‘Subscriber Share’ Royalty Payment Model in Music Streaming

Only by switching from ‘global/regional pool royalty payment system’ to ‘subscriber share’ system on a music streaming platform the doors of some interesting aspects may open.

What is royalty?
According to the following link the definition of royalty is: ‘ ‘A royalty is a payment to an owner for the use of property, especially patents, copyrighted works, franchises or natural resources. A royalty payment is made to the legal owner of the property, patent, copyrighted work or franchise by those who wish to make use of it for the purposes of generating revenue or other such desirable activities. In most cases, royalties are designed to compensate the owner for the asset’s use, and they are legally binding.’

How current royalty payment models work?
The following simplified method is followed by Spotify on a regional (per country level).

Spotify claims that approximately 30% of the revenue generated from an artist’s catalogue stays with Spotify, while the other 70% is handed over to the rights holder (labels, publishers, distributors) who are then charged with paying out their artists. Two important considerations are that royalty payments and calculations are done on a per stream basis and that subscriber fees are being merged to a regional pool (per country) and the payments will be split from these pools on a per stream basis — based on my best understanding. According to the above article average ‘per stream’ payouts to right holders is approx. $0.006 and $0.0084.

In my opinion the following implications are important to understand the benefits of the below proposed ‘subscriber share’ royalty payment model (which is actually not a new desire — you can find more on ‘subscriber share’ in some other articles on medium.com. Also it is worth mentioning ‘stream to own’ model by resonate.is which is a straight forward approach either — you can find more details on their webpage):

Per stream royalty payment method makes significant difference whether a song is 2 or 20 minutes long.
1 stream is usually accepted after 30 seconds.
‘Heavy users’ — users listening way more than the average — ‘use’ some portion of less heavy users’ subscription fees and shifts those to right holders of the artists ‘Heavy users’ are listening too.

Here are some simplified calculations in relation to streams and royalty payments:

The global/regional pool model overall can lead (according to Spotify) to $ 0.006–0.0084 per streaming rate. To earn $1 by artist (right holder) means 120–165 streams per month. Users’ streams are added to overall global streams and royalty is calculated based on the above simplified scheme (noting that there are other factors which make it more complicated but the simplified method is the above).
148 min — That’s how long the average cross-platform user spends listening, dancing or singing along to Spotify every day (2015 data). This means 74 hours/30 days= 4440 minutes.
Calculating with average 4 min/stream — and $6 per month approximately paid for royalties: user ‘spends’ all his/her $6 by listening to approx. 720–990 streams — overall this means 2880–3960 minutes.
Users listening more than the above 2880–3960 min per month ‘maximize’ their efforts to donate their favorite artists completely from their subscription fees however data is not available what portion of the overall users they are actually. This really depends on whether we end up with a bell curve or a skewed distribution. In case of a bell curve depending on the standard deviation the % of users ‘maximizing’ their efforts would be less than 50%. In case of a negative skew this % can be even lower. In case of a positive skew these users can be under or over 50%. The assumption is that the curve of monthly streams (not talking about listening time at this point as Digital Service Providers count streams) most likely has a positive skew.
The royalty portion of the subscription fee of a particular user depends on the ‘performance’ of other users. Users on the lower scale will not ‘burn’ their all fees but heavy users will do for them.

Theoretical implications and consequences can be the followings:

While per stream logging of use is important for pro-rated licensing terms this seems an inadequate method for royalty payments due to the above anomalies.
A system that combines per stream method with the global/regional pool for royalty payments can be biased theoretically and the bias will not remain on a single user level but will have impact on other users subscription fee value.
Due to the potential bias and the broader impact (impact for not just one user who does the actual bias) the system may not be able to disclose important and useful data and may not be able to connect parties directly — e.g. artists with individual users. This is a theoretical assumption.
This closes the opportunities for great engaging and motivational tools that may strengthen connection between artists and dedicated fans — or as we can call in the future: ‘friends’.
While the above may not be interesting for the majority of the users the opportunity of engaging and motivational tools in a system which uses the below described ‘Subscriber Share’ model can provide additional advances for a potential music streaming service — provided that this has a reasonably broad catalog as well.
This year as being a user of one of the major digital service providers (music streaming service) I received an end of year e-mail compiling some great data of my usage of the system in 2016 . It turned out that I am in the highest 1% percentile of fans for Haken (which is a fantastic band actually) however the band will never know about that. Why? My assumption is that the disconnection that disables providing this data to the band is emerging from the above implications and consequences.

So what is ‘Subscriber Share’ model?
To avoid the above implications and potential anomalies one of the opportunities of a music streaming platform is to utilize ‘Subscriber Share’ model and to use listening-time based royalty payment method.

The definition of ‘Subscriber Share’ model is simple: user’s subscription fee does not feed into a global/regional pool — the fee is split between artists (right holders) based on what the user was actually listening to. This can be done on e.g. a monthly basis.
Royalty payment portion should be calculated based on user’s listening time and not on per stream basis.

Below I will highlight just a couple of easy examples staying with the $6 assumption:

1. User only listens to 1 song in a month (for royalty payments it does not make difference whether 1 time or 1000 times however for other aspects this will make difference — e.g. engagement). In such case $6 will go to right holder of the song.
2. User listens to 2 songs only from 2 different artists in a given month — A and B. User was listening to A’s song for 2 hours overall while he/she was listening to B’s song for 4 hours overall. In that case $2 is paid for A’s song right holder and $4 is paid for B’s song right holder.
3. User listens to 100 songs from 100 artists — all songs are exactly 4 minutes long. Each song’s right holders receive $6/100: 6 cents.

The following implications and considerations may need to be made:

This is cannot necessarily be stated that certain type of right holders will be winners or losers in the subscriber share model compared to the global pool model (e.g. majors vs. indie). This can be however assumed that artist with a highly engaged fan-base should benefit from such approach.
Any system usage biases remain on an individual user level. A user may listen to one artist for 24 hours per day and can make ‘per stream’ ‘click bias’ (clicking to one song in every 31 seconds) — this may only impact user’s position as being a heavy fan of the artist or may have only statistical implications on the overall number of streams for that particular artist/song BUT this would not have an impact on other users’ subscription fee shifting.
With the ‘Subscriber Share’ and listening-time approach the system is able to retrieve and provide trustful and reliable data to both parties — artists and users — so that voluntary disclosure and connection of the parties can be enabled.
What can this mean in practice? I can choose to disclose my listening time data to Haken voluntarily and safely and there would be no surprises and disconnections between data even if I am not a ‘heavy user’ of the system but a ‘heavy fan’ of Haken. I would not realize that despite I am a big fan of Haken some portion of my money went to Justin Bieber as I am not heavy user enough to maximize my efforts of donating my favorites.
I can be personally recognized by the artist as a huge fan.
I can clearly see directly/indirectly how much money I have donated the band with.
Even — I know at first glance this may sound pretty weird — I can set a higher subscription fee than a minimum to fully donate the artists I love.
And there can be even way more engaging and motivational tools for key stakeholders built in just by switching to ‘Subscriber Share’ and ‘listening time based’ royalty payment and tracking model — that can be subject of a subsequent article.

One con is that such a service may hardly be able to utilize ad-supported service as the basic concept is clearly in conflict with a model where users do not pay for the service. Personally I think ad-supported service ideally would need to be a ‘no-go’ in music streaming. An ad-supported service is devaluing the music itself.

My opinion is that a service utilizing the ‘Subscriber Share’ method and ‘listening time based tracking’ can increase engagement and potentially is able to engage a significant portion of users. The feature of direct connection between artists and fans would strengthen the relation and both parties can step into win-win situations.

The ultimate goal is to recognize the irreplaceable value that music and artists give us by talent/soul and hard-work and donate these efforts fairly in this ever changing digital era of music distribution.

Author is currently working on a concept and plan of a music streaming platform built on the ‘Subscriber Share’ model and ‘listening-time based tracking’ principles. Looking for funds/investors to bring such a platform alive.