Big Idea

The argument in one line.

YouTube pushes videos based on relevance, not quality: a broad, undisqualifiable title and opening combined with high watch time per impression (click-through rate times average view duration) is what keeps a video getting recommended.

Who This Is For

Read if. Skip if.

READ IF YOU ARE…

A YouTube creator at any subscriber count whose videos look well-produced but still stall on recommendations.
Someone using highly specific title and thumbnail formulas who wants to understand why narrow targeting can backfire.
A creator willing to test longer video lengths and AI-assisted audience research before locking a title.

SKIP IF…

You're optimizing for a platform other than YouTube's recommendation algorithm, since TikTok and Reels distribution work differently.
You already rely on an owned audience like an email list or podcast feed and don't depend on algorithmic discovery.

TL;DR

The full version, fast.

Brian G. Johnson breaks down why some videos suddenly get pushed by YouTube's algorithm even when their audience retention looks weak. The mechanism is relevance: every narrow, over-specific title or topic silently disqualifies chunks of a potential audience before they ever click, so the fix is designing the first one to two minutes of a video to feel broad before narrowing to a specific point. The real signal YouTube tracks isn't retention percentage alone, it's watch time per impression: click-through rate multiplied by average view duration. A longer video can win with a lower retention percentage because the raw minutes watched still go up. He also uses AI chat tools to sketch target-audience profiles and pressure-test titles before publishing.

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Chapters

Where the time goes.

00:00 – 01:40

01 · A video that shouldn't be working

17,000 views three days after publish despite unremarkable watch-time metrics; teases the 'wave strategy' behind it.

01:40 – 04:23

02 · Relevance decides everything

The single word that matters is 'relevant.' Picture the target viewer clearly, and understand that YouTube serves a video to people it thinks will care.

04:23 – 06:23

03 · The 100,000-person test

A narrow title like 'run 10 miles a day to lose weight' disqualifies most of a potential 100,000-person audience; design a broad entry point before narrowing.

06:23 – 10:03

04 · The algorithm chains your videos together

Once one video gets recommended and watched, YouTube often serves the same viewer a second video from the channel; only 2-3 of every 10 uploads carry a channel.

10:03 – 13:08

05 · Watch time per impression is the real signal

CTR times average view duration beats retention percentage alone; a longer video can win with lower retention because total minutes watched still climb.

Atomic Insights

Lines worth screenshotting.

A video can get recommended by YouTube even with mediocre audience retention if its topic disqualifies almost no one.
Every narrow, hyper-specific title silently excludes a chunk of the potential audience before anyone even clicks.
The viewer's real question isn't 'is this good,' it's 'is this for me,' and a title answers that in under a second.
A title built around running 10 miles a day to lose weight disqualifies everyone who isn't already a serious runner.
Design the first one to two minutes of a video to be broad enough for almost anyone, then narrow to the specific point.
Once an algorithm successfully pushes one video from a channel, it often follows up by recommending a second video from that same channel to the same viewer.
On a typical channel, only two to three videos out of every ten uploads end up carrying the channel's growth.
Watch time per impression, click-through rate multiplied by average view duration, is a clearer satisfaction signal than retention percentage alone.
A 10-minute video needs 50% retention to hit a 5-minute average view duration; a 20-minute video needs only 30% retention to beat that at 6 minutes.
YouTube keeps viewers watching longer because more watch time means more ad inventory and more revenue for the platform.

Takeaway

Relevance Beats Retention on YouTube

WHAT TO LEARN

YouTube's algorithm keeps pushing a video less for its quality than for how few viewers a title and opening manage to disqualify, measured through watch time per impression.

A title or topic answers 'is this for me?' in under a second, and any narrow framing silently excludes viewers before they ever click.
Picture the broadest version of your target audience before writing a title, then design the opening one to two minutes to speak to all of them before narrowing to your specific point.
Watch time per impression, click-through rate multiplied by average view duration, matters more than retention percentage alone.
A longer video can win with lower retention: a 20-minute video at 30% retention beats a 10-minute video at 50% retention on total minutes watched.
Once YouTube successfully recommends one video from a channel, it often follows with a second video from that same channel to the same viewer.
Across any ten uploads, expect only two or three to actually carry a channel's growth, and treat that as normal rather than a failure signal.
Use an AI chat tool to sketch out who your target viewer actually is and to pressure-test whether a title or topic reads as broad or disqualifying.
YouTube optimizes for watch time because more minutes watched means more ad inventory, so anything that extends average view duration works in a creator's favor.

Glossary

Terms worth knowing.

Watch time per impression: A satisfaction metric combining click-through rate and average view duration; it measures how many total minutes a video earns for every time YouTube shows it to a potential viewer.
Disqualification: The moment a title, topic, or thumbnail tells a viewer 'this isn't for me,' causing them to scroll past without clicking, even if they would have enjoyed the video.
Entry point: The opening one to two minutes of a video, which determines how broad or narrow an audience the video can hold onto before narrowing into its specific point.
Average view duration (AVD): The average length of time viewers spend watching a video, usually reported in minutes and seconds.

The Script

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If you're struggling, if nothing seems to work, the easiest way, in my opinion, like what I've discovered, the thing that's changed my channel, finally getting views, is to really focus on getting recommended and this is a great example. Now this video was published past two days. We're past the two day point.

I'm into day three and you can see 17 ,000 views. And what's really weird is that the metrics, we're gonna talk about this, they're not really that great. The watch time, not really that great, but something is happening based on kind of this new workflow that I want to break down.

And it's based on, if you watch some of my previous videos, what I call the wave strategy. Now, here's what's really cool. This has had a huge impact on my ability to get videos recommended, drive views, and grow.

And now subscribers, people to the channel, they're like, this absolutely works. really good stuff. But the thing that is really hard for me to watch is so many channels are absolutely being rejected, disqualified.

And that's what we're going to talk about as we move forward. Because really, like, here's what happens is we make a video, we publish the video, the title, the topic, the thumbnail. But more than that, how we set up the first minute to two minutes in a video is literally make or break.

And so many videos end up getting disqualified. And you can see here, I didn't have this strategy figured out until recently, and my results were horrible. Losing subscribers, driving hardly any views, it was absolutely a mess.

And the process is based on one single word, and that word is relevant. Now sadly, my videos were not relevant. And the word I like is appropriate.

Followed by for me now think about like the audience that you want to get in front of and picture What those people look like in the clearer you can understand who they are What they're about what drives them the better now if you're like, I'm just not sure I get it But again, we're gonna tailor this for you. I'm gonna give you some prompts that you can use with Claude with GPT with Free Ask Studio to understand the type of audience and more than that, to figure out the angle of your video.

Let's just keep moving forward here. But the thing is, is it's gotta be about the individual viewer because when we publish a video, the algorithm grabs it, sends it out, thinks, okay, I think these viewers would be interested. But sadly, the title in the topic will create a disqualification for so many viewers.

And until I understood how this worked, I was absolutely doomed, disqualified. And the reason why is the viewer is, again, is it for me? What is this video going to do for me?

And until I really figured this out, I was stuck in the water. There are so many ways that someone will disqualify a video. For example, this is kind of.

one of the big ones. What will this require? For example, diet and weight loss.

How do we do it? Eat less, exercise more. Simple.

So imagine a video title that's like, all you need to do is run 10 miles a day, six days a week, and you'll lose weight. Well, no kidding. But you just disqualified a huge percentage of the audience.

And every time I used to make a video in the past, they were so specific. And they only appeal to a very small slice of the audience. And when I say slice of the audience, like think about this big, huge audience that you want to reach with the video you publish.

Now, here's what's so interesting. Literally in real time, as you're releasing your video, there could be 100 ,000 people that would be perfect for your video. But if I label my video title like, I'm gonna go ahead and do it.

How to present well on YouTube. Now if I talk about presenting, all the people that aren't on camera, maybe 40%, there's no reason for them to click because the video isn't about them. So the thing that I think about when I'm coming up with a video idea is, is this relevant to the broad audience?

And ultimately, If too many people say it's not for me, I'm doomed. Now, again, this is the part about your channel.

And if you're like, I'm just I'm trying to wrap my head around this. I'm not sure I get it because it took me a long time myself. But do this.

First off, know that you can create very similar, if not the same videos to what you're already publishing right now. which is amazing. It's literally just the angle, or think about this, the entry point of a video.

So think about every video, not just the title, not just the topic and thumbnail, but how you open up the video, the first one to two minutes. What you share. You can design that for a broad audience and then you can get into a specific point that you want to make no matter the video.

And if you're not sure like how to connect the dots, use Ask Studio and then add this prompt and get some feedback from Ask Studio. And then again, use the prompt in the description to get feedback and to open up this conversation. Now, this prompt really it helps Ask Studio understand your subject matter, the channel, the type of view.

viewers you want to reach, and more importantly, the video you're thinking of making. And you can start this discussion about like, is this a broad topic or not? What might be some disqualifications that cause viewers not to click?

And the moment you start having this discussion is the moment it starts coming together with videos that actually do connect. And here's what's so very powerful. This viewer came in and watched this video, my most recent, that's currently getting recommended.

Now this other video, less than a thousand subscribers, has really great watch time metrics. Again, we're gonna get to how to make that happen. And what happens is the algorithm serves one video through recommendations.

A viewer watches, and then guess what do you think happens? they find another video from your channel, they recommend that, and this is exactly what we have. The two exact videos.

Now, this is the part I think we need to get really clear about and understand because of how challenging YouTube is, it really is. If we look at this one of 10, it's gonna show us the last 10 videos we've published.

And notice, at this point, my top three videos, or 30%, are really performing much, much better than the 10 videos overall. And this is totally normal. Now since I started using this method, I'm getting maybe two videos out of ten that do exceptionally well, and maybe three or four percent, like one in 25 or one in 50, that do exceptional.

Like the less than a thousand subscribers, that video now has 91 ,000 views. But it does take a little bit of time. Now the good news...

is that I want to show you that watch time stuff that has made it so much easier for me. And it really comes down to watch time metrics. Because watch time is the one signal that signals satisfaction to the algorithm.

And for the longest time, I really focused on this. Watch time and it's it's actually it's not this it's not just that the video is gaining more watch time It's really the two signals. You've you've probably heard about not number one is the click -through rate And if you look at this, it's so interesting The line over the last three days is almost perfectly stable.

The video metrics are not eroding or coming down, which typically happens as a video gets sent out. But the topic is very broad. Like this topic is the fastest way to make videos that YouTube pushes.

Perfect. And that appeals to almost anybody on YouTube that wants more views. So the CTR is holding steady.

Now, this is the thing that's so interesting. Honestly, the audience retention for this video is not that great. It's only 26%.

In other words, 26 % of the video is being watched by all the viewers. Not even 30%. However, I went a bit longer with this particular video.

I've done it a few times now, and you know what happens is that extends the average view duration in one specific core metric that people don't talk about enough, and that's watch time per impression. And if there was one metric that I think, and it's funny, Ask Studio says, This is the one metric.

Like if you go ask, and in fact do this, ask, ask studio, hey, what do you know about watch time per impression and should I give this thing a shot? Is this the thing to focus on? And I'd love to get, I'm curious what ask studio tells you.

What it tells me and what I've believed for a long time, it's the one signal for satisfaction because it combines the CTR. and the average view duration, and it kind of lets the algorithm know every time we show this video to a viewer, this is what we can expect as far as how long they watch. And we know the thing that YouTube wants is to keep viewers watching longer because the longer the videos keep viewers watching, the more ads YouTube can show and the more money they make.

So it's like if we can focus on improving the watch time per impression, great things happen. And this is the thing. If I publish a 10 minute video.

To get an average view duration of five minutes, I need this metric, the retention, to be 50%, which is very challenging, especially on a 10 -minute video. But by going 20 minutes, I can keep the audience watching for less than 30%, and still, like let's take 30%. Then the average view duration is six minutes.

So now we have that CTR multiplied by six minutes, and when I launched this video, the watch time per impression was very high. because people are watching longer. And here, what does it say?

One minute and one second longer than usual. And I think the thing that really connects it for me is then identifying like the perfect title for the video. And again, this is something you can leverage with Ask Studio and even do this.

Ask Studio, hey, what is my audience currently watching on YouTube? And fact is, if you're getting started, this can be such a sore point. Like if you're bigger, you're going to get some ideas back and you're going to start thinking and seeing titles that could be perfect.

But if you're getting started, well, what the heck do you do? Literally check that this is kind of ridiculous, but stick with me. You watch.

YouTube and you pay attention to what's happening in your space you keep uploading videos on a regular basis and over time you're going to start learning you're going to get more data back and it's going to be easier to publish a video that does this you're going to see patterns through other people's videos which is sort of okay but as you publish more videos you'll get more data back from those videos allowing you to make better decisions and and again Use Ask Studio.

Here's the shortcut. This video on the screen right now really breaks down that wave strategy and identifying the perfect title and thumbnail combination. Click on that video.

When you do, you're going to get the tips, tactics, and so much more. But you are going to feed a kitten. And she is so hungry.

I'm Brian G. Peace. Power.

I'll see you on the next one.

The Hook

The bait, then the rug-pull.

Brian G. Johnson opens with a number that shouldn't make sense: a video published two days ago already has 17,000 views, even though its underlying watch-time metrics aren't that impressive. The explanation he unpacks is a shift in how he thinks about getting recommended at all, built on a single word: relevant.

CTA Breakdown