Traditional Pilots vs. Viewer Measurement

Few know and appreciate that one of the best examples of the power, indeed the magic, of modern data analytics is Netflix’s series House of Cards (HOC).


Indeed, HOC registers as one of the most successful TV and video programming introductions of all time. Yet, what is most remarkable is how HOC was developed and introduced. As HOC star Kevin Spacey explained in his iconic YouTube speech, “Netflix was the only network that said, ‘We believe in you…we’ve run our data, and it tells us the audience would watch this series’” (emphasis added).


Netflix replaced the traditional (and very expensive) “pilot” TV test process with intimate knowledge (via intensive data analytics) of the Netflix viewer. Netflix used its sophisticated data analytics as a basis to invest $100 million upfront in HOC; then, as a basis to green light HOC for at least four seasons (thru 2016), and for today’s 39 completed episodes. Today, Netflix producers envision a 12-season collection of HOC, through 2023.


Anther Example: AMC and ‘Mad Men’

Other ways in which data about viewers is being collected are nearly as interesting. AMC, the network home of The Walking Dead and Mad Men, has also taken a fascinating lean toward data collection and analysis.


As noted in a recent, free IBM-New Bay Media whitepaper, Vitaly Tsivin, AMC’s SVP of business intelligence, used IBM’s advanced analytics to get a richer picture of who its viewers are, what they want, and how to keep their attention in an increasingly crowded entertainment marketplace.


“We need to know who’s watching and why, and we need to know it quickly, so that we can decide…whether to run an ad or a promo in a particular slot during tomorrow night’s episode of Mad Men,” Tsivin said.


Much of the challenge comes from having so much information available – hundreds of billions of rows of data from industry providers such as Nielsen and comScore; from channels such as AMC’s TV everywhere live Web streaming app and video-on-demand service; from retail partners such as iTunes and Amazon; and from third-party online video services such as Netflix and Hulu – and the need to analyze data minute-by-minute and viewer-by-viewer.


And CBS, Too

A recent article talked of CBS News Digital (CBSN), a free, ad-supported streaming news network, available on the Web, via mobile and on connected TVs. Providing 15 hours a day, typically, of news-related content, CBSN taps into its deep well of video viewer data and analytics, much of it via social media, to determine what  viewers want to see (or see more of).


The data analysis also helps CBS News strategize what content to promote on its social channels. Additionally, data influences CBSN content in the presentation itself, i.e., if the average age of the viewing audience is 40 years old, a subtle but important change involves dressing male news anchors without ties, and having all anchors stand instead of sit behind a desk occasionally.


CBSN is another prime example of how networks and others in the ecosystem are accessing data and analyzing it to drive better viewing and thus more profits in the making and distribution of content.


10 Lessons

The IBM white paper mentioned above spells out 10 key lessons that members of the telecom, media, and entertainment ecosystem need to consider and eventually understand and implement if they are to be successful in marketing and selling future content, including (1) Know Your Goals; (2) Know the Viewer; and (8) Realize the Vastness and Potential of Today’s Analytics.


A current telecom adage has it, “We will see more change in the next 10 years than we have in the past 100.” Data analytics in the media, entertainment and telecom worlds (especially the video part of those) is a perfect example of this very lesson.

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