But there are some analytic "black holes" that we - the buyers, sellers, and content creators - can't see into. For starters Netflix, iTunes, Amazon, and Hulu. And we are receiving data but there is no uniform reporting or clarity along the chain that would allow us to really do something with that information.
A "viral video" from the last week or two is also relevant to this discussion about data and content. You may have caught this speech from Oscar-winning, Emmy-nominated actor Kevin Spacey at the Edinburgh Television Conference.
In it he discussed his experience getting "House of Cards" off the ground, and how Netflix and similar platforms are affecting the traditional television development model.
Spacey sort of embodies the bridge between old media and new; he is the Artistic Director of the Old Vic Theatre Company in London and the co-founder of Trigger Street Productions and Labs with digital pioneer and social media maven Dana Brunetti.
If you haven't seen Spacey's talk yet (which some of you probably have since it's already had more than 1M hits), I encourage you to watch it.
One of the most interesting things he said was that when he, Beau Willimon and David Fincher met with all the networks in pitching the series "House of Cards," something unique happened at Netflix. They said, and I quote: "we looked inside our data and know our subscribers will enjoy your series -- 'we believe in you.;" (
He also made a point that should be very compelling to content creators in the room about the difference between the traditional TV pilot model and the "straight to series" /"House of Cards" model.
He implied that there would naturally be a different product at the end of these two processes by the very fact of how they operate and strive for success.
Netflix greenlights approximately 13 episodes at once, releasing them at the same time, trusting that the audience is going to allow the story to play out. In the traditional model, networks order about 100 pilots a season, air about a third of them, and decide what they will send to series based on the reaction to more or less one block of 22 or 44 minutes.
The full season approach allows for and recognizes that it can be afforded more patience from the audience. Meanwhile in the network model, makers of TV pilots have to describe everything that's at stake, define all of the characters and their motivations, and wow and cliffhanger their way to a positive response from execs and focus groups in less than an hour.
Spacey talks about how focus groups almost tanked "House of Blues" for all the wonderful characteristics that made it so unique and special, and draws our attention to how both "The Sopranos" and "Seinfeld" developed audiences over 4 or 5 seasons before reaching their peak. Sometimes content needs time to connect with its core audience. And sometimes that might not even happen it a film or TV series' primary window.
At the recent season premiere of season 5.2 of "Breaking Bad," the accumulated audience from the series picking up speed on other platforms - ringing in the highest ratings to date - was called "The Netflix Effect.
People are watching things out of time, on demand, and that very fact is also giving the content more of a chance.
Most of the platforms showing content out of time are creating original series, but the point is the data set is helping them do it in potentially more effective ways, and also helping audiences connect with them, paying dividends back to the creative process.
Of course we know that both Netflix and the networks have data. But the types of data they have are very different.
Over the past decade Netflix has developed a much more complex data set for film and television content viewing. They know everything you and I have ordered since the day we became subscribers. They know if you consistently rate content from different genres, if you're watching "Breasts: A Documentary" in the middle of the afternoon…they even know if you are cheating on your spouse - Have you seen those ads?
I can see the engineer who was puzzled at the behavior of all of these households watching episodes twice. Probably right at the beginning of a binge, and intuiting that it meant someone in the household couldn't wait to get further ahead into their favorite series so they committed Netflix Adultery.
Networks don't have data at such a sophisticated level.
They don't have the ability to see all of the series that you're watching, they can't follow what you’re watching on your office computer, and they definitely don't have insight into what series you are passionate about, evidenced by a weekend of binge watching, willingness to sit through an episode twice to keep your marriage alive, or whether you give a series of film a 2 or a 5 star viewer rating.
The idea here is that access to data is not enough. More so, it's the complexity of that data and the ability to relate it to data about other content that will ultimately allow creatives like many of you in this room the opportunity to make better content. And relate it across platforms.
So if this is a means to richer content and more engaged audiences, where are we with gaining access and analysis of this data?
While we have insight into some of the data, the reporting hasn't evolved with the rapidly increasing viewership patterns. There is still no uniform reporting system that aggregates all data on, say, a film or documentary across all of the platforms.