Big Data: the success story of Netflix

by bold-lichterman

Netflix’s strategy is focused on data analysis. As such, the company has developed its own data visualization tool. The aim is to improve reporting tools in order to communicate relevant information in real time on the state of the environment. This is intended for all departments and trades. Equipping the entire company means allowing everyone to be helped in their decision-making or in their creation process.

Our brains need less than 250 milliseconds to grasp, understand and respond to information in visual form. Conversely, comparing several tables of raw data requires an effort of abstraction and memory which is no longer achievable from a certain volume of data.

A data visualization quality gives managers the means to manipulate large volumes of data to bring out trends. Thanks to dynamic comparison and cross-referencing tools, managers reveal unsuspected information, which can only be revealed through massive analysis of the data.

With the instruments of Data Visualization, Netflix obtains data already compared, sorted and put into perspective. You just have to concentrate on the decision making.

Example of a data visualization at Netflix:


This visualization offers a real-time view of connections in the United States on the Netflix platform. The dataviz highlights performance indicators with a map view on the main screen. On the right of the screen, we watch an incident follow-up, supplemented by performance indicators over time, such as number of customer calls and latency.

The screen is dynamic and customizable by each user. It provides real-time understanding of incidents in relation to connections. Before this screen, evaluating these metrics must have been laborious. The data comes from multiple media and is difficult to access for an average employee. This data visualization makes it possible to monitor its activity every day and to make simple and relevant presentations to the various stakeholders. This is what Netflix calls operational visibility.

The importance of Dataviz at Netflix

One of the next evolutions of the tool will highlight recurrences from the data. The data will be updated in real time and will provide an optimal view of the market. The objective, to bring out anomalies or trends in order to help decision-makers, reports the tech blog from Netflix.

This same logic applies to the creation of series. For example House of cards. Netflix’s flagship series, was created based on analysis of subscriber data.

Create series based on consumer tastes

The data analyst analyzed the audience of the original English series. They discovered that this same audience was a fan of actor Kevin Spacey and films by director David Fincher, following analysis of subscriber interests.

This strategy allows Netflix to create blockbuster series. The company renews more than 80% of its seasons. The average of lindustry is 25%. Data analysis offers a clear competitive advantage. It makes it possible to understand the needs of consumers and to provide a targeted offer.

In this regard, Netflix has made 10 different trailers for the House of Cards series. Each targeted according to audiences. So fans of Kevin Spacey watched a trailer showcasing him. While fans of series with female protagonists saw a trailer focused on the female characters of the series.

Unify understanding of data

Data Visualization is the solution implemented by companies like Netflix, Twitter or Amazon to enhance their data.

Netflix owes its growth to its strategic use of the data collected. Thanks to its 75 million subscribers, the company has a phenomenal amount of information about its users. This strategy of Big Data management offers a new approach to reporting and the creation of series.

Moreover, the data visualization unifies the speech. Raw datasets create ambiguity, all readers can draw their own conclusions.

Data visualization negates this effect and makes data easy to share and accessible. Netflix uses dataviz tools to achieve communication objectives, reporting and production. Managers have their data in real time. They monitor business activity while benefiting from predictive analytics, allowing them to make more informed decisions.