Summary
Provide per-user listening statistics for tracks, including play counts and listening engagement metrics.
Proposed Endpoint
GET /me/track-stats
Example Response
{
"track_id": 12345,
"play_count": 47,
"total_listening_time_ms": 8923000,
"last_played_at": "2026-06-05T12:34:56Z",
"completion_rate": 0.91
}Requested Data
- Number of times a user played a track
- Total listening time per track
- Last played timestamp
- Completion rate
- Replay count
Use Cases
Personal Analytics
Users can discover which tracks they actually listen to most, rather than relying on likes as a proxy.
Recommendation Engines
Play frequency often provides a much stronger signal of preference than likes alone.
Music Compatibility Apps
Comparing shared listening behavior becomes much more meaningful when based on actual engagement rather than saved tracks.
DJ & Playlist Tools
Developers can identify tracks that consistently receive high replay rates and engagement.
Why This Matters
Currently, developers can access likes, playlists, and follows, but cannot determine which tracks users truly engage with. A track played 50 times and a track played once appear identical through the current API.
Exposing listening statistics would unlock a richer ecosystem of analytics, recommendation, and discovery applications while remaining compatible with OAuth-based user consent.
Privacy
Access should require explicit OAuth authorization, for example:
track-stats:read
Summary
Provide per-user listening statistics for tracks, including play counts and listening engagement metrics.
Proposed Endpoint
GET /me/track-stats
Example Response
{ "track_id": 12345, "play_count": 47, "total_listening_time_ms": 8923000, "last_played_at": "2026-06-05T12:34:56Z", "completion_rate": 0.91 }Requested Data
Use Cases
Personal Analytics
Users can discover which tracks they actually listen to most, rather than relying on likes as a proxy.
Recommendation Engines
Play frequency often provides a much stronger signal of preference than likes alone.
Music Compatibility Apps
Comparing shared listening behavior becomes much more meaningful when based on actual engagement rather than saved tracks.
DJ & Playlist Tools
Developers can identify tracks that consistently receive high replay rates and engagement.
Why This Matters
Currently, developers can access likes, playlists, and follows, but cannot determine which tracks users truly engage with. A track played 50 times and a track played once appear identical through the current API.
Exposing listening statistics would unlock a richer ecosystem of analytics, recommendation, and discovery applications while remaining compatible with OAuth-based user consent.
Privacy
Access should require explicit OAuth authorization, for example:
track-stats:read