Algorithm Insights: YouTube answers general questions about CTR and AVD

In a video, YouTube shares insights on the YouTube algorithm and tips for creators on how to get the most out of the new YouTube Analytics.

In order to rank well with video content on YouTube, it is important to understand how the platform’s algorithm works. A little over a month ago, YouTube announced an update to the Insights. Now a video explains how creators can use them to work with the algorithm so that their videos are shown to more people.

YouTube algorithm insights: what do CTR and AVD say?

In the video of the Creator Insider Channel, Rachel and Patricia, both product managers at YouTube Analytics, talk about the YouTube algorithm. In particular, they focus on how Click Through Rate (CTR) and Average View Duration (AVD) are evaluated by the algorithm. With the new Insights Update, these two metrics will be available to all creators, giving them the opportunity to improve their performance. In the video, Patricia explains that many clicks don’t mean high CTR – sometimes the opposite:

Click-through rate is a really tricky metric to understand. So, for a lot of creators, if you go in you look at your most successful videos the videos with the most views those are actually the most likely to have the lowest click-through rate.

Because videos with a high distribution of a wide audience are displayed, this means on the one hand more clicks, but on the other hand that the target group is less selected and it is therefore increasingly unlikely that the viewers will click. Conversely, videos with a few views can have the highest CTR, since they were played out to a small but very suitable target group. But, as YouTube explains in the video, individually, each metric can seem illogical or confusing. It is therefore always better to include all of the metrics in the analysis.

Does a longer video mean a longer average view duration?

In the video, the two product managers also discuss average view duration. Users expressed concerns about different video lengths. But the question of whether the length of a video is decisive in the recommendation is answered clearly by YouTube:

So, in discovery, we actually look at both relative and absolute watch time, those are both meaningful signals and how your videos are going to be recommended. You would still need to do some cross-referencing, even if we swapped out ’average view duration’ for ’average percentage viewed’, because it’s easier for short videos to hit a really high amount of average percentage watched. We can only focus creators on so many metrics, and we chose average view duration because how much time somebody spends with you in your content is a really strong indicator of interest. That being said, we want videos of all lengths to succeed on YouTube, and get discovered.

While AVD and CTR are clearly crucial metrics for YouTube, they don’t always provide an explanation for the good or bad performance of a video. YouTube highlights three factors that significantly influence the performance of a video:

  • Competition / competition
  • interest
  • Seasonality

Creators should keep in mind that there is already a lot of good content on certain topics. To stand out in the correspondingly large competition is not easy. Likewise, videos that treat less popular content would also be played less. Not because the algorithm wants to keep some topics small, but because the topic is simply of less interest. In addition, creators should note that some topics are seasonal and therefore do not perform well all year round.

A / B tests and channel comparison tools: new features in development

In order to improve the performance of videos and to provide Creatorn with answers to which content is most popular, A / B tests for thumbnails are currently considered:

In the long term, we hope to have A / B thumbnail testing eventually, which will help give you even more concrete answers.

In addition to the A / B test for thumbnails, YouTube is also working on developing a comparison tool for CTR and AVD. This would make it possible to compare your own metrics with those of similar channels. This should make it easier and easier for creators to create suitable and interesting content that can be discovered by as many people as possible.

There is more insights in the full video.


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