Some areas in which NETFLIX uses MACHINE LEARNING for:
Unlike most production companies, Netflix behaves as a tech enterprise. They don’t create content solely based on the creativity of a few writers or content creators. The first area where they use data is to better understand us as consumers so they can exactly understand what we're watching, browsing, and skipping. Most of the content providers haven't got the same ability, but Netflix does because they're so big, they have huge volumes of data and their understanding of us as consumers is becoming more and more granular. They looked at horror movies, for example, so they thought, okay if you watch 70% of a film and then suddenly you stop watching at the end of this film, this probably indicated this is almost too scary for you to finish. And so they released the top ten scariest movies that we're too scared to finish. So all this data gives them a hugely granular insight into customers. And they use this data to produce new content because they know what we like and dislike. So in the past, there was this fear that by looking at what customers like and dislike, you would only have those big blockbuster movies that everyone likes. But what Netflix actually understood well is that there are lots of different niches that people like to watch, and if they produce content for those niches, they will have a ready audience for those bits of content. What is interesting is that this is making their content extremely successful. So the success rate of newly produced content in traditional TV is around 30 and 40%. In contrast, Netflix is now at 80%, which is leaving its competitors behind because they now use its customer understanding to drive content and new productions.
The second area where they use AI and big data is to recommend us new movies and new TV programs to watch. What is interesting is that 80% of what we watch on Netflix is now driven by their recommendations. So this is something completely unprecedented. And Netflix has put a lot of effort into fine-tuning their algorithms that will understand us as consumers and then give us content and recommend content for us that we will actually enjoy. Consider the example. Let's say there's a moviegoer named Maria who enjoys romcoms but also likes action adventure movies. And Paul also enjoys adventure and romance, but he also loves superhero movies. So because Paul likes this new superhero movie and Maria has shown these same kinds of preferences, Netflix recommends this new movie to Maria. The annualized cost of Netflix's recommendation engine is close to $1 million. And its only purpose is to enhance the customer's overall satisfaction.
The third area Netflix uses, AI and machine learning is to auto-generate thumbnails. They obviously realize that we only spend a limited time trying to find the next film that we want to watch. And what they found is that we only spend a minute, a minute and a half looking for films and in this time we scan between ten and 20 titles. So they only have a very short amount of time to show us something that we might or might not be interested in. So they show these little thumbnails with their titles, but the thumbnail could be anything, any scene out of the movie. So they need to figure out which scene to show you. And again, what they're now doing is they're using machine learning to extract the thumbnails, the algorithm has chosen we will like best. So this whole process is now automated dynamically and it is personalized - you see a different thumbnail for the same film compared to your friend because they know what you are responding to. Recently thumbnails even became “alive”, so we can see a short trailer only by hovering the mouse.
The fourth area where Netflix uses AI and big data is their streaming optimization. When you’re watching a show, what’s the worst thing that can happen? Buffering. Buffering can be a huge issue no matter what streaming service you use. People tend to immediately exit the platform after waiting for a few seconds because of buffering. Netflix is well aware of this issue.
When you sit at home, your broadband speed varies. What they don't want to do is to lose quality. So they are now predicting speed at different times and then their machine learning algorithms determine what films people might want to watch and whether they want to cache them in a regional server to make it faster to download. Netflix is monitoring the quality and what impact it has to be able to automatically scale down or scale up the quality of a movie streaming to your house. Netflix AI is able to foresee how many subscribers it will have in the future. Therefore, it has room to make more technological advances. Netflix improves video quality for viewers even during busy viewing times by placing video assets near subscribers in advance.
Another really cool area that Netflix is now using AI in their pre-production, especially around finding a location to shoot a movie in. Netflix isn’t just a streaming platform for showing movies and shows. They are also a production company. Producing unique content helps to increase their revenue and profitability. So far, this strategy has worked amazingly well because, over the years, the amount of Netflix-original content has increased substantially.
Every show requires a shooting location. Netflix uses machine learning to determine which shooting location would be perfect for a particular show or movie. For example, Artificial intelligence tools will look at things like the actors, their availability, where they're located, the camera teams, their availability and where they are located, weather, the possibility of getting a permit, shooting requirements (city, desert, village, etc.) and many other relevant factors. And all of this information is now used to identify the best places. And again they will look at what sort of scenes are required. So then algorithms recommend areas, cities, and places where they might want to shoot a movie.
And the final area Netflix uses AI is in the post-production. So the editing process, this was done pretty manually in the past. Nowadays, the editing is still done manually, but the quality checks are driven by AI. AI will look at where do we need some human quality control? Where and when in the past have there been mistakes? Maybe sinking a subtitle to a certain scene? If this was a problem, AI will flag this up. This has made this whole post-production process a lot more efficient and effective.
Netflix is one of the most loved platforms among global streamers. Hence, it becomes the obligation of the platform to consistently satisfy its customer base. With the help of AI/ML/Data, Netflix is already thriving in the industry. In fact, there might be more to come.
As you can see from Netflix's expertise, you can implement ML into areas which require a lot of analytics and statistics and make it on autopilot to improve decision making which influences your business. There are areas in your business where you can collect data and analyze it on autopilot mode to make important decisions. Let's get in touch, and we can guide you on how we can do it for you and your business.