Netflix is an appealing Super Cruncher case because it serves as a practical and exciting application. Nowadays with the availability of different types of user data, Netflix is one of the major companies driving recommender systems and applying large-scale data mining and machine learning data models. When the Netflix Prize was launched in 2006, it put a spotlight on the key role of data mining algorithms in our fast paced digital era. Netflix uses terabytes of information spread in over 190 countries and 98 million members. Through their business success, many companies have discovered the significant value in integrating user-based recommendations in order to provide a tailored, more satisfactory user experience.

This Case File provides an analysis of Netflix as a Super Cruncher of online recommendations and aims to answer the previously stated research question. In the Reference Set page, we dig deeper into the various elements that make up Netflix's personalized recommendations. First, there is an overview of different types of recommender systems, and it is followed by a break-down of the components forming the basis of their personalized predictions, such as their recommendation objectives, ranking system, and data sources. Then, we provide a more in-depth review of the science behind their data models, including an introduction to collaborative filtering recommender systems, and how Netflix uses Matrix Factorization and Restricted Boltzmann Machine algorithms. The next section discusses the recent improvements Netflix has implemented to provide a better personalized experience to its member community.

In the rest of the website, we discuss scientific follow-up regarding the topic as well as relevant news articles about Netflix found in the News page. We also include the potential hurdles faced by the company, a critique addressing this topic introduced in the book "Super Crunchers" by Ian Ayres, as well as the societal impact brought by Netflix's personalized recommendations.

Since the Internet emerged in the 90's, there has been a rapid shift in technology, both in hardware and software. The rather exponential growth of hardware based on transistor generation and development, as stated by Moore's law in 1965, led companies to plan their production, research, and development strategies towards sophisticated electronic digital advancements. Meanwhile, the birth of Software as a Service (SaaS) and the emergence of e-commerce and social media networks gave way to the formation of Big Data and data centers. In fact, cloud services have become ubiquitous and accessible through multiple devices (smartphones, tablets, notebooks, smart TV's) as on average, people own at least two of these and have become part of their daily lives. In this social context, companies have had the need to continuously adapt and maintain a flexible business model to keep up with industry and societal changes.

Netflix, an American company founded in 1997, was one of the pioneers in using the Internet as a business opportunity. They were able to tap into a new market in the entertainment industry, leaving behind competitors that failed to adapt to the new online environment, such as Blockbuster. Netflix introduced a new concept in the consumption of movies, which first started as a platform for online movie rentals and now has transformed into the most popular online streaming service today. In particular, their initial business model included DVD sales and rentals, although when the demand for physical formats decreased they saw the opportunity to expand the business and introduced streaming media in 2007 while retaining the DVD and Blu-ray rental service. Their success has also been driven by super crunching user data to make personalized recommendations for its members, presenting them with content they are likely to enjoy. The company has grown internationally, making their streaming service available for an accessible monthly subscription. As of 2017, they have 98 million subscriptions (Statista, 2017) spread over 190 countries around the world (Wall Street Journal, 2016), leading them to attain terabytes of information from its user interactions. In just one quarter of 2014, Netflix streamed over 24.021.900 terabytes of data (cordcuttersnews, 2017).

Moreover, Netflix entered the content-production industry in 2013 by debuting its first series, House of Cards. Since then, it has significantly expanded the production of both original films and television series, featuring them as "Netflix Originals" through its homepage and library of content. Netflix released an estimated 126 original series and films in 2016, more than any other network or cable channel (Netflix, Inc. History, 2017).

As a result, Netflix is an interesting Super Crunching case. From the beginning, they have incorporated the tastes and preferences of their target consumers through data input, crunching and forecasting data to support its members future decisions and create a pleasurable experience. They are in the forefront of content recommender systems and have played a crucial role in the development of collaborative filtering algorithms. Their dedicated focus in user experience, data analysis, personalized recommendations and platform scalability has allowed Netflix to be a strong competitor in the industry and be a compelling Super Cruncher case.