How to calculate and interpret streaming metrics correctly

How to calculate and interpret streaming metrics correctly
29th November 2021 sandra
Streaming Metrics

Basically, as musicians, we have access to tons of stats and metrics, and sure, we spend a lot of time counting how many people are streaming our songs, but what do we do with that information once we have it? How do we make the data speak to us in a way that makes sense? Don’t despair! We have made a quick guide to get into the nitty-gritty of reading and interpreting your stats.

“But I don’t know anything about math… I just know how to make music!”

Don’t worry, we have had calculators since 1642 and you’ll need them just for a few (easy) operations at the end of this post.

We can distinguish two basic groups when talking about music streaming metrics based on what they analyze: Song/Music and Artist Account. Analytic platforms offer us different kinds of data within these two.

If we go further, we can distinguish three different analytic categories: KPIs (Basics & Metrics/Graphics), Demographics, and Behavioral data (Cultural, Social & Personal behavior, Brand Affinity, Interests, Related Artists, Music Genres, etc). Perhaps, the next step may be psychological data.

KPIs (Key Performance Indicator) are simply indicators such as the number of monthly streams & listeners, saves to collection, downloads, views, likes, followers, subscribers, etc. On the other hand, metrics analyze the behavior of maybe two or three KPIs. Then, the metric translates the results into the form of a graph, a percentage, a chart, etc, and shows us the important info we want to know such as Skip Rate Value, Source of streams, Charts, Song Retention, Profile Retention, Level of Engagement, etc. In this blog, we’re going to talk about the spiciest ones.

 

Profile Retention

In ancient times (1 month ago) we had to use a calculator but Spotify knows we are lazy and now we have these stats available:

Profile retention spotify stats

There’s no average goal (of course, the higher the better), but we should always make a personalized study about the artist profile and set up the suitable value based on their career stage. The most important thing is to focus on the direct consumption from listeners rather than the consumption from playlists. In the end, this metric teaches us the magnitude of the audience’s engagement with the artistic project. Both metrics Song & Profile retention are ruled by two KPIs: Streams and Listeners.

 

Song Retention

Time to take out that calculator!

Monthly Streams / Monthly Listeners = Song Retention

Practical example:

Song retention spotify analytics

1969/1102= 1,78 streams per listener

 

This would mean that every listener, listens to this song 1,78 times per average.

Song retention evolves throughout the release stages (promo – stabilization – descent). The most suitable value averages about two streams per listener once the song has surpassed the promo stage. When it’s time to analyze this metric, we should ask ourselves which have been the main sources of streams.

 

Level of Engagement/ Fan Conversion Rate

 

Number of Followers / Monthly Listeners x 100 = Level of Engagement 

 

Practical Example:

Number of followers: 77.203

Monthly Listeners: 551,353

77,203/551,353 x 100=14,00 would be the conversion rate of singer and songwriter Eloise

When someone follows, they want to know what’s gonna be next (‘Release Radar’ algorithmic playlist is the perfect example). The level of engagement metric shows who are your loyal listeners. Once again, we have to make the same analytic exercise that we’ve done before to understand what’s the appropriate value for each artist. Any time a song gets into any kind of playlist that has a massive audience, this metric will go down due to the song being displayed to many listeners. This is not bad behavior: in fact, it’s really helpful to give the extra push that artists need on the streaming ecosystem to get known by a different type of audience. However, if we stick to a strong strategy guiding our actions, we’ll increase the probability to get better results in less time.

We hope you enjoyed this post! Click here to know the most useful tips for turning listeners into fans 

 

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