How can you spot fake playlists?
Between 1 and 3 billion streams were considered fraudulent in 2021
The private curator playlist market is an opaque one, with many playlisting solutions charging you inordinate prices for fake streams generated by bots, or in countries that don't share the language of your music.
While we were looking into this subject, we came across Isitagoodplaylist, a playlist analysis tool. So we decided to talk to Julien Mahin, its founder, whose values we share: saving artists time by giving them access to accessible, high-performance tools.
What impact can you expect from playlist placement? What rules need to be applied to make it consistent?
The impact varies greatly depending on the playlist, and in any case you can have different objectives. If the artist simply wants to increase the number of listeners, it will be more interesting to target playlists with a large number of listeners, while hoping to be among the first tracks on the playlist. On the other hand, other objectives may be more interesting in the long term, such as generating enough quality listens to trigger Spotify's algorithm, and thus start appearing in the algorithmic playlists.
Finally, generating listener engagement is also crucial in the long term. The more times listeners save tracks or follow the artist, the more likely it is that they will be listened to on a regular basis. For these two objectives, the playlists with the most listeners are not always the best. You can get very good results with smaller playlists, the important thing being to target the genre as much as possible, to ensure that the listener enjoys the music and doesn't move on to the next track.
Be careful, however, not to pay too much to be added to a playlist, as this is generally a sign of a business that's a little on the limit, and you simply run the risk of your track being listened to by bots, and ultimately degrading the Spotify algorithm's understanding of your audience.
What indicators are useful for differentiating a good playlist from a bad one, and how can these indicators be gauged?
The first indicator to look at is very simple and within everyone's reach: the change in the number of followers of the playlist. If you see spikes or drops in the graph, it's probably a sign of bots: the curator has probably bought followers whose accounts have been deleted by Spotify at some point, or when the curator has stopped paying for his fake followers... Instead, focus on playlists where the number of followers grows steadily over time, which is much more like organic growth.
If you continue to focus on the number of followers, you can also extend the analysis to all the curator's playlists. This is a brand new feature recently added to isitagoodplaylist, and it allows you to check that each of the curator's playlists has its own growth. Several playlists have exactly the same peaks and drops? Run away. All the playlists have the same number of followers? Be careful too, it doesn't look like a legitimate situation.
Another key indicator to take into account is the genre of the songs and artists in the playlist. Ideally, it's best to target playlists that fit your genre as this will give Spotify a better understanding of who/when/how to suggest your tracks to, and you're also more likely to get listeners to actually enjoy your music (and generate engagement). Of course, you shouldn't rule out more generic playlists (such as current hits, artists from a particular region or country, hits from a particular era, etc.) but these shouldn't account for the majority of your submissions.
Unfortunately, the number of followers of a playlist does not always have a real link with the number of listeners, which is not shared publicly. However, thanks to the collaboration of over 3,000 artists who share their Spotify For Artists data with us, we are able to estimate the number of listens you can get to certain playlists. This can also help you select the right playlists, but above all it can help you avoid playlists with thousands of followers but very few listens.
This estimate is not available for all playlists, so you can make a fairly broad estimate, based on the "Discovered On" section of the artists in the playlist. On the artist's profile, this section lists the playlists from which the artist has had the most unique listeners in the last 28 days.
For example, an artist with 300 monthly listeners was added to the playlist more than 28 days ago, at the top of the playlist, but does not appear in the "Discovered On" section? Chances are that the playlist has very few listeners, if any, as it would then appear in the list. Of course, checking this manually for each artist in the playlist is extremely time-consuming.
That's why we've tried to automate this part, by displaying this data in a single table, grouping together all the artists in the playlist. At a glance, you can form your own opinion.
What is the intrinsic aim of isitagoodplaylist and how is it a good tool for spotting fake playlists?
The aim in creating isitagoodplaylist was to create a tool to simplify the analysis and time needed to understand whether a playlist was interesting for an artist or not. That's how it all started: to automate a process already done manually by many artists, which would now take a few seconds instead of several minutes.
What's more, thanks to all the data available, we can now help a lot of artists avoid being taken in by a lot of playlists that are actually scams. Their time and money is, I hope, better spent thanks to our playlist analysis tool. We've recently extended our functionality to help artists find playlists where they can submit their tracks. We already had the data available, so all we had to do was put an interface on top of it and add a bit of logic. Now, our members can browse a database of almost 5 million playlists (140,000 curators) with contact information (an email, an Instagram account, a submithub link, a facebook profile, etc.).
Of course, the list can be filtered on the basis of a number of parameters, such as genre, whether the playlist has been updated recently, the estimated number of listens, etc. And to make things even simpler, we can also automatically suggest playlists that might match your music, based on hundreds of parameters. All you have to do is enter your Spotify link, and we'll take care of providing you with a list of playlists where your music might fit in. All you have to do is check that they match your criteria, and contact the curator.
Contacting the curator is not always easy, and can be time-consuming if you want to do things right with a personalised message. The good news is that we've also developed the Pitch Writer, which will automatically write a message to send to a curator to submit your track for one of their playlists. The artificial intelligence will generate a message briefly introducing you and explaining why your track should be included in the playlist (other similar track, similar artist, genre, tempo, etc.). This is another step that used to take several minutes, but can now be completed in a matter of seconds. We're doing everything we can to simplify the whole process from playlist discovery to submission as much as possible, while helping to validate that the playlist is legitimate.
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