Special Post: OVAB Guidelines for Dummies

December 31, 2008 by Dave Haynes

It is well-considered, well-conceived, entirely laudable work — done with the best intentions of starting to herd the industry cats and get the many, many, many network operators out there to start measuring and selling what they’ve got in some roughly harmonious fashion. Without such guidelines, the people in media planning groups and at brands who control media spend will continue to look at the digital out of home industry as an interesting sideline that’s WAY too perplexing to understand, validate and buy. 
But the guidelines, to be kind, are tough going. For the time-crunched or nominally interested, they are pretty much impenetrable.
Read the core statement of the thing: Average Unit Audience should be the currency metric for out-of-home video networks. Average Unit Audience is defined as the number and type of people exposed to the media vehicle with an opportunity to see a unit of time equal to the typical advertising unit.
A handful, and I do mean handful, of people will read that over and conclude, “Ok, yup . Good. Got it.”
The rest of us will more likely be bug-eyed and blinking, with bubbles forming on our lips. 
For the research nerds, and ad sales operations types, the guidelines have a lot of good, deep thinking and plenty of rationalization and back-up on why the guidelines were shaped this way.
But the document is too big, too deep and too laden with new jargon to be absorbed and, more to the point, embraced and used. Much of this industry will succeed or fail based on the ability to win advertising and brand marketing dollars, and that means we should ALL know at least a little about the measurement standards that are being created and advised to give the industry credibility. My fear is most of us looked at the OVAB guidelines last fall, and decided we were going to need to set some time aside later to really read and absorb them. And because we’re all stinkin’ busy, that time hasn’t been set aside and many of us have moved on.
So, for my own benefit, and sanity, I have been reading the guidelines over (and over) and boiled it down to what I am calling OVAB Guidelines for Dummies.
I started down this path trying to break down the sections into easy-read, easy-understand versions, but abandoned that concept. There’s a lot in there, and for those truly interested, it’s not that hard to digest once you get over the hump of some tortured phrasing. My intention is to break down the core thinking into something more easily understood and remembered for those of us who just need to know the highlights.
The background to the guidelines is straightforward. There are countless digital screen networks out there now, and more coming. Just about all of them have their own way of measuring their viewing audience, and there is little in common between them. The venues, from corner stores to airports, buses to elevators, are too diverse to even imagine a single measurement system. But the thinking is that maybe a common set of measurement standards would lead to results that could be compared by the agency and brand people who would buy time on these kinds of networks.
“If each audience measurement study strives to produce the same set of metrics with an acceptable level of research quality,” says the guidelines, “and the data reporting is harmonized, the results can be safely compared for any number of typical media buying and planning analyses.”
The people who put the guidelines together recognized many of the companies in this space do not have pockets deep enough to fund really high quality measurement, and the net result are fairly elemental guidelines that might make media research uber-nerds roll their eyes. But OVAB says these initial guidelines are a foundation, and that it will be in the interest of everyone to do deeper (read more expensive) research as the industry matures and research budgets grow.
With that stated, here’s the nut of it:
This is all about sorting out how many people had the opportunity to see an ad, therefore defining the network and venue’s advertising value. The key characteristics are presence, notice and dwell time.
The product of these guidelines is a number, that spits out at the end of a calculation, that sorts out the following:
  • the foot traffic in a venue, like a medical clinic
  • the foot traffic in the area(s) where the screens are up and running
  • what percentage of that foot traffic actually looked at the screen
  • dwell time in the vicinity of the screen
  • length of the playlist loop
What this does is level out the measurement for different networks who can can claim similar foot traffic but, because of the other variables, may actually be delivering very different ad impression/eyeball numbers.
For example, let’s use the example of two clinics that both claim to run 5,000 people through their doors each month.
Each clinic is a “venue” in OVAB terms.
In both cases, 80 per cent of the people end up parking their butts in the area where a screen is running (this area, in OVAB’s terminology is the “media vehicle”). 
So based on that 80 per cent, the potential audience is reduced by 20 per cent to 4,000. That number, says OVAB, is the “vehicle traffic.”
For those 4,000 people, in both cases, surveys or other technologies sort out that 75 per cent, on average, actually notice the screen. So that reduces the number to 3,000, which OVAB calls the “vehicle audience.”
Now here’s where things start to diverge.
In clinic A, the average dwell time is 10 minutes (600 seconds) and the playlist loop time matches that. So of those 3,000 people who noticed the screen, all of them had the opportunity to see all of the ads and other content in the playlist loop. The means the final number, the “average unit gross impressions,” is 3,000.
In clinic B,  the average dwell time is 10 minutes (600 seconds) but the playlist loop time is 30 minutes. So the playlist is three times longer than the dwell time available for people to be exposed to all the ads in the rotation. The result is that the audience only had an average 33 per cent exposure opportunity, which reduces the overall 3,000 number to just 1,000 “average unit gross impressions.”
So two medical clinic networks that may be selling their ad inventory on the basis of pure foot traffic have, using these guidelines, very different actual audiences when these calculations are used.
 Network example  Clinic A  Clinic B
 Venue Traffic  5,000 5,000 
 % in the vehicle zone (near screen)  80%  80%
 Resulting vehicle traffic 4,000   4,000
 % who notice the screens (vehicle)  75% 75% 
 Resulting vehicle (screens) audience  3,000 3,000 
 Dwell time near screens  600 seconds  600 seconds
 Content loop time  600 seconds  1,800 seconds
 Match of dwell and loop times   100% 33%
 Average unit gross impressions  3,000  1,000
Another example: A network in a train station may have 100,000 people a day near the screens, but if only 10 per cent look and the dwell time is only 10 seconds and the loop is 60 seconds, the actual gross impressions per day is more like 1,600.
It was doing this calculation, a fairly close variation on one that has been used in my own industry circle of friends for years, that finally gave me the Eureka moment. The words are tough to grasp but the calculation makes it pretty simple. 
It allowed me to go back to this tortured statement: 
Average Unit Audience should be the currency metric for out-of-home video networks. Average Unit Audience is defined as the number and type of people exposed to the media vehicle with an opportunity to see a unit of time equal to the typical advertising unit.
And turn it into this:
Average Unit Audience should be the standard measurement used for digital screen networks. That means a common way of defining how many people had an opportunity to see the ads on screens installed in network venues, and how many of those people were around those screens long enough to see all the ads that were scheduled to run. Ideally, the average amount of dwell time around the screens is equal to the length of the ad loop.  If not, the average unit audience may be larger or smaller depending on that dwell time and loop length.
The OVAB guidelines go much, much deeper than this, and talk about variables such as networks with a content/ad mix, things like reach and frequency and the longer view approach that goes beyond audience measurement, into performance measurement and attitudes towards networks. There’s lots of good stuff in there, and if you have the time and the inclination, do drill down.
If not, and you just need to have a base understanding of what all the OVAB fuss was about, hopefully this cleared the fog a little for you.