Free YouTube Monetization Course – Lesson 8
The YouTube algorithm is developed every year by making small changes with the aim of increasing the level of service. Each development process aims to adapt the algorithm to users. No matter how many changes there are, there is one single working principle that does not change. The YouTube algorithm makes evaluations based on user behavior. Let me explain the logic of this working principle to you with a small example.
Let’s assume that you are sitting in a café and drinking coffee. Across from the café where you are sitting, there are three stores. All three of these stores are clothing stores. All three stores are men’s clothing stores. You are observing these stores from where you are sitting. You see that a customer enters the first store. Five minutes later, the customer leaves the store without buying anything and enters the second store. After spending 20–30 minutes in the second store, the customer leaves the store with a bag in hand and goes to the third store. After spending up to an hour in the third store, the customer leaves the store with their hands full. As a person sitting outside and observing, you may think of the following possibilities about these stores.
- You may think that the first store’s products are either low quality, or the product variety is limited, or the prices are expensive, or the salesperson does not know customer behavior. That is why the customer left the first store without buying anything.
- You may think that the second store’s products are high quality and the prices are reasonable, the salesperson knows the rules of behavior with customers well, but because the product variety is limited, the customer left the store after buying one product.
- You may think that the third store has a wide product variety, its products are high quality and inexpensive, and the salesperson knows the rules of behavior with customers very well. That is why the customer left the third store with their hands full.
Taking these possibilities into account, let’s give all three stores an evaluation score out of 100.
- First store: 10 points
- Second store: 50 points
- Third store: 100 points
The YouTube algorithm works in exactly this way. As in the example I mentioned above, the algorithm observes YouTube channels from the outside and gives these channels an evaluation score. The higher the evaluation score, the higher the number of views of the videos. Remember, your YouTube channel is your store. The more satisfied the customers, meaning the audience watching your video, are with you, the higher score you will have. And the YouTube algorithm highlights your videos in every ranking factor. YouTube ranking is not only search results ranking, but also recommended videos ranking. The algorithm analyzes user behavior on your videos and, as a result of this analysis, decides whether your videos will be recommended to other users or not.
Which behaviors in videos are analyzed by the YouTube algorithm?
The following segments are the factors that constitute user behavior.
- Average watch rate of the video
- Video view count
- Number of likes and dislikes
- Number of comments and whether the comments are negative or positive
- Number of subscribers gained by the channel thanks to that video
Although these segments are accepted as user behavior, they are not sufficient for a video to be recommended. For a video to be recommended to a user, the algorithm analyzes that user’s general internet behavior, interests, demographic information, and most importantly, what they search for the most on YouTube. The algorithm brings together the data it obtains and shows the user whichever video seems more interesting to them.
As you saw in the three-store example, it was clearly explained in the end which store received a higher or lower evaluation score and why. The same logic is applied on YouTube, and it is possible to see this evaluation in reality on your own videos. When you open and watch your video on a computer, the analytical data presented about that video by the VidIQ tool appears on the right side of the video page. If you do not see this data, it means that you are not using the VidIQ tool yet. I will talk about VidIQ in more detail in the lessons dedicated to YouTube SEO. Among these indicators, there is also an evaluation score that reflects the overall performance of the video, and this score helps to understand how the YouTube algorithm “evaluates” your video.
What is the main goal for the YouTube algorithm?
At this stage, you should now understand that for YouTube, the main issue is not the video, but user satisfaction. The algorithm does not highlight a video because it is “good,” but because the user is satisfied with that video. In other words, YouTube does not look at what you want to explain, but at how the user behaves while watching the video. There is a point where many people are mistaken: they think that if they write a good title and get clicks, that is enough. However, the click is only the beginning; the real decision is made after the click. If a user enters YouTube and:
- watches videos for a long time
- moves from one video to another
- does not leave YouTube
The algorithm evaluates this situation as high quality. That is exactly why YouTube highlights channels and videos that keep users on the platform more. For example, the YouTube algorithm brings forward videos that have the following characteristics:
- Videos that keep the viewer until the end of the video
- Channels that can make the viewer watch another video after one video
- Videos that the viewer reacts to (like, comment, share)
- Videos that cause the viewer to subscribe to the channel
The basic conclusion that emerges from this is: to achieve success on YouTube, it is necessary to focus not on “tricking” the algorithm, but on satisfying the user. Title, description, and tags are important, but these are the factors that open the door. What is inside the store determines everything. In other words, your content, your narration style, the rhythm of the video, and the benefit it provides are more important. In the next lessons, I will explain with real examples how to optimize each of these behavioral factors separately, which mistakes pull videos backward, and why the algorithm does not “see” you. If you have come this far, you are now on the side that understands the system, not just someone who uploads videos to YouTube.
