Netflix relies heavily on its recommendations system, which is responsible for suggesting what you may like. The recommendation system is why different accounts and profiles have other titles on the home page. But have you ever wondered how Netflix recommendations work? This is everything you need to know.
How Netflix Recommends Content to Its Users
Netflix uses a variety of pointers to find the movies and shows you will most likely want to watch. The recommendations system is essential as it can be challenging for you to sift through the hundreds of titles available on the platform. Here are some of the key points the platform's recommendation system considers.
1. Your Watching History
Netflix places a massive influence on what you watch on the platform to recommend what you may want to watch next. Most noteworthy, your watch history informs the Because you watched section on your home page, which includes titles similar to one of your recently watched titles.
By now, you should know that Netflix keeps a tab on everything you watch on the platform. You can even download your Netflix watch history to check what you watched in the past and when.
2. Your Ratings
The second factor that informs Netflix's recommendations algorithm is your ratings. Ratings tell the algorithm the type of titles you'll like and those you don't. You can even use the double thumbs-up feature on Netflix to let the platform know what you really love. With this information, you are most likely to see titles similar to those you liked.
When you create a Netflix profile, the platform asks you to select a few titles you like. Even if you don't select any, what you watch will inform the algorithm of your taste.
3. Favorite Titles From Other Users With Identical Taste
In this regard, you have less control over what Netflix recommends. The algorithm placed you in a specific category based on your taste. If other users in the same category like a particular title, Netflix will also recommend it to you.
In a 2013 interview with the Wired, Xavier Amatriain, Netflix's engineering director at the time, said collected "data is fed into several algorithms, each optimized for a different purpose. In a broad sense, most of our algorithms are based on the assumption that similar viewing patterns represent similar user tastes."
Similarities have multiple dimensions, though. It also includes metadata, ratings, year of release, and others, apart from the title.
4. The Title's Information
You may also see a title in your profile based on its information. Netflix considers title details like the release year, actors, category, genre, and others. Your duration of watching is also necessary, which will inform the algorithm to include those that fall within that category. If you prefer the latest releases, Netflix will recommend more of them.
"By looking at the metadata, you can find all kinds of similarities between shows. Were they created at roughly the same time? Do they tend to get the same ratings? You can also look at user behavior—browsing, playing, searching," Carlos Gomez-Uribe, former Netflix VP of product innovation and personalization algorithms, told Wired in 2013.
5. Time of the Day, Devices You Use, and Location
Netflix also considers the time of the day or week you're watching a title and on what device. The two might sound pointless, but there is a variation in behavior when watching at different times of the day and on different devices.
The location also influences your recommendations. If others highly rate a movie in your region, you may also see the same in your suggestions. For instance, Netflix's Top 10 row displays what other users in your region watch, which helps you avoid asking other people for recommendations.
5. Other Factors That Influence Your Netflix Recommendations
To create a personalized home page and recommend titles you might like, Netflix considers many other factors. As reported by GigaOM in 2012, Netflix's Senior Data Scientist, Mohammad Sabah, hinted that your search data is also important.
Sabah also said that the company tries to predict what you'll watch next by considering what other users watched after finishing a specific movie or TV Show. For example, if more people watch movie B after watching movie A, Netflix will probably recommend you to watch movie B next when you finish movie A. The critical thing considered here is the transition probability, which might also depend on other factors, including overall popularity.
The Power of the Algorithm on Your Home Page
Content recommendation is tough; no wonder Netflix uses different algorithms for the task. You can see the real power of Netflix's recommendation engine on your personalized home page. The company ranks titles in rows on the home page with specific themes you may be interested in.
"Most of our personalization is based on the way we select rows, how we determine what items to include in them, and in what order to place those items," an article from Netflix's technology blog reads. Netflix explains, "Each row represents three layers of personalization: the choice of genre itself, the subset of titles selected within that genre, and the ranking of those titles."
Rows whose content you will most likely watch come at the top. Within the row, more suitable content is given priority and shown on the left (or right if you use right-to-left languages in your account).
How to Refine Your Netflix Recommendations
Netflix's recommendations system is not perfect by any measure. It may work for you today, and one week later, work against you. Fortunately, you can recalibrate your Netflix recommendations if recommended titles don't fit your specific taste.
Now that you know the different factors that inform Netflix's algorithm, how can you fix your recommendations? Well, there are several ways to do it.
The platform includes a way to delete your Netflix watch history, adjust incorrect ratings, and jump-start the algorithm by creating a new profile. However, you don't need to rely entirely on Netflix's recommendations algorithm. Various third-party tools can help you find good movies and TV Shows on Netflix.
Big Data Is at the Core of Netflix's Recommendations Engine
It's easy to get lost in the details of what powers the Netflix recommendations system, and these can only be achieved due to the company's rich data collection practices. By looking at how you and others interact with the service, its different algorithms are more informed on what you'll probably watch next.
This data also offers Netflix more advantages in creating programs its massive user base is most likely to watch.