Many good points and good question about how people actually quit! I don’t know for sure how people quit, and this post mainly addresses the narrower case of a single video causing someone to quit immediately for some measurable amount of time. Two mechanisms being considered right now: people quit on one dramatic change, versus people incrementally update over time until they ease over the boundary of quitting. It would be cool to see surveys of people who quit and see if quitting is gradual or something suddenly clicks.
It would also be interesting to what extent YouTube can deduce what videos correlate with users quitting and punish them regardless of their immediate chain breaking. For example, YouTube could look at two batches of comparable viewers, half who saw a certain video and half who didn’t, and see how many are still viewing an hour, day, week, month, and year later. I suspect with enough data YouTube could find some connections.
Additionally, maybe YouTube could gather user leaving or use reduction stats by channel rather than viewer. That way YouTube could gain confidence that a certain channel rarely makes people leave, so YouTube can recommend the content quickly while it is still relevant.
As for ad free success, I’m not sure if it is the same for all users but I searched Scott the Woz and clicked on the first video and got a pre-roll video ad, then clicked a second video with no ad, then clicked on the next Scott video and got a sponsored ad below the video.
Thanks for all the great points, I suppose it’s time to start making additional predicted observations for these different directions and see!
Additionally, maybe YouTube could gather user leaving or use reduction stats by channel rather than viewer.
Wow. Diabolical. I have never thought of this. Grateful to have this pointed out to me.
I searched Scott the Woz and clicked on the first video and got a pre-roll video ad
Actually, that makes sense. I’m making a prediction, that if I check the first Scott video when I search his name, the description will say something like “This video contains copyrighted content from XYZ-Corp and has been claimed”. Going to check that now… Nope. Incorrect prediction. I was wrong there.
I know that I get that message, in my video descriptions, when I have copyrighted content in the video. Checking that now. And wow! This part of the description has gotten some pretty insane updates since I last looked at it.
This is in the description for a video in which I reviewed 10+ different movies. The owners of those songs have put claims on this video. and they-at least, used to-run ads on this un-monetized video.
It would be cool to see surveys of people who quit and see if quitting is gradual or something suddenly clicks.
I started writing a post on this, and collecting some data. But have now realized it’s a much bigger project than I anticipated. But I agree that this would be interesting data.
Many good points and good question about how people actually quit! I don’t know for sure how people quit, and this post mainly addresses the narrower case of a single video causing someone to quit immediately for some measurable amount of time. Two mechanisms being considered right now: people quit on one dramatic change, versus people incrementally update over time until they ease over the boundary of quitting. It would be cool to see surveys of people who quit and see if quitting is gradual or something suddenly clicks.
It would also be interesting to what extent YouTube can deduce what videos correlate with users quitting and punish them regardless of their immediate chain breaking. For example, YouTube could look at two batches of comparable viewers, half who saw a certain video and half who didn’t, and see how many are still viewing an hour, day, week, month, and year later. I suspect with enough data YouTube could find some connections.
Additionally, maybe YouTube could gather user leaving or use reduction stats by channel rather than viewer. That way YouTube could gain confidence that a certain channel rarely makes people leave, so YouTube can recommend the content quickly while it is still relevant.
As for ad free success, I’m not sure if it is the same for all users but I searched Scott the Woz and clicked on the first video and got a pre-roll video ad, then clicked a second video with no ad, then clicked on the next Scott video and got a sponsored ad below the video.
Thanks for all the great points, I suppose it’s time to start making additional predicted observations for these different directions and see!
Wow. Diabolical. I have never thought of this. Grateful to have this pointed out to me.
Actually, that makes sense. I’m making a prediction, that if I check the first Scott video when I search his name, the description will say something like “This video contains copyrighted content from XYZ-Corp and has been claimed”. Going to check that now… Nope. Incorrect prediction. I was wrong there.
I know that I get that message, in my video descriptions, when I have copyrighted content in the video. Checking that now. And wow! This part of the description has gotten some pretty insane updates since I last looked at it.
This is in the description for a video in which I reviewed 10+ different movies. The owners of those songs have put claims on this video. and they-at least, used to-run ads on this un-monetized video.
I started writing a post on this, and collecting some data. But have now realized it’s a much bigger project than I anticipated. But I agree that this would be interesting data.