When it comes to YouTube, you shouldn’t think of views, likes, and subscribers in terms of free will. In fact, YouTube works on a fairly complicated algorithm that influences how many likes, views, and subscribers content creators gain. One may consider the idea to buy YouTube views as a helpful marketing tool. As a rule it helps to boost activity faster and to gain non-effort results. Since YouTube’s algorithm is responsible for driving over 70% of what most folks watch on the social media platform – it makes sense to get more familiar with how it exactly works. Seventy percent is a lot, and content creators should focus on following the guidelines and rules of the algorithm rather than have preconceived notions and expect a video to work no matter what. 70% shows the level of influence the algorithm has on YouTube and how content is distributed to people in different niches. The platform already has over 2.5 billion users who watch 694,000 videos every minute. And YouTube’s algorithmic recommendation system works its magic and is responsible for most views on videos.

YouTube Algorithm: Perspective Matters

It shouldn’t come as a surprise to most creators, influencers, and marketers that they need to figure out the mechanics of the YouTube algorithm to unlock the full potential of their content’s growth on the platform. So, what makes YouTube’s algorithm tick? There are many elements that the YouTube algorithm favors, and there are some factors that don’t work well with the algorithm. When it comes to creating content on YouTube – it is crucial to spark some level of curiosity and follow rules that put you in the good graces of YouTube’s algorithm.

YouTube Algorithm in 2023

The YouTube algorithm makes more unique recommendations to users in 2023. Remember that these recommendations are personalized based on each user’s watch history and interests. The algorithm takes into account the quality and performance of videos for recommendations. When it comes to deciding on a recommendation to a specific user, the algorithm considers more than one element. For instance, the YouTube algorithm considers what videos a user has loved watching in the past. So, if a user has watched a lot of tech reviews – it is safe to say he’ll get more refined recommendations on more tech-related product reviews. Similarly, YouTube’s algorithm considers what channels or topics a user usually looks at to consume content. If a user is subscribed to, say, Jeremy Jahns or Chris Stuckmann to watch their film reviews, there is a good chance he’ll get more recommendations of similar content from other film and TV show reviewers. The same rules apply if a user is subscribed to a food network, travel log, or political commentary channel. YouTube’s algorithm also considers what videos users typically decide to watch together. So, if a user watches “Best Pasta Dishes to Try in 2023,” – he might also check out “Best Italian Pasta Dishes” or similar content. YouTube algorithm picks up your loop on how you decide to watch a combination of videos and follow up with the most suitable recommendations, which boosts videos’ overall viewing. So, the question is – how does YouTube review whether or not a video is good enough for recommendation? For starters, it’s not ALL about content – YouTube’s algorithm reviews the actual video content before making recommendations. It is obvious that videos about how perfect YouTube is probably won’t go viral than the helpful video that teaches people how to paint their apartment before Christmas. YouTube’s algorithm checks a combination of metrics for video recommendations:

How long do users watch a video?

The YouTube algorithm considers the average percentages and view duration to rank recommendations.

Do users watch the full video?

With each video recommendation, YouTube considers how long people watch it, click on it, or ignore it.

What is the geographical context of the video?

The day and time of the language significantly influences the algorithm’s recommendation.

Did people like the video in general?

The YouTube algorithm reviews likes, dislikes, views, and engagement rates to get the full picture.

What Elements YouTube Algorithm Prioritizes

Different users looking for similar content can find altogether different results. This boils down to “how” the YouTube algorithm prioritizes different content. Let’s take a look at the key elements:

• Quality

To review the quality of videos – the algorithm checks signals to establish the trustworthiness and authority of the channel based on a specific topic.

• Engagement

Signals involve watch percentage, watch time, shares, comments, and likes.

• Relevance

The algorithm matches elements like tags, descriptions, content, and titles to each user’s search query.

• User Watch and Search History

The YouTube algorithm prioritizes what users have viewed and enjoyed recently, and this impacts their search results. In fact, search history is crucial for the YouTube algorithm to not just recommend the most viewed and quality content – but helpful content based on each user. Also, “how” the YouTube algorithm combines these prioritized elements can vary. It usually depends on “where” on the platform you’re getting recommendations.

YouTube Algorithm Recommendations: 3 Spots

The YouTube platform recommends content in three places:

1.   Home

This is a personalized space for each viewer. The YouTube algorithm works around a recommendation engine that chooses videos for each user’s home screen. Home video recommendations are based on video performance and search and watch history of the user.

2.   Suggested Videos

The YouTube algorithm recommends suggested videos based on what users are already watching. Suggested videos pop up as “Up Next,” and the algorithm suggests these videos based on the watch history of the viewer and the current topic of the video.

3.   Search

Content users find through search boils down to keywords. In fact, the algorithm recommends videos on its search engine based on the placement of the most relevant keywords. However, search results for each user would be relatively different because of personalized signals. Algorithm’s customized signals include:

• Engagement and performance of the video
• The relevance of the video content, search keyword, description, and title

YouTube Algorithm for Shorts

YouTube shorts are vertical videos that most content creators create from a smartphone or vertical angles of their mirrorless cameras. Millions of users watch YouTube Shorts daily, and this format, like TikTok, is getting a lot of attention on YouTube. So, does YouTube follow the same rules and standards to recommend Shorts to users? Most importantly, is it more difficult for content creators to get their YouTube shorts discovered? You can watch and find YouTube shorts on the homepage whether you’re using an app or website. Shorts involve more or less similar recommendation signals, like long-form YouTube content. When it comes to Shorts, the YouTube algorithm considers relevance, the watch history of the user, engagement, and similar content. Watch time is a crucial signal for the algorithm to focus on 15-second Shorts that are different from classic YouTube videos. Inbound YouTube experts concur that most YouTube channels have realized the value of the Shorts format and want to make the most of it. The emergence of vertical video format works on similar algorithmic standards. If you already have experience creating TikTok videos or Instagram Reels, you’d love YouTube Shorts. However, this rise may propel YouTube to make algorithmic changes in how people get recommendations for Shorts.

Follow the Algorithm Standards and Rules

Improve Branding

Continue to improve the branding of your YouTube channel so that the algorithm recommends more of your videos. For instance, personalize the design aspects and keep it consistent without making too many changes. It means profile color schemes, aesthetics, and logos on a YouTube channel should be similar to social media profiles. You can also include custom banners and use design elements that reflect your unique brand.

Create Catchy Thumbnails

Posting videos with eye-catching thumbnails makes a huge difference to algorithm and viewers. It’s one of the most effective ways to get more people to click on your videos and boost engagement. However, in an attempt to create a catchy thumbnail for your video – don’t add inappropriate elements. In fact, based on the algorithm – YouTube recommends videos with impressive thumbnails. For instance, enlarge the thumbnail to a maximum of 1280 x 720 pixels. And don’t use any other image format other than PNG and JPEG.

Focus on What Draws the Most of Your Audience

If you want continuous exposure, nothing beats direct and honest involvement with your target audience. Sure, it’s common to ask for feedback and add a solid CTA. But it’s not enough to just “ask” your audience to like, share, and subscribe – you have to actively engage and focus on elements that draw most of your subscribers’ attention. Take sincere and constructive feedback from your audience seriously. In fact, how you respond to feedback determines the success of your future YouTube projects.

Improve SEO

YouTube has become the second biggest search engine after Google, and optimizing content around SEO is crucial to get more views and subscribers. SEO-optimized videos – even with a relatively small view count pop up high on YouTube search results. So, when you add your video description, use keywords and phrases that would improve your ranking and visibility on YouTube search results. Conduct keyword research so that you add the most relevant keywords and consistently improve your ranking.

The algorithm reviews the metadata of each user and then decides which video is suitable to recommend. And this metadata revolves around SEO. So, use only relevant and high-performing keywords to get more recommendations from the YouTube algorithm. However, there’s no need to place keywords in your video tags. In fact, contrary to what you may have heard – tags have little to do with video discovery. Another reason to SEO-optimize your YouTube content is to avoid scams, deceptive practices, and spam that are against the platform’s policies.

Final Thoughts

The official word from YouTube is that its algorithm doesn’t directly pay close attention to content. Instead, it focuses on viewers. So, it’s not all about making algorithmic-driven content or creating videos that work just for the algorithm – the quality of videos has to be good enough and user-centric to get consistent recommendations from YouTube’s algorithm. In hindsight, there are no shortcuts to get algorithmic recommendations on YouTu