For independent musicians especially, the change highlights how much modern music discovery depends on algorithmic systems. When listeners adjust their profiles, it can influence which songs and artists appear in their personalized playlists.
Testing Before a Wider Rollout
Spotify has not yet confirmed when the Taste Profile editing feature will launch globally. As with many experimental updates, the company is testing the feature with a limited group of users in New Zealand before expanding it further.
If the beta proves successful, the update could mark a significant evolution in how streaming platforms handle personalization, shifting some control over recommendation systems from algorithms to listeners themselves.
