Today, who doesn’t know netflix? This company is a movie streaming service provider whose growth is quite rapid. New netflix logo just imagine, in 2011, the number of netflix users was still at 24 million people . But a decade later, the number has jumped to 213 million users! Of course there are many things that influence the success of netflix. Starting from an interesting selection of films, to a user-friendly platform. In addition, there is one more factor that plays an important role in the growth of netflix, namely: accurate movie recommendations . So, how does netflix present movie recommendations that are right on target? The answer is to use big data . In this case study, we’ll thoroughly explore how netflix does it. Let’s listen! Contents hide 1 overview of netflix 2 how does netflix leverage big data? 3 what benefits does netflix get from big data? 4 what lessons can be taken from the netflix case study?

How Does Netflix Leverage Big Data?

Netflix at a glance do you know? Even though netflix is ​​currently popular as an online streaming platform, this company actually started as a dvd rental business. Netflix was founded in 1997 by marc randolph and reed hastings. At first, they only rented dvds per disc, but then they started introducing a subscription business model in 1999. Old netflix logo on netflix case study as netflix developed, they finally launched a movie streaming service in 2007. With its new business model, netflix is ​​also trying to provide a more enjoyable movie watching experience for its users. One of the efforts they have made is to B2B Email List provide a recommendation system , which is a feature in which netflix provides movie recommendations according to the user’s taste. Illustration of movie recommendations on netflix case studies but how? How many netflix users are there? Their tastes must also vary.

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What Benefits Does Netflix Get From Big Data?

So, to overcome this, netflix uses data science . How does netflix leverage big data? Before discussing how netflix uses data to create an accurate recommendation system, you must first know the two types of recommendation systems that are commonly used: content-based system – a recommendation system based on the movies watched by the user. Collaborative-filtering system – a recommendation Mobile Lead system based on similar user profiles. So, if profile a and profile b are similar, profile a will receive the same film recommendations as profile b. Then, which system is used by netflix? Not both. Netflix uses a hybrid recommendation system , which is a recommendation system that is a combination of content-based and collaborative-filtering systems. In other words, this system can provide more accurate recommendations than the two predecessor systems.


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