There’s no doubt that Netflix’s very first original series House of Cards, about an ambitious U.S. senator, is a hit and has heralded a slew of original programming from the company that at its inception was a DVD rental service. To create it, Netflix used big data–culling stasticial information about the biggest shows on their platform to come up with the concept.
Similarly, Amazon used data to create another political satire, Alpha House. The difference is that Alpha House was not a success.
Data scientist Sebastian Wernicke “has an explanation for why data analysis created two shows that were similar in theme but very different in how they were received,” writes Observer’s Serge Lazzaro. “From his experience, he’s noticed a pattern he believes separates successful and unsuccessful data-based decision making—the fact that this process involves two main steps: 1) taking data apart to analyze it and 2) putting it back together to make use of it.
“’The crucial thing is that data and data analysis is only good for the first part…It’s not suited to put those pieces back together again, and then to come to a conclusion,’ he says. Amazon’s show wasn’t a booming success because they used data all the way. Netflix, however, looked at what users like and used that insight to think up a concept for what they believed would be a hit show, and it clearly worked.”