YouTube: How to Trick the Algorithm and Get 100 Unique Views

In the ever-evolving landscape of digital marketing, understanding how YouTube: how to trick the algorithm and get 100 unique views, becomes critically important for marketers. Are you wondering why YouTube views have skyrocketed, but leads and sales have remained flat? Do you want to know which YouTube metrics truly matter now and how to make your videos discoverable in Ask YouTube, ChatGPT, and other AI search tools? In this article, you will learn how new YouTube view metrics work, which analytics to track instead of the old ones, and how to optimize videos, chapters, and Shorts for AI search and discovery.

Now, the YouTube view metric is closer to an impression. If someone scrolls through a long video, and it automatically plays for a fraction of a second, YouTube counts it as a view. What YouTube previously called a view is now called an engaged view, meaning the person showed some interest in the video, rather than just scrolling past it.

YouTube Changes the Game: What Marketers Need to Know

Evolution of Metrics: YouTube Catches Up with Competitors

According to Justin Brown, this change is YouTube’s attempt to catch up with other platforms. For a long time, creators who published the same video on multiple platforms noticed that YouTube reported fewer views than TikTok or Facebook, because platforms count views differently. On some platforms, scrolling past a video has been counted as a view for many years.

In the old system, YouTube never published a precise definition of a view. Rumors attributed a 30-second threshold, but Justin argues that this was never a good metric because it didn’t work for short videos. A view was simply someone who watched enough of a video for it to be considered meaningful, which could mean a few seconds on one video and most of another.

YouTube also hasn’t explained what an engaged view is, and Justin suspects the platform intentionally left the definition vague. Google owns the web browser, operating systems, Chromebooks, and Android phones, so it can use signals like whether a browser tab is open or whether a person watched a previous video and is more likely to watch the next one when it plays automatically.

Justin believes these behavioral signals now carry more weight than the percentage of video watched. His best guess is that engaged viewing depends on the video’s duration and starts with a couple of seconds—enough time for a person to decide if the video is right for them. From there, the score should depend on what happens next: a viewer who leaves immediately probably shouldn’t be counted, while one who stays should.

Autoplay and its Impact on Engagement

Autoplay also changes how people watch videos. Videos that previously didn’t autoplay now do so on TVs, mobile devices, and computers. Justin has caught himself watching videos in the mobile app that he never clicked on, because they started playing as he scrolled through the feed.

YouTube now plays these previews from the beginning of the video, and if he scrolls through the feed and returns, playback resumes from where he left off. Since the YouTube algorithm understands viewer behavior and preferences, Justin sees that this autoplay experience leads to more engaged views, not just views.

On the Primal Video channel, the number of views noticeably jumped on the day the changes took effect, and the baseline is now higher. A search-oriented video without a clickbait title used to get a few thousand views in the first 24 hours. Now that number is closer to 5,000-7,000 views. Engaged views, in contrast, are at roughly the same level or slightly higher.

Justin views the higher view counts as a new baseline rather than a performance gain, because the internal tracking his business relies on has barely changed. The rollout also appears uneven. Justin sees different view metrics on desktop than in the mobile app, especially for live streams, which he says is typical of how YouTube implements changes.

Key Metrics for Business: Not Just Views

For a business, the most important YouTube metric is the one tied to the video’s goal. Justin says that views are only a small part. Before evaluating a video, he recommends deciding whether its task is audience building, growing an email list, or driving sales. For companies building a brand, the goal is to generate leads, sales, and customers, and Justin works backward from that.

Views are nice, but by themselves, they say little about business results. Among the available YouTube analytics, engaged views (the equivalent of the old view count), watch time, and click-through rate provide a clearer picture of whether the right people are clicking and watching.

Justin believes every metric is worth looking at, but says each needs to be considered on a case-by-case basis. Comparing average view duration works when videos are similar, such as a recurring series. On a channel like Primal Video, where one week’s video is about editing software and the next is about shooting on an iPhone, a longer watch time on one video doesn’t mean viewers got more value from it. A viewer who watched a video for less time might have gotten exactly what they needed, solved their problem, and become a loyal, returning viewer.

Performance Analysis: Focus on Anomalies

Instead of spending hours in YouTube Analytics, Justin recommends doing future-focused analysis based on anomalies. He identifies the best- and worst-performing videos over a period, whether by engaged views, views, or watch time, and then compares their retention graphs to find where people are dropping off.

A video that performed poorly might have lost most of its audience early on, while the people who stayed watched the rest. This pattern indicates one of two problems: a weak hook or YouTube showing the video to the wrong audience, who clicked on it and immediately left. No single metric explains performance in isolation, so Justin looks at average view duration, watch time, and retention together to understand what’s happening with people who watch beyond the first 30 seconds.

How a video performs initially doesn’t reflect how it might perform over time, especially for YouTube search-focused channels. Primal Video doesn’t get big numbers on day one or week one, even with its channel size. Over time, videos get picked up by YouTube search and, increasingly, AI-driven traffic, and then they start to “snowball.” Some of the channel’s biggest videos flopped at launch.

Because of this, Justin usually leaves a poorly performing video alone and moves on to the next one. Re-editing has also become riskier. The Primal Video team used to shoot multiple “hooks,” publish the video, and use the YouTube editor to cut out the versions that weren’t working, with the option to restore them later. Now, edits to a published video can only remove footage. Nothing can be added back, and once an edit is saved, it can’t be undone.

• Pro Tip: The YouTube editor can still be used to test a longer intro. Justin’s approach is to publish a video with an extended section and, if it doesn’t work, trim it with a clean cut. Justin says viewers watching free content rarely notice a jump cut or a skip in the music.

Co-Viewing: A New Metric or Just an Estimate?

YouTube also added a metric called “views (co-viewed)” which estimates when more than one person is watching a video together, such as a family watching on a living room TV. YouTube bases the estimate on factors like demographics, video genre, and time of day.

Justin doesn’t recommend changing content to encourage group viewing, such as asking viewers to invite a friend or spouse. From everything he’s seen, the metric is still an estimate on YouTube’s part, and shared family accounts on TVs are already skewing the data. Until YouTube finds a more robust way to track co-viewing, he doesn’t see it as a meaningful lever for content strategy.

The value of co-viewing data is in brand deals and sponsorships because it can show that a creator’s reach is larger than just the view count suggests, especially for family-friendly content. Justin expects the ratio of views to engaged views to become a metric creators compare, replacing the traditional comparison of impressions to click-through rate. Because the co-viewing metric is so new, it’s too early to establish benchmarks.

Content Uniqueness: Packaging Is Everything

But turning a view into an engaged view still comes down to packaging: the title, thumbnail, and especially the beginning of the video. When a video auto-plays, the thumbnail matters less because the viewer may never see it. What happens in the first few seconds matters more. This isn’t entirely new.

When YouTube first introduced auto-play in the feed, the Primal Video team noticed people were watching without sound, without clicking on the video — a behavior Justin calls “toilet TV.” Justin’s answer was to put text on the screen at the beginning of each video explaining what the video is about. This isn’t closed captions that viewers can turn on or off. This is a title embedded in the video, such as “Best Mac Editing Software 2026,” so anyone seeing the video auto-play knows exactly what it’s about, even if they never saw the thumbnail or title.

The text appears in about the first 3 seconds, as the action starts on the screen, stating the video’s promise: the result or transformation the viewer will experience. Justin says this made a significant impact for Primal Video when auto-play launched because it moved viewers into an engaged state. A talking head with no on-screen text makes it difficult for a silent viewer to understand what the video is about.

• Pro Tip: The on-screen title text doesn’t require a specialized video editor. Justin describes it as simple on-screen text stating the video’s promise that any editor can add.

Ask YouTube and AI Search: A New Era of Content Discovery

YouTube is rolling out a feature called Ask YouTube, starting on TV and expanding to mobile and desktop. It allows users to have a conversation with YouTube to explore complex topics beyond traditional keyword search, and answers can include text as well as relevant videos, Shorts, and video clips. YouTube states that creators can improve their chances of appearing in Ask YouTube results by continuing to create unique, high-quality content and adding clear video chapters and descriptive titles.

Justin sees Ask YouTube as part of a broader shift. People expect to get to the outcome faster, whether they want to learn something or be entertained, and AI tools have raised those expectations. He anticipates that viewers will increasingly jump to specific sections of videos rather than watching the entire thing. The hope is that a short clip or summary will entice viewers to watch the full video, much as Google search snippets help some searchers on the spot while still driving traffic to videos.

AI search is already a significant traffic driver for Primal Video. The number one traffic source for the channel is YouTube search, and the second is Google search, from people who never started on YouTube. The third, and fastest-growing, is AI tools. ChatGPT and Claude are sending viewers to Primal Video’s YouTube videos, and the channel regularly gets comments from people saying ChatGPT sent them there.

SEO for AI: What’s Working Now

Keyword research isn’t gone. Primal Video still looks at search volume to gauge demand before creating a video, rather than publishing and hoping. But keyword order matters less than it used to. YouTube has long transcribed what’s said in videos, and now AI allows it to understand what’s actually happening in a video. The longer a video is live, the more YouTube learns from watch time which parts viewers find compelling, and Justin expects YouTube to direct viewers to those sections.

This means YouTube optimization now comes down to viewer experience. Justin focuses on what viewers want, what they would type into Google or YouTube to find a video, and what would grab their attention even if they weren’t looking for it.

As quick answers increasingly come from AI, Justin believes the part of video that AI can’t replace is the human part. A viewer can get a banner size or a setting from AI, but they want to hear how a specific person would approach it, what choices that person would make, and why. By sharing opinions, experiences, beliefs, and frameworks, you give viewers something no one else can offer. Justin says people are already “burning out” on AI content and that he leaves as soon as he hears an AI voice, so he expects human-created content to become more valuable, not less.

Optimizing Chapters: New “Fishing Lines” for Search

Primal Video treats chapters the way it used to treat titles. For each chapter, the team asks what someone would type in to find that section if it were a standalone video, researches keywords and search volume, and titles the chapter accordingly. Timestamps and chapter markers in the video description remain a place for optimization for both YouTube search and Google, and each is a direct link to that moment in the video.

Instead of writing chapter titles as “hooks” that tease what’s coming next, Justin recommends titles that communicate what each section actually covers. For a video about five things AI edits well, each chapter would name a specific thing. Revealing the answer in the timestamps helps YouTube surface that section, gives AI tools like ChatGPT a direct path to the answer, and prevents it from being hidden in a cryptic title that viewers may or may not click.

Justin views search-optimized chapters as additional “fishing lines” that help viewers find content. This approach works for channels built for search. Primal Video educates rather than entertains, so instead of competing with entertainment creators like MrBeast for a spot on the homepage, it aims to appear at the top when someone has a specific problem. He sees the same opportunity for most business owners, who can share their insights and talk about their products without competing for entertainment views.

AI tools make optimizing chapters much faster than doing it manually. Justin points to vidIQ, whose AI tools generate titles and chapter markers based on search volume. The Primal Video team connected vidIQ to their AI assistant via an MCP connection. After a video is complete, the team uploads a VTT or SRT subtitle file, which includes timings for everything said, and asks the AI to generate chapters based on key phrases around each section, while keeping the titles readable