How the Youtube algorithm works
More than two billion users use the YouTube platform every month. It is not surprising that modern companies are increasingly relying on promoting their brands on YouTube. However, to reach the right audience, you need to know the algorithm of this platform. How does it work and what should you know about it to increase the visibility of your materials in search results?
When positioning sites in Google, the most important thing is to follow the rules of the search engine algorithm. When deciding whether to create video visibility on YouTube, you need to consider the platform's guidelines.
The Google algorithm is a system based on machine learning and artificial intelligence that processes data in real time to generate search results based on the preferences of individual recipients. This is a very advanced and sophisticated tool that understands both simple keywords and more complex phrases that capture user interests. The rating of this video is based on interaction with various materials in the profile. Therefore, it is worth taking care of the involvement of your audience, because the visibility of the video in search results depends on it.
Although YouTube's recommendation algorithm has changed over the years, it still prioritizes users' preferences and tailors results to their expectations. It is estimated that up to 70% of views on the platform are generated through algorithm recommendations.
The number of YouTube users is constantly increasing. Therefore, the platform should use recommendation systems and provide users with content tailored to their preferences.
How does the YouTube algorithm work?
YouTube's algorithm tailors search results to individual users by analyzing how likely they are to be interested in the material.
The system then takes into account the feedback loop to ensure that the diverse interests of recipients are not missed. The algorithm consists of two basic neural networks: - the first neural network - its task is to create a list of videos that may be of interest to the user. The algorithm then collects data from your browsing history and analyzes a small collection of content available on the platform. A key aspect of YouTube's first neural network recommendation system is to select the few most relevant videos from a large list; - the second neural network is responsible for ordering the selected videos, assigning each of them a certain score. Then a lot of information is taken into account, not only related to the material, but also to the characteristics of the user.
Although there are many aspects to building YouTube search results lists, there are 6 main factors that have the greatest impact on a video's ranking:
- total viewing time;
- click-through rate;
- browser history;
- user interests in the context of the topic;
- user interests in the context of content on this channel;
- information about the author of the video.
Based on these factors, individual materials are assigned a certain number of points, which are then taken into account when constructing a rating.
An important benefit of YouTube's two-step approach to making recommendations is the ability to select the best videos from a large collection of content. However, while this is a very favorable situation from the users' point of view, it is becoming increasingly difficult for creators to tailor content to YouTube's algorithm guidelines.
YouTube Algorithm: Content Rating System
Recommendations tailored to individual users' personal preferences are presented on the YouTube home page. Viewers can discover new content and discover interesting channels there. In recent years, the click-through rate of materials presented on the main page has increased significantly. Therefore, it is important to optimize your materials so that they are on the main page of the site.
First, you should familiarize yourself with the characteristics of the content posted on the main page. First of all, these are videos from subscribed channels, content viewed by users with similar preferences, and viral videos that have gained great popularity recently. The viewer then receives a list of different offers, among which he is sure to find content that meets his expectations.
When making recommendations, Google's algorithm relies on two key factors:
- user participation;
- personalization.
Audience engagement is measured using metrics such as click-through rate or total watch time. Based on them, the value of individual content is assessed, which is then assigned a certain position in the ranking.
Personalization refers to compiling a list of recommendations based on the individual preferences of users or people with similar interests and involvement in a particular movie topic.
Also worth mentioning is the “Recommended” section. The algorithm places in it a personalized list of content taking into account the interests of a particular user. It is built on the basis of the viewer's previous activity and information, for example, materials that are thematically related to previously watched films or TV series started.
Many people forget that YouTube is the second largest search engine after Google. Therefore, it is important to comprehensively optimize your content on this platform in terms of SEO and artificial intelligence algorithms.
YouTube is the most effective of all social networks for user retention. This proves that the platform's algorithm is effective and correctly tailors content to the preferences of individual recipients. So it's worth studying your target market's expectations, optimizing your videos, and trying out different promotion methods that will ensure satisfactory content visibility in YouTube search results.
