Spotify is overhauling Release Radar, its weekly playlist of new music from followed artists, with granular filtering controls. Users can now narrow recommendations by genre, prioritize discoveries from artists new to them, and apply additional filters within the playlist settings.
The feature addresses a core complaint about Release Radar: algorithmic curation doesn't always match listener mood or discovery goals. Some users want strict new artist exposure. Others want to rediscover deep cuts from established favorites. Spotify's solution lets listeners customize the algorithm's output without unfollowing artists or rebuilding their library.
The playlist, introduced in 2015, generates significant engagement. Spotify users check it weekly, making it one of the platform's most trusted discovery surfaces. But the algorithm has no way to distinguish between "I want mainstream hits" and "I want experimental indie." These controls inject user intent directly into the curation pipeline.
Up to five filter options can be stacked, letting users create highly specific playlists. A metal fan could filter for subgenres and exclude collaborations. A pop listener could focus solely on emerging artists. The controls persist week to week, building a playlist that evolves with preferences rather than forcing users to start from scratch.
This approach mirrors what Spotify learned from Discover Weekly, which remains its most successful personalization feature. Giving users agency over algorithmic output increases engagement and retention. When listeners control the dial, they trust the results more.
The update rolls out gradually to all Spotify users. It's a modest but meaningful shift toward transparency in playlist curation. Spotify reveals little about how Release Radar actually works, but these controls signal that the platform sees value in letting humans shape machine recommendations rather than accepting them passively.