Here’s How The YouTube Algorithm Actually Works
Many believe that when a video was uploaded to YouTube, the algorithm would “test” it with a group of people. Then, based on the test results, it would either continue to push the content or stop recommending it. However, this idea has flaws and doesn’t reflect how the algorithm truly works. It’s a bit more complex.
Here’s what’s really going on:
User profiling: As people browse and watch videos on YouTube, the platform gathers data on each user. It builds a profile based on what they like, when they watch, how often they watch, and many other details.
Personalized Recommendations: Then, instead of trying to push videos to random audiences, YouTube uses this data to predict what content a viewer would enjoy when they log in. If it thinks your video is a great fit for someone, it’ll suggest it. YouTube then learns from its process to see how well it performed for future recommendations.
Interesting insight: If your video doesn’t seem like the best option—even if that person is subscribed to your channel—it might not show up in their feed.
So really, YouTube's main goal is to match viewers with videos they’ll like the most, based on everything it knows about both the viewers and the content.
But here’s where things get interesting.
Exploration: Sometimes, you’ll notice that a video with very few views or something outside your usual interests pops up in your recommendations. This is called "exploration." YouTube occasionally tries out videos it doesn’t know much about yet, giving them a chance to gather data and see if they might be a good match for viewers down the line.
TLDR: So, YouTube isn’t just testing videos on a small group and expanding from there. It’s more about constantly predicting which videos will resonate with viewers based on the data it has.
If there’s one takeaway here, it’s this: make videos that people will want to watch, and let the algorithm do the rest.
And just a heads-up—this explanation is simplified for clarity. The algorithm is a complex thing, but this should give you a good idea of how it works.