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20 Confirmed Facts About YouTube’s Algorithm

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Instead of counting the number of clicks or views a video gets, YouTube’s algorithms focus on ensuring viewers are happy with what they watch.

This article examines how YouTube’s algorithms work to help users find videos they like and keep them watching for longer.

We’ll explain how YouTube selects videos for different parts of its site, such as the home page and the “up next” suggestions.

We’ll also discuss what makes some videos appear more than others and how YouTube matches videos to each person’s interests.

By breaking this down, we hope to help marketers and YouTubers understand how to work better with YouTube’s system.

A summary of all facts is listed at the end.

Prioritizing Viewer Satisfaction

Early on, YouTube ranked videos based on watch time data, assuming longer view durations correlated with audience satisfaction.

However, they realized that total watch time alone was an incomplete measure, as viewers could still be left unsatisfied.

So, beginning in the early 2010s, YouTube prioritized viewer satisfaction metrics for ranking content across the site.

The algorithms consider signals like:

  • Survey responses directly asking viewers about their satisfaction with recommended videos.
  • Clicks on the “like,” “dislike,” or “not interested” buttons which indicate satisfaction.
  • Overall audience retention metrics like the percentage of videos viewed.
  • User behavior metrics, including what users have watched before (watch history) and what they watch after a video (watch next).

The recommendation algorithms continuously learn from user behavior patterns and explicit satisfaction inputs to identify the best videos to recommend.

How Videos Rank On The Homepage

The YouTube homepage curates and ranks a selection of videos a viewer will most likely watch.

The ranking factors include:

Performance Data

This covers metrics like click-through rates from impressions and average view duration. When shown on its homepages, YouTube uses these traditional viewer behavioral signals to gauge how compelling a video is for other viewers.

Personalized Relevance

Besides performance data, YouTube relies heavily on personalized relevance to customize the homepage feed for each viewer’s unique interests. This personalization is based on insights from their viewing history, subscriptions, and engagement patterns with specific topics or creators.

How YouTube Ranks Suggested Video Recommendations

The suggested videos column is designed to keep viewers engaged by identifying other videos relevant to what they’re currently watching and aligned with their interests.

The ranking factors include:

Video Co-Viewing

YouTube analyzes viewing patterns to understand which videos are frequently watched together or sequentially by the same audience segments. This allows them to recommend related content the viewer will likely watch next.

Topic/Category Matching

The algorithm looks for videos covering topics or categories similar to the video being watched currently to provide tightly relevant suggestions.

Personal Watch History

A viewer’s viewing patterns and history are a strong signal for suggesting videos they’ll likely want to watch again.

Channel Subscriptions

Videos from channels that viewers frequently watch and engage with are prioritized as suggestions to keep them connected to favored creators.

External Ranking Variables

YouTube has acknowledged the following external variables can impact video performance:

  • The overall popularity and competition level for different topics and content categories.
  • Shifting viewer behavior patterns and interest trends in what content they consume.
  • Seasonal effects can influence what types of videos people watch during different times of the year.

Being a small or emerging creator can also be a positive factor, as YouTube tries to get them discovered through recommendations.

The company says it closely monitors success rates for new creators and is working on further advancements like:

  • Leveraging advanced AI language models to better understand content topics and viewer interests.
  • Optimizing the discovery experience with improved layouts and content pathways to reduce “choice paralysis.”

Strategies For Creators

With viewer satisfaction as the overarching goal, this is how creators can maximize the potential of having their videos recommended:

  • Focus on creating content that drives high viewer satisfaction through strong audience retention, positive survey responses, likes/engagement, and low abandon rates.
  • Develop consistent series or sequel videos to increase chances of being suggested for related/sequence views.
  • Utilize playlists, end screens, and linked video prompts to connect your content for extended viewing sessions.
  • Explore creating content in newer formats, such as Shorts, live streams, or podcasts, that may align with changing viewer interests.
  • Monitor performance overall, specifically from your existing subscriber base as a baseline.
  • Don’t get discouraged by initial metrics. YouTube allows videos to continuously find relevant audience segments over time.
  • Pay attention to seasonality trends, competition, and evolving viewer interests, which can all impact recommendations.

In Summary – 20 Key Facts About YouTube’s Algorithm

  1. YouTube has multiple algorithms for different sections (homepage, suggested videos, search, etc.).
  2. The recommendation system powers the homepage and suggested video sections.
  3. The system pulls in videos that are relevant for each viewer.
  4. Maximizing viewer satisfaction is the top priority for rankings.
  5. YouTube uses survey responses, likes, dislikes, and “not interested” clicks to measure satisfaction.
  6. High audience retention percentages signal positive satisfaction.
  7. Homepage rankings combine performance data and personalized relevance.
  8. Performance is based on click-through rates and average view duration.
  9. Personalized relevance factors include watch history, interests, and subscriptions.
  10. Suggested videos prioritize content that is co-viewed by the same audiences.
  11. Videos from subscribed channels are prioritized for suggestions.
  12. Consistent series and sequential videos increase suggestions for related viewing.
  13. Playlists, end screens, and linked videos can extend viewing sessions.
  14. Creating engaging, satisfying content is the core strategy for recommendations.
  15. External factors like competition, trends, and seasonality impact recommendations.
  16. YouTube aims to help new/smaller creators get discovered through recommendations.
  17. AI language models are improving content understanding and personalization.
  18. YouTube optimizes the discovery experience to reduce “choice paralysis.”
  19. Videos can find audiences over time, even if initial metrics are discouraging.
  20. The algorithm focuses on delivering long-term, satisfying experiences for viewer retention.

Insight From Industry Experts

While putting together this article, I reached out to industry experts to ask about their take on YouTube’s algorithms and what’s currently working for them.

Greg Jarboe, the president and co-founder of SEO-PR and author of YouTube and Video Marketing, says:

“The goals of YouTube’s search and discovery system are twofold: to help viewers find the videos they want to watch, and to maximize long-term viewer engagement and satisfaction. So, to optimize your videos for discovery, you should write optimized titles, tags, and descriptions. This has been true since July 2011, when the YouTube Creator Playbook became available to the public for the first time.

However, YouTube changed its algorithm in October 2012 – replacing ‘view count’ with ‘watch time.’ That’s why you need to go beyond optimizing your video’s metadata. You also need to keep viewers watching with a variety of techniques. For starters, you need to create a compelling opening to your videos and then use effective editing techniques to maintain and build interest through the video.

There are other ranking factors, of course, but these are the two most important ones. I’ve used these video SEO best practices to help the Travel Magazine channel increase from just 1,510 to 8.7 million views. And these video SEO techniques help the SonoSite channel grow from 99,529 views to 22.7 million views.

The biggest recent trend is the advent of YouTube Shorts, which is discoverable on the YouTube homepage (in the new Shorts shelf), as well as across other parts of the app. For more details, read “Can YouTube Shorts Be Monetized? Spoiler Alert: Some Already Are!“

Brie E. Anderson, an SEO and digital marketing consultant, says:

“In my experience, there are a few things that are really critical when it comes to optimizing for YouTube, most of which won’t be much of a surprise. The first is obviously the keyword you choose to target. It’s really hard to beat out really large and high authority channels, much like it is on Google. That being said, using tools like TubeBuddy can help you get a sense of the keywords you can compete for.

Another big thing is focusing on the SERP for YouTube Search. Your thumbnail has to be attention-grabbing – this is honestly what we test the most and one of the most impactful tests we run. More times than not, you’re looking at a large face, and max four words. But the amount of contrast happening in the thumbnail and how well it explains the topic of the video is the main concern.

Also, adding the ‘chapters’ timestamps can be really helpful. YouTube actually shows these in the SERP, as mentioned in this article.

Lastly, providing your own .srt file with captions can really help YouTube understand what your video is about.

Aside from actual on-video optimizations, I usually encourage people to write blog posts and embed their videos or, at the very least, link to them. This just helps with indexing and building some authority. It also increases the chance that the video will help YOUR SITE rank (as opposed to YouTube).”

Sources: YouTube’s Creator Insider Channel (1, 2, 3, 4, 5, 6), How YouTube Works

More resources: 


Featured Image: Roman Samborskyi/Shutterstock

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