Have you ever noticed that once you finish watching one episode of your favorite Netflix show, an interesting recommendation appears that you just can’t ignore? That’s all because Netflix works for you by deploying AI/ML and data science to match your preferences with existing content on the platform. Artificial intelligence and Netflix are now connected with 260 million engaged users, accounting for a total revenue of $33.724 billion in 2023.
Today, our article explains how Netflix uses artificial intelligence to enhance and personalize the recommender system and the applicable AI recommendations algorithm. It also explores the main benefits of the Netflix recommendation system for both the viewer and the company. So, let’s start from the basics – Netflix’s history.
Introduction: Why Millions of Viewers Fell in Love with Netflix?
If we travel back to the early 2000s, the entertainment landscape was vastly different from what we see today. However, with the rise of entertainment giants like Netflix, people were given access to an immersive library of content, and thanks to its user-friendly interface, Netflix managed to capture the hearts of millions of viewers worldwide.
Netflix, founded in 1997 by Reed Hastings and Marc Randolph as a DVD rental service, transitioned to streaming services in the late 2000s as the rental business struggled to stay alive. In the early days of streaming, Netflix focused on licensing existing TV shows and films. However, the wind of changes came with the production of original content. Hits like “House of Cards,” “Stranger Things,” and “The Crown” proved Netflix is capable of creating compelling and high-quality series that resonate with viewers of all ages.
Yet, the numbers can describe Netflix’s presence and influence on the audience better than words. As of 2023-2024, Netflix boasts over 260 million subscribers globally in over 190 countries, with the largest share in Europe and America. Interestingly, users spend an average of 3.2 hours each day consuming the content on the platform. The audience is 51% female and 49% male.
But why does it attract so many users? The two main reasons are:
- The great range of licensed TV shows and original productions, with the top show, The Night Agent, gaining around 812 million viewed hours;
- Clever use of AI to provide the best viewing experience.
Even now, when Netflix is proudly positioned as one of the leading OTT (over-the-top) platforms, the company hasn’t stopped searching for new ways to improve its quality and competitive edge with investments in cutting-edge technology like machine learning and artificial intelligence. With the vast AI experience in mind, Netflix has stated its desire to spend 8 billion dollars for this year’s content production.
Netflix and AI
The company’s path to applying AI started by adapting to changing viewer preferences and embracing new technologies that will keep Netflix atop the competitive streaming market. Today, a mix of artificial intelligence, data science, and machine learning aims to engage all audiences with the movies they most prefer.
With the global market for OTT services predicted to jump to $1,079.1 billion by 2030, the further deployment of AI technologies is inevitable. This key market driver requires better user experience, high-speed loading, feature recommendations, and fast problem-solving services.
The real story of Netflix AI recommendations started with the production of House of Cards and the need to promote it to a large audience segment. By integrating AI, ML, and data science, the tech team worked on learning consumer behavior, preferences, and watch patterns. Based on the researched data, Netflix released ten totally different trailers for House of Cards that could attract a variety of audiences. How does it work?
The idea is the consumer will see exactly what he or she likes. For instance, a female consumer saw the trailer with the frame of her favorite actor, while another consumer saw the frame that demonstrates her preferred type of story plot. This technique helped the audience find the show and encouraged them to watch it.
By smartly implementing artificial intelligence, Netflix has proven that computer science attracts more users to its streaming service and can adjust consumer behavior. But, the most remarkable discovery comes with applying an AI recommendation engine and increasing the platform’s revenue.
How Netflix Uses AI: Netflix Recommendations Algorithm
AI is changing the world by using data science research to enhance the user experience.
Netflix’s AI recommendation engine analyzes massive amounts of data, including viewing habits, ratings, searches, and time spent on the platform, to curate personalized content recommendations for each viewer.
Now let’s split the whole Netflix recommendations algorithm into a more simplified process so we can digest it and understand the whole idea:
- Netflix, using artificial intelligence, identifies what you watch, how many times you click the same video, and how long you keep watching it;
- Based on the initial preferences of the user, Netflix identifies the preferred types of movies and shows using the following factors:
- The kinds of movies you watched previously
- Whether you finished watching previous shows/movies
- How quickly have you watched all episodes of a series
- What movies and shows are watched now by users with the same preferences
- Next, the AI rates preferred shows and movies based on their popularity rankings and creates a list of recommendations for what to watch next.
- As in the above step, new recommendations keep appearing on the playlist based on the previous watching history and similar popular ratings.
This amazing algorithm is simply called Netflix AI, the product of technologies and entertainment.
Use Cases of AI/ML/Data Science in Netflix
Netflix’s commitment to providing excellent user experience and engaging more viewers to the platform is elevated by its use cases and best practices. By understanding the power of new technologies, businesses can integrate AI to enhance content, customer support and communication, behavioral predictions, and increase ratings.
- Netflix Machine Learning
While machine learning helps to process recommendation lists, it also helps to find the most suitable shooting locations for upcoming movies and shows. For instance, the system learns the locations with the less rain likelihood for any day of the week and other factors helpful in problem-solving and decreasing costs under certain circumstances.
Moreover, with the help of machine learning and data science, teams can now easily determine the schedule and cost of the cast crew.
Furthermore, machine learning allows tech teams to monitor users’ activities and viewing patterns in real-time to determine the platform’s peak hours. The obtained data is used to cache the local servers and speed up loading.
- Personalization & Search
Its AI-driven personalization and search capabilities are at the heart of Netflix’s success. Without personalization and AI recommendations, the viewer won’t be attracted by the appeal of the next series and won’t stay on the platform for as long.
Despite an extensive library of content, all users have their own tastes and preferences: some are looking for fantasy, some are obsessed with trending K-drama, and some prefer movies only with their favorite actors. In other words, not every user will click the first movie they see to find out whether they would like it.
To resolve this issue, Netflix uses AI to analyze users’ watching history and time spent on the show to select similar movies that the user will enjoy. The result is personalized, engaging content.
- Auto-Generated Thumbnails
Netflix AI works perfectly by examining thousands of video frames and capturing the one frame that is most appealing to the viewer—the thumbnail. Next, this thumbnail is displayed on the movie recommendation list, increasing the likelihood of people clicking on the movie or show.
Moreover, thumbnails appear on the playlist not randomly but based on the clicking rates of other viewers with the same interests. If you are addicted to Netflix, you have probably noticed the same pattern over and over again. That’s how Netflix identifies which thumbnail works best for you.
- Streaming Quality
Another critical case of AI for Netflix is optimizing streaming quality. Through ML algorithms, Netflix continuously monitors network conditions and adjusts video quality in real-time to ensure a seamless viewing experience.
By analyzing bandwidth, device type, and location data, Netflix can deliver the best possible video quality while minimizing buffering and interruptions. As a result, people are likely to stay on the platform due to high-speed performance and faster content loading.
- Content Quality Checks
Netflix uses AI to identify and categorize content based on various factors, including genre, language, and maturity rating. This enables the platform to uphold quality standards and ensure content meets viewer expectations. As a result, the Netflix recommendation engine promotes high-quality and relevant content to users, enhancing the overall viewing experience.
Benefits of Netflix AI
Netflix’s artificial intelligence recommendations benefit both viewers and Netflix itself, paving the way for a more engaging and satisfying entertainment experience. Let’s make a breakdown and see the results of AI magic.
For Netflix:
- Increased Engagement. By providing personalized recommendations, Netflix can keep viewers on the platform longer, reducing exit rates and increasing customer satisfaction. This leads to higher viewer engagement and more time spent watching content.
- Keyword Upscale. By tagging films and TV shows with keywords related to genre, theme, cast, and more, Netflix’s algorithm can identify patterns and similarities between content and recommend relevant titles to viewers. This way, recommendations are more accurate, diverse, and appealing to a wide range of people.
- Content Promotion and Discovery. Netflix’s AI recommendations let viewers explore new genres, discover hidden gems they have yet to notice, and broaden their entertainment horizons. As a result, more traffic is attracted to the platform.
For viewers:
- Personalized Experience. Instead of sifting through a vast library of content to find something to watch, viewers are presented with a curated selection of movies and TV shows that align with their interests and preferences. This not only saves time but also enhances the overall viewing experience.
- Discovering the Next Big Show. If you are a big fan of watching movies and TV shows, you don’t have to spend hours searching for the next big hit. Netflix will recommend all possible great shows for you according to your previous viewing history. Indeed, Netflix’s AI feature saves tons of time.
Conclusion
The rise of Netflix AI can be attributed to its innovative approach, diverse content library, and user-centric focus. By focusing on personalization, streaming quality, and content quality checks, Netflix continues to set the standard for digital streaming platforms.
Adopting best practices in machine learning, data science, and AI yields incredible results. By embracing Netflix’s success, businesses can maximize their turnover, increase leads, and improve customer experience. If you want to learn more about your business potential, contact our team, and we will share our expertise in AI solutions.
Finally, let’s give a round of applause to Netflix for its amazing user experience and unbelievable movies. Now, let’s go watch some Netflix!
