The advertising industry has a long and distinguished history of measuring, and often, the wrong, shiny things very precisely.
For years, we measured reach. Then clicks. Then viewability. Each time, we congratulated ourselves on the sophistication of our analytics and moved on. That is, until someone quietly pointed out that the metric we’d enshrined as ‘gospel’ didn’t actually tell us whether a human being had engaged with the ad in any meaningful way.
We are at one of those inflexion points again.
The attention movement and its limits
‘Attention’ has become the industry’s favourite new word. And rightly so; the case for it is compelling. A landmark joint study by Lumen Research and Ebiquity, published in late 2024, found a near-perfect correlation (0.98) between the number of attentive seconds generated per thousand impressions and the long-term incremental profit delivered to advertisers.
In plain English, the more genuine attention an ad receives, the more money it makes for the brand. Eyeballs, it turns out (obviously), really do predict hands going into wallets.
The Interactive Advertising Bureau (IAB), working alongside the Media Rating Council and over 200 industry experts, released comprehensive Attention Measurement Guidelines in late 2025. The first industry-wide framework of its kind found that attention is no longer a fringe idea. It is becoming the new standard.
Attention is a laboratory-tested construct (covering ad size and shape, creative impact and placement) whose results are later overlaid on a campaign. Attention cannot be measured ‘live’ as no JavaScript tags can turn on a user’s camera to track eye movements.
So far, so good.
But here is where it gets complicated.
Attention is a probability, attentiveness is proof
The IAB guidelines are careful to note that attention measurement “examines the likelihood that an ad was actually noticed”. Likelihood. Probability. These are honest words, and credit to the industry for using them. But ‘likelihood’ is not certainty.
And, for a media analyst trying to reconcile campaign spend with commercial outcomes, ‘probability’ can be a woolly area.
The fundamental issue is one that the industry has danced around for a decade: our standard metrics (impressions, clicks, viewability, and most current attention scores) cannot definitively confirm that a real human being was present.
Viewability requires just 50% of a display ad’s pixels to appear on the screen for one second, and for a video ad, two seconds (MRC standards). That is a technicality, not a marketing outcome. And as Graham Page of Affectiva puts it: “Looking isn’t the same thing as reacting.”
This is where the concept of attentiveness becomes important, and it is a meaningful distinction from the way the industry currently uses the term “attention”.
Attentiveness is measured on the landing page, in real time. Thus, an ‘attentive’ user has seen the ad and taken further action. Clearly, the ad had to have been viewable and to have garnered attention.
Attentiveness is not a score. It is not a probabilistic model. It is deterministic, forensic confirmation of human engagement: live touch events, mouse movement, scrolling behaviour, and interaction signals, triangulated across hundreds of variables to confirm, not just that an ad was in the vicinity of a screen, but that a person genuinely engaged with it.
Think of it this way. Attention asks: “Was the ad likely to have been seen?” Attentiveness asks: “Can we prove a human was there?” (It is vital to ask about human presence, as neither viewability nor attention distinguishes between humans and fake-traffic bots.)
Why this matters more than ever
The gap between those two questions has financial consequences. Research shows that attention metrics are six times more predictive of ad recall and seven times better at forecasting brand awareness than older metrics. That is a significant improvement on simple impressions.
But in an ecosystem where sophisticated bots can now scroll, hover, and simulate complex browsing behaviour with enough precision to defeat standard verification filters, even attention signals are becoming vulnerable to manipulation.
Higher attention impressions have double the success rate of those with low attention, but only when those impressions involve real humans. A bot that scrolls convincingly is not attending. It is performing.
The Ehrenberg-Bass Institute at the University of South Australia published research in 2024 confirming that some attention measures can indicate high attention scores, while actually recording only moderate or no conscious ad processing. The visual signal and the cognitive reality can be two entirely different things.
A better question for your next campaign brief
Media analysts are uniquely positioned to drive this shift. They are, typically, the people who see the full picture, the inputs, the outputs, and the yawning gap between them that everyone else in the room has agreed not to discuss.
The question worth asking is not “How much attention did this campaign generate?” It is: “|How much of that attention can we prove was human?” Viewability establishes that an ad had the opportunity to be seen. Attentiveness asks whether it actually was.
Those are not the same thing, and conflating them is how budgets quietly evaporate into the digital ether while dashboards glow reassuringly green.
A 2025 study by VCCP Media in the UK found that brands are wasting up to 66p in every £1 spent on digital ads. This equates to £66 billion (R1.5 trillion) in lost value globally each year, largely due to insufficient branded attention. It’s time to start clawing that back.
The industry is moving in the right direction. The IAB framework is a genuine step forward. The Lumen-Ebiquity research is among the most compelling evidence that the quality of engagement predicts commercial outcomes.
But the final frontier, the metric that closes the loop between spend and human reality, is attentiveness. Not as a buzzword. As a forensic standard.
Marc Dhalluin is the co-founder of TruthsetsOnline.com. With over 25 years in marketing — spanning agency, client, and consultancy roles across Africa, Europe, and the US — he has helped build, transform, and rescue brands, generating more than $500 million in annual revenues. A long-time collaborator of fraud researcher Dr Augustine Fou, Marc is now focused on one thing: proving that real advertising reaches real humans. He is based in Los Angeles and writes regularly on digital transparency, programmatic fraud, and what brands should actually be measuring.
Connect with Marc on LinkedIn or visit TruthsetsOnline.com
