One of the great, eternal mysteries of the internet is the YouTube algorithm. Over 70 percent of the content consumed on YouTube comes directly from recommendations, so it’s easy to understand why creators and marketers are obsessed with figuring it out.
Although nobody (not even YouTube themselves) has a full understanding of how it works, certain factors do influence it more than others. But to understand the algorithm, we must start from the beginning.
Read more: How to Grow Your YouTube Channel in 2024: The Ultimate Guide
In the beginning, there was no algorithm. It was all about gaining credibility as a platform for YouTube. Since everything revolved around views, YouTube’s first algorithm strove to recommend videos that attracted the most clicks. The more people clicked on a video, the more it would appear for others to click on, too. Soon, malpractices around using tags became common, and YouTube stepped in.
Image Credit: veedyou.com
In 2012, YouTube changed its algorithm in favor of video watch time because they thought time viewed was the true test of quality. But, soon enough, creators found loopholes like view-botting their content or making long videos with no value. This led the algorithm to change again around 2015-16.
Through surveys, YouTube collected data from users to understand what kind of videos “satisfy” them the most, and with their sophisticated AI developed the recommendation system. As a result, YouTube began to suggest videos that each viewer would be more likely to watch, rather than videos that other people were viewing. And the outcomes—well, they were really excellent! So much so, that YouTube hasn’t announced major changes to the algorithm since.
In 2025, YouTube introduced significant updates to its recommendation system, shifting focus from traditional performance metrics to personalized user engagement and satisfaction.
For the algorithm to recommend videos to a user, there are two steps involved. First, it rates videos based on their performance analytics. Then, it matches videos to users based on past viewing habits and comparable material. Matching people with the content they want to watch is the objective.
The YouTube algorithm isn't a singular entity, but a combination several systems on the platform. These different algorithms appear in different areas of YouTube and have different factors influencing them.
You can see recommendations from the algorithm in 3 main areas of YouTube:
How is it that YouTube already knows what you want to watch from the moment you’re on the website? That’s because your homepage is curated just for you!
Videos that show up here are usually:
That’s why, as a creator, it’s so important to get people watching your videos so your channel is always in their watch history. Then you can find ways to keep them watching longer and engaging more frequently.
Depending on someone’s viewing habits, they may also see videos related to their location, language, or other demographics.
These are the videos recommended alongside the video you’re already watching, on the right side of your screen. The YouTube algorithm takes into account a number of variables, including your topic of interest, liked channels, and your watch history, to provide a customized list of videos for the recommended area.
In a nutshell, the algorithm compiles a list of videos that you could find interesting and relevant by analyzing your behavior on the website.
So how do you persuade YouTube to suggest your videos to more viewers? Start by observing the “suggested” column next to your competitors’ content. If YouTube is recommending specific videos there, try filming your own version of that content so you can get recommended too!
How does YouTube decide which videos should go on a search page? Based on user behavior and keywords, the system narrows down the enormous video library to a limited number and then ranks them according to engagement metrics and relevancy. YouTube makes sure that users get the greatest search results by balancing relevancy and popularity.
Of course, YouTube keywords are important here. However, because the system takes into account personalized signals, each user's search results may vary significantly.
Videos with better engagement metrics and potential, such as views, shares, likes, and comments, are given priority in search results, but YouTube also makes sure that fresh content from new channels isn't unfairly eclipsed by popular YouTubers. The platform adds a certain amount of randomization and can show diverse results that are still relevant to the search query.
The main goal of YouTube’s algorithm is to keep viewers on the website for as long as possible, so be sure to optimize your content for this crucial area of the platform.
YouTube doesn’t spray your video out to the whole platform and cross its fingers. It moves strategically, starting with the people most likely to care, then expanding only if your content keeps delivering. Here's how it plays out:
These are your ride-or-dies—the viewers who show up almost every time you post. Usually subscribers, but not always. Some people just watch everything you make, even without subscribing.
If you’re just starting out, you won’t have this group yet. YouTube has to take a best guess based on your video’s topic. No traction usually means there’s not enough info yet to find your people.
Next are the occasional viewers. They know your content, but don’t watch everything. Maybe they caught a few past uploads, maybe they’re subscribed but don’t tune in often.
If the video’s still doing well, YouTube shows it to people who are into the same general subject. So, if your video is about photography, it’ll start appearing in front of viewers who already watch photography content.
Next, the algorithm widens the net to audiences in closely related fields. A photography video might now reach fans of videography or graphic design—areas that overlap enough to still be relevant.
The next jump takes your video to people who are into content that’s barely related to those nearby fields. Think animation, motion graphics, or web design. Still in the creative zone, but getting more distant.
Eventually, it hits a point where your content no longer connects. Maybe now it's showing your video to people into programming or cybersecurity—still technically connected through a chain of interests, but too far removed. If the video starts flopping at this stage, the algorithm stops pushing it.
The algorithm moves outward in layers, only if your video keeps hitting. It’s not about going viral overnight—it’s about climbing step by step, keeping each audience engaged as you go.
It’s safe to say the YouTube algorithm won’t be changing its core function in the future. While metrics like click-through rates (CTR) and watch time remain relevant, the algorithm now prioritizes user satisfaction indicators. These include likes, comments, and survey feedback, which provide insights into the value viewers derive from content. Additionally, the system considers viewer retention patterns, recognizing that both short, impactful videos and longer, engaging content have their place, depending on audience preferences. Encouraging return visits and sustained engagement has become crucial for creators aiming to thrive under the new algorithm.
In the past, we've stressed the importance of watch time and engagement to get ahead with the algorithm. But the way to look at the YouTube algorithm going forward is beyond a single metric. Many aspects now influence the impact of your video, as opposed to earlier days. For example, traditionally we would associate the packaging of a video with the title and thumbnail but now, particularly for mobile users, the first 10 seconds of your video, which is called a visual hook, is equally important.
The integration of advanced AI labels in content evaluation has also changed things up a bit. Beyond basic categorization, AI analyzes the nuances of content, including style and target audience, to ensure precise recommendations. The system evaluates the tone, emotions, and delivery style, aligning them with viewer expectations and preferences. and production factors editing quality, pacing, and overall structure are assessed to determine suitability for different audience segments.
Considering all the above will be increasingly important for getting the algorithm working for you. So, implement them to the best of your abilities.
Remember, the algorithm’s job is to provide the perfect content to each viewer, without creator or content bias. So, stop making videos for the algorithm! Instead, aim to satisfy that one ideal viewer, and you’ve got the algorithm playing for your team!
In addition to being an avid movie and gaming enthusiast, Uttaran Samaddar is an experienced writer who has lent his creativity and unique perspective to various publications. He loves hearing and telling stories.
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