CSPC: Drake Popularity Analysis

Drake

Digital Singles Sales – Part 2

As a reminder, the weighting is done with a 10 to 1,5 ratio between one album and one digital single.

Nothing Was the Same (2013) – 1,883,000 equivalent albums

Started from the Bottom – 3,200,000
Hold On, We’re Going Home – 4,450,000
All Me – 1,300,000
The Language – 700,000
Remaining tracks – 2,900,000

If You’re Reading This It’s Too Late (2015) – 585,000 equivalent albums

Energy – 1,025,000
Know Yourself – 600,000
Legend – 525,000
10 Bands – 400,000
Remaining tracks – 1,350,000

What A Time To Live In (2015) – 390,000 equivalent albums

Jumpman – 1,600,000
Big Rings – 500,000
Remaining tracks – 500,000

This intermediate period wasn’t well structured around one specific album. By 2013 Drake had understood already that the whole concept of album was dying. As a result, he started dropping mixtapes at fast pace, plus tons of collaborations that we will see on following page. Hold On, We’re Going Home is the biggest hit of that period extracted from those studio albums.

5 thoughts on “CSPC: Drake Popularity Analysis”

  1. Hi MJD!

    Nice analysis as always, but I have 1 main question concerning how you calculate streaming equivalent sales, particularly audio streams.

    Your method of calculating audio streaming equivalent sales of records is by multiplying the cumalative streams on Spotify with the ratio between the total audio market and Spotify in the current year, and finally dividing it by 1500.However, one problem I see is this: the growing share of Spotify among streaming platforms, hence a much smaller ratio for each year.

    For older acts (eg. Beatles), their streams increase at a relatively slow pace. If we were to multiply their cumalative streams with an updated ratio, their streaming equivalent sales will undoubtedly be lower every year as the ratio keeps getting smaller and smaller.

    However, this doesn’t concerns those acts as much as acts of today that achieve huge streaming (eg. Drake) While streaming only takes up a small percentage of the total CSPC total for the former, the latter is the total opposite, with some acts total CSPC sales having more than half coming from streaming. What’s more, with a dying market of album sales and downloads, these newer acts heavily rely on streaming to generate catalog “sales”. If the records of these acts don’t increase in streams at a certain pace on Spotify, then using a decreasing ratio every year will cause their totals to will remain more or less the same, perhaps even lower. Hence the concept of catalog sales is meaningless to them.

    What I suggest doing is to multiply the streams of a record it achieved on Spotify during a year with the ratio of that particular year, and using the updated ratio for another year on the Spotify streams it achieved for that year. For example, let’s say that an album achieved 500 million streams and 200 million streams for 2019 and 2020 respectively, while the share of Spotify among all audio streaming platforms is 40% and 50% respectively. What I suggest is to calculate like this: ((500m*100/40)+(200m*100/50))/1500= (1,25B+400m)/1500=1,1m audio streaming equivalents for 2019 and 2020

    Of course, this is only a suggestion. Tell me your thoughts on this. If you were to use this formula I proposed, the only real problem is to keep a large database that shows how many streams an album generated each year and the share of Spotify among all audio streaming platforms each year as well.

    1. Hi Raffi!

      The main error on the old formula for streams was the paid users vs total users confusion. The formula was using the percentage of paid users of streaming services that were using Spotify as there was no data on IFPI report for free users. The problem is that paid-only platforms appeared, creating a very different share of “paid users” and “free users” using Spotify. The formula used the share of paid users, while counts of streams were built by all users combined.

      Now that this is fixed and that each streaming platform took its place, I’m not expecting notable changes. For nearly 1 year now, Spotify goes up and down between 62% and 64% of the overall market, this is quite stable at the moment. The ratio is someway wrong for years 2012/2014, but the impact is minimal there. As noted on updates, the artists roughly doubled their streams during the last 10-11 months, e.g. last 2 years represent a good 80% of the total streams to date of an artist. If the formula deflates an artist results for pre-2015 years by 20% for example, that would be 20% out of 20%, an error around 4%, a percentage that gets smaller every week of new streams which lower even more the importance of ‘old’ streams.

      Obviously, if a new change of policy, for example Spotify going premium only, changes the share of all services, the formula will be adjusted. I do not exclude the possibility of ‘dating’ streams as you mention to apply the most relevant formula for each stream. I stay optimistic there though about shares staying flat during the next months/years!

  2. Hi, I just noticed for Drake all his features sales/streams are given to him 100%. Why is this?

    It doesn’t seem to make sense to give a feature 100% of a song’s sales/streams, even if they were on the song for 5 seconds. Janelle Monae shouldn’t receive 100% of We Are Young’s sales/streams.

    You also made the formula for video streams 11,754 = 1 album versus 1,500 = 1 album for audio streams, the reasoning being that video streams pay much less than audio.

    An artist gets paid much less of a fraction from features than as lead artist, so shouldn’t they receive a fraction of the sales/streams from features?

    1. Hi Anon!

      The case of features is definitely a tricky one. To be honest, I don’t like the 100% attribution that much, but I can’t see a better solution. I don’t like using a fraction, say 50%, for two reasons: 1/ it is artificial, 2/ not all features are as relevant. Many blame Rihanna due to her numerous featurings, but on most of them she has a role at least as big as the lead singer. In the other side, someone like T-Pain or Nate Dogg were never the #1 singer of a song, Quavo seems to be following the same road.

      For this reason, I can’t fix a frozen percentage. I also can’t dictate a distinct share for each feature as 1/ it wouldn’t be valid, 2/ that would imply to listen / gauge each and every song for each artist. That’s not possible.

      It must be said that I took that decision when starting the first CSPC article with Rihanna and having in mind that I would study mostly major artists that are also pretty relevant to the songs on which they contribute. If tomorrow I work on Lil Jon, I’ll most likely build an appendix to the concept to avoid getting a flawed total due to unweighted featurings!

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