Many fans would argue that the Netflix original series “House of Cards” is the perfect television show – it has a fabulous production team, compelling leading actor, and stories of drama and betrayal that keep viewers on the edge of their seats. Turns out, this was no happy accident – this and all other Netflix series have been engineered with the use of Big Data and cloud computing to create the ideal television experience. So how does it all work?
Netflix’s bright idea in delivering content
As New York Times contributor David Carr pointed out in an article on the development of how we receive entertainment, executives analyzing viewer data to inform future programming choices is nothing new.
“Film and television producers have always used data, holding previews for focus groups and logging the results, but as a technology company that distributes and now produces content, Netflix has mind-boggling access to consumer sentiment in real time,” Carr explained.
What is new, however, is how specific this information can get thanks to data willingly provided by the millions of users who make up the cloud hosting giant Netflix’s clients. Boiled down, here is how the American version of “House of Cards” came to be – analysts recognized that David Fincher, the show’s director, was a popular director on the site and unlike most videos, viewers tended to watch his work from beginning to end. When examining which actors appeared frequently in movies or television that users would stick with for the duration, Kevin Spacey fared well as did the original British version of “House of Cards.” Although there were other successful artists on the table for the project, Netflix narrowed its scope down to these three major contributors to inform its programming decision, to great acclaim.
When it began to produce its own shows as a part of the video platform, Netflix had plenty of user-provided information to draw upon. With more than 30 million video plays logged each day in its cloud infrastructure, the company employs analysts to make note of emerging trends, both to inform future products and help identify “You May Also Enjoy” options for fans of a certain genre. The company also examines which devices are most popular for streaming and which don’t encourage further watching to decide which they will continue to develop.