Netflix

How Netflix is championing Big Data

In one my posts on Big data, I tried to simplify the concept of Big Data. This one will prove why Netflix is the champion in using data to drive inferences and put them into action.

Netflix is over time become a data driven company. With over 50 million subscribers, Netflix has the tools and resources to channel the humongous data is collects from its subscribers. Not only does it use the data to identify what shows to commit to, but it can now take additional steps to ensure that the show reaches the right audience. Netflix collects a lot of data to understand how its users behave and what their preferences are, what people watch, when they watch, where they watch, what devices they use, ratings, searches, when users pause or stop watching and much more.

Below are a few remarkable decisions under consideration by Netflix via big data

Price discovery for each customer

Netflix pricing
Tracking the customer closely can multiply your profits

According to this article in Washington post, Netflix could vary its price if it had enough information on each user to know how much they might pay. Taking into account IP, device, age, past visits, OS used and more variables, throwing them into a database and calculating a charging threshold can conceivably be termed big data and Netflix is in process of deriving a process which would help it in achieving this goal.

Via Modeled Behavior, a new paper from Brandeis University economist Benjamin Shiller shows that combining traditional demographic data with information about Web browsing habits led to much more accurate predictions as to when a consumer would commit to a Netflix subscription. Furthermore, tailoring Netflix’s prices according to consumers’ estimated willingness to pay — a process known as first-degree price discrimination — led to higher profits in simulations. (Second- and third-degree price discrimination respectively occur when a business either changes the price of its goods based on the amount you buy or changes the price by grouping customers into categories, such as veterans or seniors.)

Improving video streaming

In 2008, there was an outage that left it’s customer without service for three days. This was the trigger that forced the company to turn to big data. This marked the change for the company when it switched from renting DVDs to providing digital videos.

Hadoop processing power allows the company to run massive data analyses, such as graphing traffic patterns for every type of device across multiple markets. That effort helps Netflix improve the reliability of video feeds on different platforms and plan for future growth of streaming movies and shows. For example, the greater processing capabilities can allow engineers to see where traffic on the network is running slower, allowing them to plan for additional network capacity. The technology—which can manipulate larger data sets– also helps Netflix to better analyze customer preferences so that it can make improved recommendations.

Predict viewing habits of customers

Netflix can collect and study subscriber data such as time of day that movies are watched, time spent selecting movies and how often playback was stopped (either by the user or due to network limitations). This can effect customer satisfaction and measured based on ratings given to movies, models can be built to predict the “perfect storm” situation of customers consistently being served with movies they will enjoy. Happy customers, after all, are far more likely to continue their subscriptions. This modelling can also help in suggesting subscribers with similar movies that they are likely to enjoy. Such data will also help Netflix identify opportunities in the area of customer servicing that they can easily tap into.

Finding the next hit series

House of cards netflix
Voracious appetite for content forced Netflix to outbid tough competition for House of Cards

Netflix had nailed it when it outbid networks including HBO and ABC for the rights to House of Cards. Many still consider this as a fluke and not really a data driven action. Well, as per Netflix data showed that its subscribers had a voracious appetite for content directed by David Fincher and starring Kevin Spacey. It was so confident that it fitted its predictive model for the “perfect TV show” that is bucked convention of producing a pilot, and immediately commissioned two seasons comprising of 26 episodes. Every aspect of the production under the control of Netflix was informed by data – even the range of colors used on the cover image for the series was selected to draw viewers in.

Netflix has used Big Data and analytics to position itself as the clear leader of the pack. It has done this by taking on other distribution and production networks at their own game, and trumping them through innovative and constantly evolving use of data. It faces tough competition from Amazon (who acquired Lovefilm) and Apple’s soon to be launched TV service. Only time will tell who will emerge out as a clear winner but the race to develop more accurate and insightful analytic strategies will be a key decider and big data is certainly the best bet to emerge as the king of this category. For now, Netflix id sitting on a goldmine of data – which has immense potential to change the way this category works and also has the power to influence Hollywood entertainment.

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