Filter Liked Songs and Playlists Using Custom or AI-Generated Hashtags

[NazanB]

Idea:

I’d love a feature that lets users filter their liked songs or playlists using hashtags—either custom ones or those automatically generated by Spotify/AI.

How it could work:

• Manual Hashtags: Users can assign their own hashtags to songs (e.g. #party, #chill, #roadtrip). Later, they can filter their liked songs or a playlist based on those tags.
• Automatic Hashtags: Spotify could use AI to analyze each track and tag it with relevant keywords based on mood, energy, genre, context, or era (e.g. #energetic, #focus, #2000s, #nightdrive, etc.).

Why this would be useful:

When you have hundreds or thousands of liked songs, it’s hard to quickly find tracks that match a mood or situation. This feature would help users create the right atmosphere on the fly—without having to build a new playlist every time.

Examples:

• Before going out, filter your library by #party.
• On a long drive, filter by #roadtrip or #chill.
• For studying, filter by #focus.

This would make the listening experience more flexible, personalized, and intuitive.

Bonus for DJs:

This system could also be extended to include filters by BPM (beats per minute). DJs could instantly surface tracks in a specific BPM range to create pre-configured playlists for mixing or performing, saving time and improving set curation.