I just finished watching "Breaking Bad" for the 43rd time (I may watch it again...), but every time I was binge watching it, I could see Netflix recommending me shows, similar to "Breaking Bad". I think it's time to talk about how the algorithm tailors our way of thinking to its benefit. Netflix changed the game, entertainment industry had to adapt to survive due to it. How do it Netflix do this? From time consuming to #netflixandchill, entertainment is now just a click away. Netflix offers hundreds of TV shows and movies, more than 75-80 percent of the TV shows and movies people watch on Netflix are discovered through the platform’s recommendation system. So, basically when you think you are choosing the shows and movies you want to watch, its netflix's recommendation algorithm doing it for you.
What is this Netflix Algorithm?
Simple answer: Machine learning and predictive system.
The recommendation algorithm works by collecting and putting together data collected from different places, every time you click, search or perform any activity on Netflix. "Recommended rows" are designed and crafted according to your viewing habits. That’s why you can tell when your friends/family members have been using your account to watch "Friends" or "Lucifer". In this case, algorithms are often used to facilitate machine learning. Systems like Netflix based on machine learning rewrite themselves every time a new information is feed into the database using your account.
(Every time you click and play your favorite TV show or a movie, Netflix is collecting data and information that reforms and registers on the algorithm and refreshes it.)
Todd Yellin, Netflix’s VP of product innovation, told Wired in 2017: “what we see from those profiles is the following kinds of data — what people watch, what they watch after, what they watch before, what they watched a year ago, what they’ve watched recently and what time of day”. So, the basic equation is, viewing habit = machine learning and identifying patterns.
Netflix works with taste groups, each user is categorized into different groups. Generally the groups are made of the viewing pattern of the individual, his habits and preference shape the taste group he would fit in.
Each taste group is read, analysed and you are allotted to one of these groups.
They have built a set system that tests a set of images for many titles on their main screens helping them display a relevant image to drive engagement and influence user behavior.
Netflix has a new recommendation algorithm based on artwork. It shows up unique tailor-made images to its subscribers. These images are specially designed to keep you stuck in Netflix. So, you are basically feeding the algorithm. In order to facilitate a quick action from user, Netflix takes into account your attention span and therefore the images are designed to be captivating. So, basically when you click on a certain show because it's image grabbed your attention, you know it's Netflix's predictive algorithm reading you. (Netflix ...and binging!)
Recommendations come from the users viewing activity, so if you have been watching Bradley Cooper, you would be recommended his movies on the recommended titles.
Idea of Netflix is simple "Keep the users interested and engaged!", As user I can say they are really successful at it. I think it's safe to say, once upon a time technology was growing with us and for us.....and now its growing on and through us.