Temporal Shift...and a Proposition
This is where the temporal dimension of watching television comes in. The audience's contribution to the TV value chain is their time and attention. C3 is counting time and attention, but not in a way that I believe really measures how much someone paid attention to the ad or to the show, which would get us closer to forming a link (albeit still tenuous) around the effectiveness of TV advertising relative to the program that surrounds it. Metrics that do that would, in my view, increase every group's level of accountability to the others.
What should be measured is not just a question of eyeball volume, but a question of when people watch a program and how "engaged" they are with it, and I think that has something to do with time, but in a different context than it used to be counted. Several studies have indicated that an engaged audience pays more attention to advertising. So what if, instead of simply adding up the viewers from the broadcast date to the 3rd day DVR playback, we had a metric that weighted audiences based on an estimate of their engagement level before the airing of the next episode?
My proposal for changing C3 or creating another metric is based on the principle that an engaged viewer is always trying to watch a show so that they will be caught up for the next episode. This does work best for serial drama, but also applies to any program that is not completely episodic, and has ongoing storylines. What if we took information on broadcast ratings and DVR playbacks for each day before the next episode airs and weighted it according to when it was watched?
For example, I think that there are two types of engaged viewers: people who really need to watch the show as soon as possible after it is aired to see what happened, and people who will watch a previous episode right to catch up shortly before the next episode is on. What I am proposing is that we measure everyone who watches between the broadcast of an episode and the airing of the next episode. However, I would give more weight to the people who watch it within the first 0 to 2 or 3 days after broadcast and the last 0 to 2 or 3 days before the airing of the next new episode. The precisely how to weight these and the number of days to count on either end of the spectrum would require some research, some of which I am hoping to cover in an upcoming project.
Looking at the number of viewers in each of these groups over time may also help understand the audience for a particular program, and how to use transmedia tools to keep people involved and engaged enough to keep interest peaked for the next episode. Understanding online viewing behaviors, also an area of interest for me, would be a critical piece of the puzzle in comprehending and reaching engaged viewers.
There is little doubt that the TV economy is shifting. C3 is one way to make sense of the changes, but I doubt that it will be the final currency. We have said it many times on this blog, but there's a need for a set of metrics that account for the varied ways in which people view television content to ascertain the true value of the contributions of the networks, advertisers and audiences. Stay tuned...