- In this video, I'm gonna show you
how to beat the YouTube algorithm in 2022,
I'm gonna show you draw dropping graphs,
I'm gonna show you data that's never been seen before.
I'm gonna reveal the algorithm secrets
as told by YouTube themselves.
And if you watch this video to its conclusion,
I guarantee you, it will fundamentally change
the way you think about the YouTube algorithm.
It's pretty exciting, isn't it?
Say hello to Todd, he works at YouTube
and is an expert in search and discovery.
If you've ever watched the Creator Insider the channel
which you really should, he often pops up on there
to remind us that the algorithm isn't against you.
Spoiler alert, it is.
And Todd at recently took his wealth of knowledge and data
into the conferencing circuit.
Here he is talking at VidSummit
and he had some fascinating insights to share.
So just before we jump into this, I'm curious to know
if you could ask Todd one question
about the YouTube algorithm what would it be?
let us know in the comments below.
Haven't asked you but,
I know there's only one thing you're interested in right now
that graph I teased a little earlier on.
Watch time, let's take a look.
What is good audience retention on YouTube videos?
Well, here we have it.
For a three minute video,
the average view duration is 62%
for a 30 minute video it's half at just 31%.
Now I thought that YouTube
we're trying to avoid these types of global benchmarking
because ultimately it just gives creators a stick
to prod YouTube with when their expectations are not met.
Let's say for example that I had a 50 minute video
with a 45% average view duration that doesn't take off.
That will be jolly annoying, wouldn't it?
Or on the flip side, you have a video
with very mediocre audience retention
that would put it around about here on the graph
and yet it blows up performing well beyond typical.
Of course, that isn't annoying in the slightest,
you want it to happen,
but at the same time you're left scratching your head
figuring out how it happened.
This might help explain it a little bit.
Watch time for the video
was above typical right out of the gate.
So YouTube tested a video with new viewers
who aren't as invested in your content
and that lowers the average view duration.
Relative audience retention is pretty strong too,
but this is just one example
up against the millions of videos that make up this data.
So if you do want to match up your audience retention
with the rest of YouTube, now's your chance.
Although having looked at all of this,
there is one big data point
that's missing from this graph, YouTube Shorts.
Now full disclaimer, this is not official YouTube data
but this is where I think YouTube Shorts
would probably end up on that graph.
Perfect.
Should probably give this back to Jasper.
Go on Jasper, take it, go on.
It's yours.
Clearly haven't figured out the dog algorithm have I.
When it comes to YouTube is pretty much impossible
to take one single number from the analytics
and extrapolate success or failure,
and watch time is no different.
And that's because, according to the YouTube algorithm,
not all watch time is considered equal.
Sometimes a viewer can watch 30 minutes of content
on YouTube and come away from it
not feeling very satisfied.
And if that is the case, it could lead to that person,
not using YouTube for a couple of days
and opting for TikTok or Instagram reels instead,
and that is what YouTube hates.
They're in it for the long game.
YouTube's algorithm, wants viewers to be satisfied
by what they watch today, tomorrow, next week,
next month, next year, next decade.
So watch time simply isn't enough by itself.
YouTube needs to measure the value
and satisfaction of a watch time,
and they do that with many other signals.
If you wanna dive into this small,
we've got a whole video over here.
But what Todd specifically mentioned in his conference talk
was the idea of transformational experiences.
YouTube can do this because it measures
80 billion different signals, whatever that means.
And when a video successfully transforms
a viewing experience in a positive way,
the algorithm wants to amplify that.
So yeah, let's talk about that a little bit.
Does YouTube give your video a fair chance to be discovered?
Well, according to Todd at YouTube,
over 600 million different videos
are recommended every day on the homepage
and through suggested videos.
Now that sounds like a really
incredibly impressive number on the face of it,
but is it really?
I genuinely don't know.
For me, this statistic lacks a little bit of context
since there are over 2 billion monthly users on YouTube.
I don't know if this includes all languages,
there are millions of new videos published every single day,
and yet I can still be recommended one from 10 years ago.
So 600 million, I don't know.
So let's try and add a little bit of context of that,
and this is something that Todd said about viewers.
The history of what a user has watched
is the most valuable thing
that the YouTube algorithm can understand.
That's because a viewer's recommendations,
what they see on the homepage, up next,
suggested videos are highly influenced by personalization,
what YouTube knows about the viewer.
So let me give you my personal experience of this.
I don't know about you, but I have multiple interests
and when I'm on YouTube,
I tend to associate different channels
with each one of those interests.
I religiously watch MKBHD for tech stuff.
I watch the channel called Wrestling Bios
for 1990s wrestling stuff.
And I watch Oliver Harper
for anything to do with film retrospectives and reviews.
Now because I watch these channels so regularly,
at least once a week,
these channels frequently appear on my homepage,
even though I'm not subscribed to two of them,
I gave up subscribing to channels years ago,
YouTube has all of the signals it needs,
doesn't need this one anymore, hasn't needed it for years.
Now, if one of those channels covered all of those topics,
would I just watch that one channel?
I don't think so.
Their styles, personalities, and formats match their topics.
So as usual, in some respects this goes back
to channel focus and becoming the best creator
for a certain niche and target audience on YouTube.
I have a deep passion for YouTube, tech, wrestling, films,
but what do you come here to watch?
None of the other stuff.
And when you come to the vidIQ channel
and really enjoy a video about YouTube education,
what do you really want to watch next from us?
And that leads us onto another
really insightful data point from Todd.
If 100 people watch your video this week,
700 potential viewers will see your thumbnails
the following week.
Or to put it another way, that every view you earn
YouTube gives you on average seven more opportunities
to gain another view.
This is basically YouTube's
advertising budget for your content.
And with some back of a napkin maths,
we can take the views from one week
and the impressions from the following week to get a ratio.
And it looks like YouTube is even more generous than average
with its content advertising budget for the vidIQ channel.
However, just like all of the other numbers,
there's a really critical human element behind the data.
YouTube isn't giving you seven random opportunities.
It's been really selective with which viewers
they put your thumbnails in front of.
I'm sure you've all seen this shelf before
when shopping on Amazon.
What else customers buy after viewing an item?
Amazon knows that if you intend to buy a Spiderman mask,
you probably want to buy over Marvel collectibles as well.
I mean, hello, I have a thousand dollars
worth of Amazon influenced decision
that's sitting on my shelves
and well, YouTube is pretty much the same,
but just a little more subtle about it.
Everything on this YouTube homepage
is driven by personalization.
Not only from the creators I watch on a regular basis
but by the content YouTube knows over viewers tend to watch
even if I myself have never seen them before.
Every time that somebody watches one of your videos
and then they watch a nother one of your videos
or a suggested video by YouTube
after watching one of your videos,
that strengthens the relationship between similar videos.
Which makes session watch time, average views per viewers,
and this panel on the YouTube studio,
which shows you what your viewers
are watching elsewhere on YouTube all the more critical.
You might call this passive collaboration
with other creators,
but at the same time you end up competing with them,
which means that your titles
and thumbnails are super important,
which leads on to click-through rate.
Unfortunately, Todd wasn't able to provide
any clutch information about click-through rate,
but there's good reason for that.
It's a constantly evolving fluid piece of data<
very hard to measure, very hard to calculate.
As I demonstrated in this video.
In the past that YouTube's algorithm has only been explained
through insane diagrams such as this.
So I want to thank Todd in his efforts
to make this type of stuff more approachable for creators.
But how does all of this fundamentally change
the way you think about the YouTube algorithm?
Well, here's the simple answer.
The algorithm is less to do with numbers
and more to do with people.
In Todd's own words, "What the algorithm is designed to do
"is follow that audience and make them happy."
And that is what Todd YouTube and myself recommend you do,
replace the word algorithm with audience.
You came into this video wanting to know
how to beat the YouTube algorithm.
well, I hope you're leaving this video wanting to know
how to beat the YouTube audience,
no that doesn't sound right, does it?
How to build a YouTube audience.
And you can start doing that by removing
these three rookie YouTube mistakes that everybody makes
by watching this video over here.