Spotify is rolling out a new feature that puts listeners in the driver’s seat of their music recommendations. For the first time, users will be able to directly review and edit the algorithmically generated “Taste Profile” that powers personalized playlists like Discover Weekly and the annual Spotify Wrapped.
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What is a Taste Profile?
The Taste Profile is Spotify’s internal model of a user’s music preferences. It’s built from every song, podcast, and audiobook a user listens to within the app. Until now, users had limited control over this profile, leading to frustratingly off-target recommendations.
How Will the New Feature Work?
The beta version, initially launching in New Zealand for Premium users, will allow users to access their full listening history in one place. From there, they can fine-tune their profile using natural language prompts – essentially asking Spotify for more or less of certain vibes. The app’s home page will immediately reflect the changes.
“This is a huge step towards transparency and user control,” says Gustav Söderström, Spotify’s co-CEO, at SXSW. “Listeners have wanted this for years.”
Why This Matters
For years, Spotify users have complained that the app’s recommendations feel inaccurate. This is due to several factors:
- Shared accounts: Family members using the same account skew the Taste Profile.
- Situational listening: Sleep sounds or music played for children contaminate the algorithm.
- Forgotten removals: Users often forget to exclude tracks they don’t want associated with their taste.
These issues have notoriously ruined many people’s Spotify Wrapped experience, a popular year-end feature that has become a cultural phenomenon.
What Happens Next?
Spotify says the Taste Profile editor will expand to other markets in the coming weeks. This feature marks a shift towards greater user agency, addressing long-standing complaints about algorithmic transparency and accuracy.
The bottom line: Spotify is finally letting users shape the music they hear, instead of being at the mercy of an opaque algorithm. This change could significantly improve the platform’s recommendation quality and user satisfaction.
