Streaming Analytics Built for Label Catalogs

Streams come from every store on the list. Listeners come from Spotify, Apple Music and Audiomack, with Spotify and Apple reporting a true de-duplicated daily count per track. Saves come from Spotify and Audiomack. Skips and shares are Spotify signals.

Streams by country for Spotify, Apple Music, Deezer, Boomplay and Audiomack, with Apple adding its own city and storefront breakdowns. AWA reports streams with no country split, because its feed carries sub-national Japanese region codes rather than countries. KuGou, KuWo and QQ Music carry no country split either.

Streams by age and gender come from Spotify and Apple Music. Listener demographics from Spotify and Deezer are a different lens on the same audience, counting people rather than plays. They cover age and gender, region, plus the free-versus-paid plan mix of your listeners.

Spotify goes deepest here. Completion rate and skip behavior, average listen time and shuffle share. Then discovery and repeat-listener rates, with lyrics and canvas views alongside. Then the mechanics: device, OS, audio format, hour of day, and where the stream started, whether that was a playlist, someone’s library or a search. Deezer reports average listen time plus device and OS.

The placements view lists the playlists a track landed in for Spotify, Apple Music and Deezer, filterable per store. Spotify rows carry the playlist name plus its owner and stream count. Apple rows name editorial playlists and the best position the track reached, sometimes with no play count attached, because a missing count means the store did not report one. Deezer rows link out to the public playlist when the id resolves.

Library adds, editorial playlist adds and Shazam counts, including Shazams by city and state, come from Apple Music. Shazam is an Apple signal and Spotify has no equivalent.

When a store does not send a metric, the dashboard marks it unavailable for that platform. It never shows a zero, because zero is a real measurement and “this store does not publish this” is a different statement entirely.

KuGou, KuWo and QQ Music report once a week. Each report becomes one data point, dated to the day it covers and carrying that week’s whole total, never divided into seven invented daily figures. On a daily chart those stores show one populated date per week with space between, which is correct rather than missing, and range totals still add up.

Every metric carries its own reported-through date and its own complete-through date, and they are not always the same day. Anything between them is still arriving, so those buckets are marked partial instead of letting a half-reported day read as a collapse. Expect the trailing edge of a chart to rise on a later view.

Demographic and geographic breakdowns are k-anonymised. Apple city breakdowns, Shazams by city and state, and listener demographics all sit behind a minimum-audience floor, and a cell that falls below it is dropped outright: no “other” bucket, no rolled-up total that would let the suppressed audience be worked out backwards. A small catalog can therefore show healthy streams next to an empty demographics or city chart. That is the floor doing its job, and the space stays empty rather than getting filled with a number we invented.

Streaming-integrity detection stays out of customer analytics entirely, so nothing in these charts doubles as a verdict on an artist. That work lives in Stream Radar, a separate add-on with its own surface.