- Wait, stop what you're about to do.
I know, instinctively,
you want to tap that thumbs up button.
Well, don't do it just yet.
(upbeat music)
Now, then.
Hey folks, I'm Rob, welcome back to vidIQ,
educating you on your YouTube journey.
And today's lesson is all about
getting discovered on YouTube.
This is one of the things that many creators complain about
YouTube not giving their content a fair shot,
especially smaller creators.
Well, the truth is it's probably not YouTube's fault.
It's likely your fault because you've got a backwards way
of thinking about the YouTube algorithms.
Yeah, we're using that term again.
In short, YouTube isn't here for the benefit of the creator.
It's here for you, the viewer.
That's why you're watching this video right now.
Thanks to YouTube recommendation system.
Now then, full disclosure, the source of truth,
for this video comes directly from YouTube
and the creator insider team,
just published eight phenomenal video
all about the discovery engine.
So that's well worth checking out, as well,
pretty much riffing on their information.
All righty then, let's get you in the right frame of mind
for this lesson.
You do not need to be an experts in algorithms,
nor do you need to be a data scientist,
but what you do need to understand is your target audience,
and the intent of a viewer within that target audience.
And let's try and get away from the idea of an algorithm,
because YouTube have already given
this collection of AI a name,
and that is the recommendation system.
The goal of this recommendation system is to
help viewers find content they want to watch,
and maximize their long-term satisfaction.
And to understand all of this a little bit more,
it's time for a brief history lesson.
(snaps finger)
YouTube's recommendation system has evolved greatly
over the last decade, but it hasn't significantly changed
in the last five years, although it has got a lot smarter
and a lot more sophisticated, but in the beginning
YouTube needed to fix an obvious major threat: clickbait.
And after a decade of tackling this issue
I'll say what I've said before clickbait on the whole,
doesn't work on YouTube anymore.
Remember that when you are researching another channel
and looking at their thumbnails and titles,
you're likely doing so as a creator,
rather than a viewer.
Thumbnails and titles can only be considered clickbait
if they do not deliver
on their perceived promise for their intended audience.
So if a video has a million views
and you hate it, well, guess what?
The video probably wasn't intended for you.
Now, of course we all know the importance of watch time.
The longer a viewer is on the platform,
the more hours YouTube can serve it to them.
So if you can pull a viewer into one
of those content rabbit holes, you'll be rewarded for it.
But what you may not be familiar with is quality watch time
because it's not enough for someone to just watch a video.
YouTube wants the viewer to be satisfied by that video,
whatever that means in a safer work context.
And this is where we reach an important pivot point
in this video.
And it's gonna blow your mind a little bit.
Not all watch time on YouTube is treated equal.
(popping noise)
So how on earth do you measure the quality of watch time?
Well, one way YouTube occasionally do this,
is through viewer satisfaction surveys.
But these don't appear on every single video.
All of this stuff on the other hand, does.
So yes, YouTube is clarifying right here
that all of these data signals can contribute to the success
of a video, but is it even more sophisticated than that?
Now let me be clear here.
I'm just floating a theory.
This does not come directly from YouTube,
but do all of these data points
only rely on if they are used.
What about when they aren't used?
Let me give you a quick example.
In the first five minutes of us launching a video
we always get a comment that says
that the video has more likes than views.
And this is because at the very beginning,
many viewers instinctively like the video
which is why I asked you not to like this video.
And through a decades worth of data,
YouTube probably knows this.
My guess is if likes are more progressively spread out
across a video, that is a clearer indication
of viewer satisfaction rather than viewer channel loyalty.
And with all of that being said, you have my permission.
Now again, let me stress.
That was just my theory.
But I believe that's the level of sophistication
that YouTube discovery recommendation engine is working out.
Consider how satisfied you are
as a viewer to use this button.
You don't share things with friends and family
unless you think they'll be satisfied
by the same experience too.
This button allows YouTube's recommendation engine
to become biological, psychological, and more likely viral.
Now, again, that's my theory,
but YouTube did tease some interesting information
about engagement on your video.
- We are looking at adding more satisfaction data
and externalizing it to creators.
So it is something we're working on.
Oh, there's nothing that satisfies me more
of a new YouTube analytics, yeah.
It seems clear then that YouTube are digging deep
into engagement signals to determine
whether or not videos satisfy viewers.
And when they do YouTube makes them more discoverable.
But the question remains how and where are they discovered?
Well, it's no secret that for most channels,
home or browse features
and suggested videos are the top traffic sources.
But that's not always the case.
Different channels will attract different viewers
in different ways, depending on the intent of the viewer.
It's your job as the creator to identify the type of viewer
that's likely to watch your content.
Once you have an idea of who that viewer is,
or your target audience, to use another phrase.
Consider this, what is that new viewer going to do
when they're first exposed to some of your content
through a thumbnail, and a title, on a homepage.
This can be a tough question to answer.
Which is why a vidIQ has this handy thumbnail preview tool.
It will not only show you
how your videos compare to the highest rank videos
for a search term, but also what it may look like
on a home browse page against random videos.
The real power of this tool is that it can show you all
of this before you even publish the video.
Now, we do have to remember
that the homepage is personalized to the viewer,
and that will depend on how much a viewer
watches a channel or a topic over time.
Now, topic is an interesting one word to use
because that relates back to keyword research.
Keyword research allows you to become intimate
with the language used in your video topic.
And once you know this, you can ensure that it is prevalent
throughout your video.
Be it in the thumbnail, the title, even the metadata.
All of this will not only help YouTube understand
what your video content is about,
but guarantee that your viewer knows they're
in the right place.
And the happy offshoot of all of this, of course,
is that fingers crossed,
your videos will rank higher in search.
All of this, of course, vidIQ can help you with
through our keyword research tools
that you see on screen now.
Also try to remember that the homepage
represents the beginning of a viewing session on YouTube,
although the page is personalized for the viewer,
they might not yet have decided
what they want to watch first.
And that's where you come in.
Consistency is the key here.
Try to bring that viewer
as much fresh content as frequently as possible.
The last thing a viewer wants to see is a thumbnail
of a video that they've already seen.
Unless they really enjoyed it and want to watch it again.
Ideal publishing cadency can vary greatly
from topic to topic, but the general rule
of thumb is that you should try
and release a video at least once a week.
And at most once a day.
Being discovered and suggested is a little more nuanced.
Now that at least one video has been watched.
YouTube has a little more data about the intent
of a viewer for that particular watch session.
If you're watching this video,
you're probably in a education mood
and you want to learn more about growing your channel.
If you're watching reviews on a particular camera,
then you're in a purchasing decision mood.
And so YouTube is going to find more reviews
and opinions about the products you're watching.
(upbeat music)
As an example, this is a video we made
about the copyright matching tool on the suggested column,
on the right hand side,
there is another vidIQ video about copyright claims,
as well as a video about how to apply
for monetization on YouTube
which would be considered a related topic.
Having YouTube suggests more of your content
within your own content is the ultimate watch
session feedback loop.
And it can be achieved through creating a video series
with a through line of consistency in titles and thumbnails.
Now, once the viewer is within your video,
try not to let them leave.
Don't give YouTube the opportunity to suggest
something else.
This can be done through calls to action
that encourage your viewers to watch related content.
And they're delivered through playlists, interactive cards,
and end screens over here where you can learn more
about keyword research and more about making those
thumbnails that are gonna get those clicks.
Did you see what I did there?
Thank you, bye.