96% of YouTubers don’t know THIS about YouTube Ranking

96% of YouTubers don’t know THIS about YouTube Ranking play video
Written by: Dexxter Clark
How YouTube ranks videos actually starts when you upload your video.
You know it says processing? …

First of all downscales your video to lower resolutions.
And second, it also analyzes your video:
1) It looks at objects and text in the video
2) it looks at video chapter names
3) it looks at the speech of your video.
4) it looks at the text in your title and thumbnail

Based in this, it generates meta-data, let’s call it “internal search labels” for now.

Based on these search labels it determines the topic of the video and therefore for a large part, the initial audience that might be interested in the video.

And this is a guess, but I think, once it has the topic it looks at topicly related videos and their labels and adds the most likely ones to your video.
This would explain how you can rank for keywords that aren’t even IN your video, but are in others.

What happens when you release a video
[google paper]
According to this paper about “How YouTube ranking works”, that I heavily used to research this video, A.I. is biased towards the past to predict the future.

Because over-time an A.I. model (which is your video) is trained with more and more data and therefore becomes more reliable because has more data about the right audience for the video.

7. [screenrec]
This is literallly what you can see in your YouTube Analytics: the line of views is gradually climbing up because YouTube starts to promote a video more over time because it has more data on who to serve it to.
This is Youtube literally training the A.I. model of your video for weeks.

How does YouTube train models for the Ranking?
The Search labels that I talked about earlier, come into play.
The algo starts to estimate which labels are the most important and starts testing each of them on actual human beings when you release the video.
The bigger the channel is, the more labels it tests on a bigger audience.

For each of these labels it looks how the viewer satisfaction is.
It looks at CTR of a video, AVD , APV, engagement and a couple of other things.

This is what everybody misunderstands about CTR and APV, it is extremely relative to the competition for that specific video, that specific topic, for that specific video length, for that specific audience with that specific age and 10 other specific things.
For example: when the algorithm starts testing on the wrong audience your CTR takes a nose dive, that doesn’t nessesarily mean that your thumbnail or video topic is bad.
Which makes especially comparing CTRs between videos extremely unreliable.

[broll apv data yt]
Average Percentage Viewed it is more reliable when you consider video length because (unlike CTR) each traffic source is counted.
YouTube recently gave us some APV numbers to shoot for, which you can see here on the screen.
But remember, this is an average over all of YouTube over all niches and all topics.

This way of Ranking is Flawed
You might have spotted a flaw in how youtube ranks videos in my previous explaination.
If A.I. thinks that older is better, because of more data, that would mean that the algorithm would only serve old videos.

And when it would only serve old videos, it doesn’t get data to train the models of new videos.
That’s the chicken or the egg problem.

To break this vicious circle, YouTube thought of something brilliant.
YouTube gives videos an enormous kick in the ass on release by serving it to a “large” audience for the first few days.
The bigger your channel, the larger the audience.

Which instantly makes content freshness a ranking factor.

This is the spike that you always see in your YouTube Analytics when you release a video.

By doing this, YouTube can gather data on CTR, AVD etc to establish a baseline or future promotion.

Bigger, bigger audience
[bord uitleg]
On release , YouTube starts testing the usual suspects for viewer satisfaction: AVD, APV, CTR, engagement and the rest.
It starts small with your subscribers, then your regular viewers, less regular viewers, similar viewers, viewers that shown interest in the topic in the past etc etc
Every time viewer satisfaction for a group is good, it promotes it to the next group.
This is why you see these stages in your views graph on a viral hit.
[broll: 2i2 video januari 2019]

Until it reaches a group of people that is not interested.

What happens with small channels, the ranking algorithm quickly runs into a group of viewers that is not interested because it doesn’t test much.
This is why momentum so important for small channels. [broll: youtube dashboard ranking ]
IF you can hit the number 1,2,3 positions in your ranking in YouTube dashboard consistently, you get a little bit more tests the next time and thus a bit more promotion by the algorithm.

On release your regular audience and similar viewers get a notification on their home screen or suggested and in YouTube Search the algorithm preliminary ranks you in between large channels.

[broll: ranking no 3]
This is a screenshot of my previous video ranking on position #3 on a pretty competitive search term right after release.

You ACTUALLY RANK in between the big guys, isn’t that bizarre.
THIS is YOUR chance to prove to the algorithm that YOUR video is better than all the others.

[broll: recording]
If you blow it … and I think 99% of creators do blow it (otherwise you would have had a viral hit), you start to go down the rankings after a few hours, like in my case,
It’s my content, not the fault of the algorithm.
If viewers would react overwhelmingly positive it would have promoted the video further.

The bigger your channel is, the more and higher it initially ranks you and tests with more search labels.
And thus a bigger the chance that it finds the RIGHT audience and therefore increases the chances of a viral hit.

25 [screenrec]
But you get actually a second chance. Remember that I said that A.I. favors age because it has more data over time?
With this video right here on my dj channel from 4 months ago [best daw 2021] started out also ranking between good and took a nosedive in the rankings.
But slowly it started to crawl up.
And I suspect that I’m going to surpass this dude, because I have a reason to click in my thumbnail, so probably my CTR is higher and the watchtime of this video is ridicously good, probably better than his.

[screenrec: 2i2 vid]
And it can even take longer. Let’s take a look at my “viral” hit.
It takes 9 months for it to properly rank and completely to blow up.
You can see the testing stages ,and the finding of the right audience, really good when you look at these spikes and dips.

Can you explain how YouTube ranks videos?
Some creators try to explain why and how YouTube ranks videos by looking at granular details of a video like a relationship between CTR and impressions for examplae

But that will never work, because
1) you don’t have all the data points that the algorithm has (remember, YouTube is pretty secretive)

2) when you have only a 500 views, your video model is trained with too little data about audience for the YouTube algorithm to promote it.
Normally A.I. models are trained with 10 thousands of samples to make them reliable.

How YouTube ranking works for the viewer
Until now I’ve talked out of the perspective of the creator, because it’s easier to understand what’s happening, but actually it is the other way around.
It works from the perspective of the viewer.

When a viewer opens the YouTube Home or types in a Search query, YouTube ranking works in 2 stages.
1) candidate generation
2) the actual ranking

But I’ll leave that for this video right here, in which I talk about why keywords don’t rank you.

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photo author dexxter clark
Dexxter Clark
Music Producer / YouTuber

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