Explaining how the success of a release is built is one of the multiple features of Datamusic analytics in your backstage. We have taught you HERE how to analyse the source of your streams. You will then be able to analyse your catalog view based on the most playlisted tracks. Let’s dig further in with CSV files and a case study.
Did you know you could download a list of the playlists revealed by Datamusic?
- Start at the global overview as previously (cf article HERE)
- Click on the top-right button to open the download menu
- Tick “top playlists”
- Open the downloaded file which will contain all the key playlists where the tracks ever appeared – and how many streams that generated!
Check the < Curator > column for a list of all registered curators. Why not generate a pivot-table if you want to go further?
You even have the playlist IDs in the list, which you can just copy- paste into Spotify’s search-box to open the playlist.
Footnote : thing you should keep in mind
We don’t measure algorithmic “personalised” playlists (playlists generated by algorithm, to best fit your listening habits): as we only register playlists which have a minimum of 50 followers.
Zoom on Key Playlists for a typical new campaign. This campaign (2 singles & 1 EP in 3 month) displays some pretty standard trends :
(Pivot-table created after a DataMusic playlist export covering a 90-day period of an artist )
- Predominance of Editorial playlists
- There are still playlists curated by media, radios or blogs which can still have a light impact
- Major-owned curators (Sony’s Filtr, UMG’s Digster, Warner’s Topsify…) are minor compared to the services’ own editorial playlists
- Third-party curators, such as other artists or labels, don’t usually gather a following as big as these other playlists (outside of
Major artists of course). Still, appearing in their playlist gives great credibility to the track and provides a great opportunity for cross-promotion on social networks.