How NetFlix Uses Big Data to Improve Its Recommendation System and Create a Better User Experience

how netflix uses big data

How NetFlix Uses Big Data to Improve Its Recommendation System and Create a Better User Experience

Netflix is well known for its on-demand DVD rental business. In fact, Netflix uses data analytics and big data in nearly all aspects of their business. Today, Netflix uses its proprietary Big Data tools to guide its online film and television selection. Netflix uses data to direct its recommendation engine to produce its customized, personalized recommendations. Data-guided recommendations help Netflix improve their membership satisfaction, customer satisfaction, and their bottom line.

Netflix uses big data to influence its recommendation system. The company recently gave away a $1.25 million prize to the group that came up with the best mathematical model for predicting how prospective customers will favor a movie according to past ratings. The winning team was so impressed by the results that Netflix subsequently adopted their formula as one of the core elements of its recommendation system. Netflix’s goal is to have more than two million subscribers.

Netflix uses big data and user experience to improve its user retention rate. A large percentage of Netflix’s current members left the site within the first three months of opening. However, when they stayed, they found great entertainment and a wealth of information on great new shows and movies. This experience boosted Netflix’s membership and user retention rate. Netflix uses data to guide its recommendations to reduce the time spent visiting the individual websites of potential customers. Additionally, the recommendations generate a more personalized user experience because they are tailored to each person’s needs and expectations.

Netflix uses big data and user experience to improve its subscription rate. Netflix originally started as a DVD-by-mail service to combat price competition from video on demand services such as Hulu and Vongo. At the time, Netflix was profitable and had signed deals with Universal Pictures and Disney for the rights to many of their movies. Fast forward a few years and Netflix now has over two million subscribers and continues to expand at a rapid pace. Netflix’s subscription rate has been able to grow despite competition from similar services because it offers more variety and less expensive fees for individual titles.

Netflix also leverages its massive network of internet users to leverage its recommendation system to strengthen customer retention rates. When someone subscribes to Netflix, they are exposed to a wide selection of television shows and movies. The company also makes it easy for customers to sign up and receive updates and new programs through its online portal and mobile application.

Netflix applied machine learning techniques to refine its recommendation system. Machine learning refers to the process of designing an artificial intelligence that allows computers to make educated guesses about real-world events. Netflix’s system uses a powerful and complex artificial intelligence called the RCTPA or the Natural Classifier. Machine learning enables Netflix to identify all of the differences between what it calls “real” data like TV shows and movies and what it calls “artificial” data like website clicks and app downloads.

The process of refining the machine learning engine, as well as the Netflix application, is known as metaflow. As explained by Jennifercers, who is Netflix’s director of product management, “We used a lot of different machine learning tools… We developed a neural network layer, a quality filter, metaflow, and a feedforward network. We combined these layers to provide better quality and a more complete user experience.”

Netflix’s recommendation system also taps into the power of natural language processing. Netflix users use specific words to describe their favorites on Netflix. Netflix has developed an application called Wordsmith that uses these words to create a comprehensive vocabulary of movie and television content. The resulting ” vocabulary map ” yields a list of terms and synonyms that users can use to find movies and television content they will enjoy. This richer user experience is one of several ways how Netflix uses big data to improve the customer’s browsing experience.