There are moments when an industry realizes the problem is not a lack of data, but that it has spent years measuring the wrong things.
In a world where dashboards still neatly report impressions, reach, and viewability, Mike Follett has long been asking the question the marketing industry has avoided for far too long: how many people actually paid attention? As a pioneer of the attention economy and co-founder of Lumen Research, Follett has not built his career by challenging industry habits for provocation’s sake, but by insisting that media effectiveness should finally be measured through genuine human attention, memory, and profitability.
His work clearly separates visibility from actual impact, showing how often marketing confuses exposure with value. In his conversation with Media Marketing, Follett emphasizes that it is not enough for an ad to be displayed – it must be noticed and remembered.
His upcoming session at Dani komunikacija, The Long and the Short of Attention and Memory, shifts the focus away from reach alone toward what truly drives business outcomes: the relationship between attention, memory, and profitability.
At a time when the industry is increasingly re-evaluating what effectiveness really means, Follett brings a rare combination of data, precision, and clear answers.
The title of your talk borrows deliberately from Binet and Field’s foundational framework on advertising effectiveness. Entering that conversation from the angle of attention and memory is a specific claim: that the original long-short debate left something unmeasured at the center of it. What does attention data add to that argument that was not visible before, and does it change the conclusion?
Attention data certainly adds an important perspective that was not visible before: that advertising is not always visible, and if visible, not always viewed.
People are very good at ignoring almost everything. There is too much world out there to fit into our tiny heads. So we have to get good at filtering out what is insignificant so that we can focus on what really matters. Advertising rarely matters, so rarely makes the cut.
Understanding the difference between the potential and the reality of attention is a good place to start – but it’s only a start. What really matters is how this attention is converted into memory and action.
And if you’re talking about memory, the next question has to be this: are we talking about short term memory or long term memory? How much attention is required to get someone to remember something for a day, or a week, or a year?
This was the question that dentsu set Lumen and Kantar: does attention work differently for the Long or the Short of it? And that’s what I will be talking through in my talk at the DK conference.
Lumen Research was built on a premise the advertising industry had held as a known problem for decades: that viewability is not the same as attention, but had not yet industrialized a solution to. When the tools to measure something that was always known to matter finally become available, why does the industry still take years to change its buying behavior?
Knowing the right thing and doing the right thing are two very different things. As you rightly say, planners have known that there is a delta between viewability and viewing for some time now, but have not had the tools to act on this insight. So the answer is to give people the tools they need – or rather, include attention insight into the tools that they are already using.
Over the past few years, Lumen has embedded our data into agency planning tools like dentsu CCS, Havas Converged, WPP Choreograph and Publicis Smart Reach. Planners can now augment their reach curves with attention data to plan and buy ‘attentive reach’. We have also partnered with viewability companies like IAS, so that advertisers can interpret their measurement data to estimate attention to live campaigns. Finally, we have worked with brand lift suppliers like Cint to combine our attention data with their memorization insights so that brands can learn how much attention they need to but to make a memory.
All these partnerships and integrations are designed to make it easy to act on attention insight. Planners are busy people: they don’t have time to learn a new tool or open up yet another dashboard on their computer. That’s why it’s so important to align our data with tools that people are already familiar with and already using. To be successful, we have to be easy.
Your research produced a correlation of .979 between attentive seconds and incremental profit across media channels, a result that surprised even you. What does a finding this strong actually mean for how media should be planned, and why has it not yet produced a more fundamental restructuring of how media is bought and sold?
Last year, we did an interesting analysis of 114 econometric models in partnership with Ebiquity and WPP. This helped us understand how much incremental profit an advertiser could expect per 1000 impressions. We were then able to align this ‘profit per 1000 impressions’ number with the ‘attentive seconds per 1000 impressions’ number that Lumen produces. The results shows that incremental attention and incremental profit are almost perfectly correlated. Increases in attention explain 98% of the variance in increases in profit.
No one advertises to get attention. No one really advertises to get sales – which can always be increased by decreasing the price. Brands advertise to generate profit. What this research shows is that attention predicts profit.
This is important because it answers the ‘so what?’ question. Some media generate more attention than other media. So what? Well, those media also generate more attention. That’s what.
At, crucially, attention predictions are a leading indicator profitability. It’s hard to plan and buy campaigns on the basis of predicted profitability. But it now easy to plan and buy them on attention – and we know that attention leads to profit.
Again, it’s about making things easy for busy planners. When attention data is available inside the tools that people are already using, then we can stop talking about attention and start doing something about it.
Attention measurement has, in practice, rehabilitated several media that the industry had been systematically deprioritizing, including print, cinema, and out-of-home. When data corrects a structural bias that was built on less rigorous measurement, what does that reveal about the quality of the decisions being made in the interim?
In English, we say that Man first shapes his tools, and then his tools shape him. The planning and buying tools that were available to media agencies misrepresented the amount of attention that different media generate. They were like a demagnetized compass, sending us in the wrong direction. Including attention data within these tools helps us understand where True North is, and so can get to our real destination – profitable growth. We have been making bad decisions because we have had bad tools: improve the tools, improve the results.
If attention becomes the primary currency of media planning, what happens to the incentive to improve creative quality? The argument for attention as a metric is that it rewards relevance and penalizes waste. But relevance is not the same as quality. Does an attention economy raise the creative standard, or does it simply make mediocre work more efficiently distributed?
Lumen’s normative does a great job of predicting attention to media. Using our data can help brand get a ‘fair share’ of attention.
But good creative can always get you more attention than the norm – and bad creative can always do worse. In this way, we find that creative agencies can make ads that deliver an ‘unfair share of attention’. Beautiful, or funny, or emotive ads effectively double or treble the media budget.
At the same time, clients may choose to cut costs by using a million instantly generated iterations of AI slop. But these ads are likely to get less attention than ones made by talented humans. You have made a saving on the production costs, but you have made your media investment much less effective. Is that really that intelligent?
But the smartest advertisers use eye tracking research to test and optimize the creative as well. We often conduct attention tests on specific creative designs to understand how much attention they generate, and use this information to optimize the media plan.
Creative and media working together? Now there’s something to hope for!
