The Problem With TV Measurement

TV’s problem isn’t an inability to provide value. It’s problem is its inability to measure and quantify that value.

TV has been one of the industry’s longest-standing holdouts when it comes to getting a measurement and metrics overhaul. But thanks to advances in real-time, historical, national and local TV metrics that rival most performance-driven digital channels, TV recently won its battle to stay relevant and has stepped back into the limelight.

This isn’t a discussion about TV making a big comeback, however. TV never really went away. It’s also not about TV underperforming when compared to digital—especially not in terms of ad spend, reach or effectiveness. A recent NY Times article hit the nail on the head when it said: “Ratings aside, television still reaches more people and provides a reliable way for an ad to be seen on a full screen with sound.”

TV’s problem isn’t an inability to provide value. It’s problem is its inability to measure and quantify that value. TV measurement methods simply haven’t been updated to offer advertisers the same speed, accessibility, accuracy and transparency they enjoy on digital. One reason for this is that doing so requires the industry to retroactively “tack on” emerging technology to a legacy medium, whereas digital was built from the ground up with measurement in mind.

The industry is also late to the game. Once digital hit the scene, TV measurement was simply left behind by an industry that assumed it would eventually be obsolete. It’s now racing to catch up by introducing real-time, hyper-local and fully transparent TV measurement. Among other things, this will require doing away with the archaic industry standard (the GRP) and replacing backlogged, manual data gathering methods with a technology-driven approach.

Here are three major problems that new TV measurement practices must eliminate.

1. The lack of local TV data has meant a lack of local attribution data. TV has traditionally been used for awareness-level campaigns, and because of that, advertisers long gave it a pass when it came to being accountable for producing ROI. The thinking seemed to be that as long as TV advertising created an emotional connection and resonated with audiences, it had done its job. This line of logic additionally gave the industry a pass for having to prioritize more evolved measurement practices.

But what all of this doesn’t take into account is the fact that the ROI of any awareness campaign follows a long-tail model, where initial awareness creates desire and desire creates purchase or engagement over time—whether hours, days or even months later. Today’s TV data, which only reveals who’s seeing what and where, but not what the resulting awareness means in terms of generating engagement or purchases beyond the spot or campaign. For the many industries that still rely on in-store traffic (Auto, CPG, Big Box Retail) to drive revenues, this means that half the data story is missing.

The solution is rooted in access to rich local TV data that will allow advertisers to tie local purchase data (or what’s happening after the ad is seen) to tangible, measurable ROI, both directly after the fact and over time.

2. There aren’t any viewability standards for TV. In addition to traditional paid TV ads, many brands are also investing in sponsorship of events, sports and athletes. This means their on-screen real-estate is smaller and their on-air time is usually shorter, but brands’ expectations for exposure with these captive audiences are just as high.

Current metrics work hard to make sure these expectations are met by reporting on things like logo appearances that actually don’t result in any tangible value for the brand. For instance, a logo far off in the stadium, not within the same focal point as the on-screen action, is likely completely off the casual viewer’s radar. Nevertheless, it’s reported as an impression, and isn’t distinguished in any way from true impressions that do provide the brand value.

Similarly, even logos right in the middle of the action aren’t always detectible to the untrained eye. Take, for instance, a logo on an NBA player’s uniform. Perhaps it gets partially covered by folds in the player’s jersey or blurred in the action, making it only semi-visible.

TV has a lot more to offer than “impressions”, but without standards for “ranking” these appearances and classifying them according to visibility and completeness, it’s nearly impossible to attribute any true ad value to more advanced metrics either.

New TV measurement technologies are using “human eye recognition” technology to eliminate false positives from TV sponsorship data altogether by only detecting logos that would be detected by the human eye—thus actually making their way into viewers’ awareness.

3. There’s a lag time in receiving TV data. While delivery of TV data is getting faster, it’s still nowhere near the speed of digital data delivery. TV data is delivered, at the soonest, two weeks after the occurrence. This results in brands operating at a deficit, with less time to optimize and change their campaigns based on known KPIs.

Now, compare this to digital advertising channels, which give marketers real-time feedback they can use to optimize their forthcoming or even current campaigns. A digital campaign might reveal that a certain ad isn’t converting as well as another, so the marketer can pull the low-performing creative or ditch a channel that’s not converting well, and introduce new creative or channels based on what it’s learned.

TV hasn’t had this luxury. While there are many TV-specific variables that hinder the faster delivery of better data, automating all manual methods with technology is step one. As new measurement solutions emerge and these old measurement problems are eliminated, brands are discovering reliable new ways of understanding what their huge investments mean for the bottom line—and how those investments impact efforts on other channels. The data points they’ve had access to until now only told a fraction of the story, and that’s just not good enough. It is not good for advertisers and it is not good for media owners.