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The linked story is from a year ago. I actually run a YouTube statistics site called SocialBlade which one of the things it provides is estimated earnings of everyone, be them partners or not meaning if they do become a partner they can see how much they could make. It's based on some data from this story and also feedback from many many partners so its more or less accurate.

I am currently as of this post using an estimated cpm of 0.75 to 8.0 (ads have gone up dramatically in september). The cpm that partners will see vary greatly depending on what types of ads they use (prerolls pay way more for example) and where their viewers are (us pays way more then canada for example) but this range seems to be on par for most people.

Regarding what people are saying about partners dismissing the linked story, that was true, but they dismissed it because they said they made 3x more then it back in aug 2010.

Check out my site if you want to see updated estimations :)

http://SocialBlade.com/youtube



Thanks, that's a useful site. An order of magnitude range for the earnings estimates is quite large. Can you not narrow that down using ad type data?


That's not a bad idea. Possibly in the future I'll see if I can incorporate this into the estimates but remember its also again based largely on the location of ones viewers. If you're from the US and your viewing audience is 99% from Canada you'll have a lower payout then the opposite. Same is even more dramatic with other countries. That type of data I'm not able to get.

[Edit] As a general rule of thumb though, the higher up partners are generally making closer to the higher range, and the lower end ones are making closer to the lower end of the range.


Adding some kind of confidence bound or estimated probability distribution might make more sense of the huge ranges. You're already computing the 'height' of partners, so you could potentially incorporate that into the model.

Something like "$100 - $1000, best-guess $500 ± 200"




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