Just because PageRank destroyed internet search engine competition and ushered in an era of Google domination that not even its visionary founders foresaw doesn’t mean the question of how to optimally rank content has been solved. Wired magazines “The New Rules of Hyper-Social, Data Driven, Actor-Friendly, Super-Seductive Platinum Age of Television” details that the hunt is on for a better way to find out which television shows and movies work with watchers and which don’t.
Traditionally, this ranking was done with something called a Nielsen number, which was derived out of how many of the select 25,000 households that make up the database’s population, were watching a show when it aired on their television sets. Only recently have programmers come to understand how incredibly inadequate this method has become in light of technological advancements. Consider my case: I haven’t watched a show when it aired on a television set for nearly three years, but I’ve stayed up to date on my favorites like NBC’s “The Office” and AMC’s “MadMen” via online streaming services, like Netflix, Itunes and Amazon Instant Video. I, like many consumers, find that buying episodes as they come out is cheaper than a monthly cable subscription (which is $600 per annum if you pay $50 a month – or 300 episodes of something that you can keep forever). The problem with consumers like me is that networks haven’t figured out how to factor in my viewing habits to the shows performance metrics. Even if streamers like me watch shows religiously and number in the millions, networks exclude our ranks when deciding whether to keep a show alive or not. This is a problem of ranking. How can a network do a better job of deciding which shows to keep and which to nix when there are so many platforms to get content on and so many different methods consumers can employ to enjoy it?
The answer to this question has yet to be definitively answered. Interested parties will be waiting with baited breath – the following five years is bound to have a revolution or two in television network economics. One bold front runner is Amazon, who has been reportedly planning to use their massive data collections to observe how viewers react to storylines, twists, genre’s, character types etc. to start churning out ideal shows and movies. Not long ago, Amazon was rumored to be doing the same thing with it’s Kindle ebook service. By compiling information on what parts of which books readers were abandoning the story at, and which books consumers were abandoning their boring books for, Amazon could theoretically derive a formula (or probably several) for the most engaging book possible. Amazon could rank a television show based on how many viewers watched in one sitting, how many times they watched it again and how quickly they searched for the next episode. Along with factors like how many people are watching the show relative to how well it was advertised, and how many references are made to the show on social media there are, Amazon could well find out what type of plot it’s Studio’s division should be producing. Until that day, we’ll have to put up with annoying premature cancellations and show’s that never seem able to die because those secret 25,000 households haven’t caught on to Hulu yet.