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If a TV is playing to an empty room, your ad money is going to waste. In this blog post, we dig in on this problem — and how brilliant minds are working to solve it.
Do we have your attention?
In advertising, few questions are as important. Our entire industry is built around grabbing audience attention so that we can encourage that audience to do what we want, whether that’s making a purchase, creating an account, signing up for a newsletter, or more. And with the Connected TV (CTV) industry booming year over year, the ability to measure consumer attention is becoming increasingly important.
As the CTV market matures, we’re going to see a lot of questions being asked about attention: how we define it, how we measure it, and, of course, how we leverage it for profit.
In this blog post, we talk about the science of attention, and how to make it work for you.
Case Study: how OKO Digital was able to boost Loop TV’s revenues by 500x — on the first day.
Is “Attention” The Big New Thing?
Attention is a metric getting a lot of discussion these days, but it’s also nothing new.
As long as there has been advertising, audience attention was the goal, whether it was a guy yelling “hear ye hear ye” in the town square, roadside signs for Burma-Shave, or frogs with a surprising amount of interest in Budweiser. Getting eyes and ears on content has always been the goal, and figuring out how to measure that has always been a hitch.
The departure of third-party cookies this year, however, has brought a new intensity to the quest to track audience attention in as direct a way as possible. Since tracking your audience as they travel around the Web has gotten more difficult (and problematic) than it was previously, finding a way to reliably measure attention has become the Holy Grail.
What Makes Attention So Valuable?
Attention’s value as a trackable metric is fairly obvious: if a publisher could promise that a particular bit of content commanded unusually-high levels of audience attention, where viewers were looking closely at the ads, advertisers would be willing to pay more for that than they would for slots where the audience is disengaged or disinterested.
For example: the same audience, viewing the same episode of “Stranger Things,” can have a radically-different attention level if they’re watching at 6 pm versus a viewing session of 2 am. That sort of consideration has long factored into the pricing structure of linear TV, where “prime time” charges differently than other programming, but it can be a little harder to nail down when viewers themselves get to decide what they want to watch and when.
But, in the data-rich environment of CTV, which also affords more-refined targeting options than linear TV, cracking the attention code will be another way to help advertisers and publishers make informed decisions.
Defining “Attention”
Before we can measure attention, however, we have to have an agreed-upon definition of what it actually is. Because CTV is a relatively-new market sector, compared to the more-seasoned areas of online advertising, the way attention is defined, both conceptually and as a KPI is a little bit “squishy” at the moment. But, to break it down:
- An “Impression” is when an ad is served. This is incredibly-basic, but bear with us: impressions are the largest number involved here.
- “Viewability” is an impression that can be seen. CTV ads are considered to have high viewability because they can’t be skipped or fast-forwarded through on most streaming services, and because they take up 100% of the screen’s view, but that can’t measure whether your audience went to the bathroom.
- “Attention” then, is a measure of whether or not a human set of eyes actually looked at those viewable impressions at any point during the ad’s airtime.
“VIEWABILITY”
With web ads, “viewability” is defined by percentages.
- On a website, ads can become partially viewable as the user scrolls, so that an ad is, say, 60% viewable at the top or bottom of the frame.
- On CTV, there’s no scrolling, so all ads are 100% viewable within the frame at all times — but the user can move around their living room while the ads are playing.
For how long a time? That’s one of the factors that’s currently varying from platform to platform. One TVision study on attention with LG calculated attention by whether or not the audience paid attention to an ad for two seconds or more. Some people say “attention” when they mean “viewability,” others might use it when they mean “engagement.” The IAB’s definition of attention is, “a consumer looking at or listening to an ad at the time they were exposed to it.”
The industry, in short, has yet to settle on a singular definition of “attention,” but given the increased spend on CTV advertising in recent years, that standardization is definitely coming soon. But for the purposes of this article, let’s consider it a measure of whether someone is actually looking at your ads, for however long that may be.
How To Measure Attention
Modern technologies have started to unlock possibilities for measuring attention in a more-direct way than we’ve ever thought possible before, but new technologies do bring with them new concerns.
In the TVision study we mentioned up-top, the way they measured whether a viewer’s eyes actually locked in on a commercial was by setting a camera on top of the TV and pointing it at the audience. Advanced versions of this technology use AI-enabled algorithms to track viewers’ eyes, to see when they’re watching and when they aren’t.
That kind of approach works perfectly when you’re performing an experiment under controlled conditions, but in the real world, this approach has experienced some pushback.
In 2022, the “MoviePass” program that promised unlimited movie-theater tickets tried to relaunch as a paid digital service, promising an ad experience that would pause the commercials if the user attempted to look away. It didn’t go over well in the press, which generally considered it “dystopian.” And while none of the major streaming players have followed suit, it does seem likely that someone else will try again in the future.
Given that the reason third-party tracking cookies have gone away is due to privacy concerns from the public, pivoting to a camera in every living room that tracks people’s eye movements will probably remain a tough sell to the viewing public for a while. However, one could make the case that since an AI algorithm isn’t a “person,” you aren’t really being “watched” in the traditional sense — and paired with a compelling enough incentive (reduced rates, fewer commercial breaks, premium content) it’s possible that this technology could work in the future.
Another avenue to measure attention is by tracking audience engagement. Content is a driver of audience engagement, and some shows are appointment television with very invested audiences. “The Bachelor,” for example, saw four-figure spikes in engagement percentages for brands that advertised during the 2024 season premiere. Viewers who watched that premiere were 54% more likely to engage with advertising brands than the primetime broadcast average, based on stats like brand searches and website visits. If an audience is paying close attention to a show, it seems they’re also more-likely to watch the commercials. Transforming that engagement-to-attention ratio into a predictable formula that brands can make decisions with hasn’t materialized yet, but in our current environment, the data is definitely available.
Ultimately, however, the best way forward might be to combine some of these new methods with some of the methods of the past.
The New With The Old
Back in the first Golden Age of Television, so-called “Nielsen Families” would agree to have their viewing habits recorded, forming a large enough sample population that Nielsen could extrapolate from there to showcase who in America was watching what. When you talk about, for example, the “ratings” of the Seinfeld finale or the latest Super Bowl, the ratings in question are generally from Nielsen, even today. On the streaming side, however, viewership numbers are usually self-reported by the apps themselves, if they’re reported at all.
In 2017, Nielsen began expanding their practice to include some streaming content on services like Netflix, YouTube, and Disney+. Though they’ve had decades to perfect this approach, it’s still an approach somewhat limited by the accuracy of the model, and CTV introduces a significantly-higher number of variables to track.
This is where the limitations of old models and the limitations of the new models might be able to offset one another. While large-scale adoption of camera-enabled eye-tracking technology might be a ways off, sample-group models like Nielsen families could deploy that technology with their willing participants, while also getting more-accurate data for their mathematical models.
Final Thoughts
While the industry hasn’t settled into a standard method of measuring or calculating audience attention, it’s clear that with the data-collection and tracking capabilities of connected TV devices, we may finally be close to cracking the attention problem that’s dogged our industry for as long as there’s been an industry.
In the meantime, while the ways of measuring audience attention haven’t been standardized, every indication is that CTV advertising is commanding more attention from their audiences than traditional linear TV. Additionally, CTV is affording advertisers a higher degree of accuracy in their targeting than we’ve ever experienced before, yielding great returns for advertisers and publishers alike.
If you’re a publisher looking to enhance your monetization, OKO Digital is a solution that demands a look. You can get started today by reaching out to our team. As a Google Certified Publishing Partner for CTV with decades of experience driving more and better ROI for our clients, we’re ready to do the same for you.
