Earlier, attention was overlooked as an assumption.
If you bought a media placement, you got attention as a bonus. A TV advertisement, a magazine page, a billboard on the busiest highway… These were treated as if the audience was there, engaged, and watching.
However, the internet completely unsettled that idea.
Attention Has Become the Rare Resource
With digital advertising, the supply of advertising space became infinite. Banners, pre-rolls, sidebar units, native placements… The number of available ad slots has been progressively infinite at any moment. And when supply goes unchanged, prices crash and quality follows.
But human attention didn’t follow the trend of scaling.
The day still has only 24 hours. People still have a limited capacity for the information they absorb, process, and remember. While the advertising world was busy creating more impressions, the component that made impressions valuable, real human focus, was constant.
This is a market situation that is at the same time overcrowded with media inventory and severely lacking real attention. Brands are paying for people’s presence that doesn’t exist. Publishers are getting revenue from sessions with very little cognitive recognition.
Something had to break. And now, with AI coming on the scene, it finally is.
If You Aren’t Measuring It, You Can’t Optimize It
For the majority of digital advertising, attention was simply assumed, not measured. Once the ad served the impression, the process was completed.
However, the problem is that an impression and a moment of attention are entirely different things.
- A banner ad that is shown below the fold and not scrolled to, that is an impression.
- An ad displayed in a tab that the user has minimized 30 seconds ago, also an impression.
- A pre-roll that is skipped at the two-second mark, one more impression.
These are just technically delivered, but from a cognitive perspective, they are irrelevant.
The industry is now confronting this issue. Attention is becoming a performance metric along with time-in-view, active engagement signals, scroll behavior, post-exposure recall, etc. AI is enabling these high levels of measurement granularity.
Machine learning algorithms can now analyze a user’s behavioral patterns in real time: the duration a user has been on a page, whether the user is scrolling or idle, the user’s recent exposure to content, and the user’s progress in the session. All these data points help form a much clearer idea of whether this moment, for this user, is indeed real attention or just a mere logged presence.
Such a small difference is worth billions of dollars.
Giving Exclusive Attention Is Turning Into a Great
When you know how to measure attention, you can begin to assign different values to different media formats.
One cannot place a banner impression and a full-screen exposure even in the same product category. The former has to fight with multiple other elements on a webpage for only a peripheral glance. The latter is in the possession of the user’s entire visual field completely, without any other content, navigation clutter, just a brand and a user.
Interstitial advertisements are being looked at again by those who market for performance and who actually care about real results, for this reason.
Attention research has proven that this type of ad creates what is called a “high-focus environment” by the user. In this setting, the user’s cognitive resources are not divided between reading an article, moving the cursor, and noticing a banner ad in the corner of their field of vision. At this moment, the user is solely focused on the message.
Brands understand this are allocate their spending toward platforms that provide a sure medium that directly targets the audience and grabs their attention. Because attention is what causing recall, intent, and conversion downstream.
Besides Quantifying Attention, AI Creates It
Here’s a part that is missing in many conversations about AI and advertising: the tool is not only a means of optimization, but also the creation of context/setting/environment.
Highly advanced AI systems do not simply sit back and continue to stare at a moment of high-attention that may arise. They assist in the formation of conditions in which a high-attention moment can be delineated.
Engagement time can be increased by means of content recommendation engines. Personalization layers can be used to present what a particular user finds truly relevant. Modes of session can be used to analyze when a user is browsing/exploring versus when making a decision.
The victorious publishers today are not those who have more ad slots.
It’s the ones who have the best signals about when their audience is paying attention and also have the infrastructure that allows them to monetize those high-quality, attention-worthy moments.
Coming up
Measurement will have to become more precise before attention will stop getting more and more expensive.
As soon as the buyers get a clear idea of what they are actually obtaining from the various types of inventory, they will be ready to pay a higher price for the good category and not to pay for the remaining series.
The brands and publishers that are linking themselves to attention quality first are setting up a base for something that is not going to change quickly. A better advertising campaign and increased understanding of what advertising is for, are two different things.
The truth is that impressions have never really been the measurement. It is the moments that have always counted.
AI is simply enabling us to see and understand the moments.
