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Spotify listeners

SubmitHub displays an "average listener" number next to most playlists on the platform. It's our best estimate of how many people will actually hear a song added to that playlist.

What the number represents

We calculate a base 28-day listener estimate for each playlist: how many people listen to songs on that playlist during a 28-day window. The number shown on the site scales with how long a curator typically keeps songs in their playlist.

So if a playlist has a base 28-day number of 100, but the curator typically keeps songs in for 90 days, the displayed figure is a range around 320 (100 scaled up by 90/28). The idea: the number you see should reflect the total listeners your song is likely to get during its actual time on the playlist.

What factors into the calculation

  • Spotify for Artists data: curators and artists can grant us anonymized read access. This is our most accurate source.
  • Discovered-on attribution: Spotify exposes which playlists contributed to an artist's listens. We use that to reverse-engineer playlist-level listener estimates.
  • Average position in playlist: songs near the top of a playlist get far more listens than songs buried at the bottom. We track where songs shared via SubmitHub tend to sit in each playlist, and that feeds into our estimate.
  • Hold duration: as above, longer hold time scales the number up.

Why it might not match your own numbers

Our estimate is an average across songs on the playlist, not a number for any specific song. Your track might outperform or underperform depending on the song, the playlist's current size, and where in the playlist it sits. We deliberately err conservative: we'd rather you beat expectations than underdeliver.

If you want more accurate numbers

The single best way to make sure your playlist's numbers reflect reality is to share your Spotify for Artists data with us. It only takes a couple of minutes, and we walk through it in the Sharing data from Spotify for Artists article.

Long-term: keep sharing music consistently. The more data flows through, the more accurate our estimates get.