Technology and the internet have had a dramatic effect on society. Primarily, this is by making information (and communication) cheap, and explosively increasing the amount of each. In many ways, it has furthered inequalities, and for marketplace businesses, such as Uber, Air B&B, and Facebook, scale begets scale. If you want to sell your wares, you go to the market with the most buyers- and if you want to buy, you go to the market with the most sellers. A handful of giants then start to dominate, the simple fact of their size being a huge advantage in and of itself.
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By Alex White Head of ALM Research at Redington
However, as often, the effects are more nuanced than the simple narrative, and ironically a lot of the best data comes from one of the big winners, Spotify. The effect is likely to be true in other areas, but Spotify release a large amount of data through their “Loud and Clear” site, which has a lot of valuable insights. From this (and Wikipedia for Drake as the top earner) we get the table below.
Earning at least $X from Spotify Number of Users (earners) in 2022
The data is heavily skewed- on a log-log plot (from $1000 up), the fit is quadratic, so it’s not quite a power law, but it’s not miles off either. This provides some confidence that the minimum of each band is a sensible proxy for the median within that band.
There is also quite a high degree of uncertainty in interpretation (e.g., where most users sit within each band), but we can bound our results by the minimum and maximum of each range. That is, the top 40 earn at most Y% of the total, where Y assumes the top 40 all earn the top of their range and everyone else earns the bottom of theirs.
Top X users % of earnings (minimum of each band) % of earnings (maximum of each band) % of earnings (maximum %)
Now, 40 users accounting for 10% of earnings from 9 million users is staggering. Even if we limit it to users earning at least $1,000 (limiting to those trying to make money from it with some success), then 10% is earned by the top 0.02%. But what do we compare it against?
In a typical radio station, most of the music played will be the current top 40 songs. Let alone the top 1,000 artists, the top 1,000 songs will be the enormous majority of what’s played. And in a 90’s CD store, it would take a huge store to stock 1,000 artists. The data isn’t as good, but this seems a robust limit. The percentage of earnings attributed to the top 1,000 artists would probably be nearly 100%, as no-one below that threshold would even be sold in the shop.
This is a neat inversion. In a supposedly winner-takes-all (meta-)environment (competition between providers), one big advantage, accounting for around half of all earnings, is the long tail of musicians (in the underlying environment) who aren’t big winners. Small-scale musicians may well benefit from having a platform at all, certainly as against the CD model(1). And while this is hardly a great example of equality, it does suggest a more complex set of changes in the market.
(1) The story here may also be more complicated- Ludacris, for instance, famously sold his first album out of his car.
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