Attention metrics are fast becoming the future of analytics in digital marketing and advertising. Here’s everything you need to know
In an online world that offers a seemingly infinite stream of digital content, users’ reluctance to pay to consume it is understandable. This has led to the popularity of attention economics, a concept economist Herbert A. Simon explored in 1971, which was later coined as the ‘attention economy’.
While the concept itself may not be new, the sheer volume of information that is available online means it is now more relevant than ever. Indeed, Simon himself summed it up perfectly by saying:
“In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention.”
It’s no wonder, then, that there is an increasing desire in the digital advertising and marketing industries to move away from traditional impression-based performance measurement in favor of attention metrics.
But what are attention metrics? Why should you use them? And what factors affect attention online? In this article, we explore everything you need to know.
The attention economy in a digital world
With such fierce competition for a user’s attention, digital publishers are investing huge sums of money into designing digital platforms that utilize every trick in the book to keep a user’s concentration firmly fixed on their content.
This could be anything from relatively simple techniques such as push notifications and auto-play video reels, to complex newsfeed algorithms and AI-powered recommendation engines.
So where does the money come from that’s driving all this investment? While some revenue does come from subscriptions, the overwhelming majority comes from advertising.
A modern example of this is YouTube, which offers YouTube Premium in addition to regular (free) YouTube. This provides users with the option of paying money for uninterrupted content or paying for content with their attention by watching compulsory advertisements, before and during a video.
With YouTube’s Q3 2021 ad revenue reportedly standing at $7.2bn, and its potential revenue from subscriptions standing at a much smaller $600m, it’s clear the value advertisers place on attention and indeed how lucrative it is for publishers. This has created a digital advertising industry projected to be worth nearly $495bn in 2024.
Having read this, it may surprise you to learn that the traditional digital advertising valuation model offers no way of measuring how much attention an ad received. Sure, the number of impressions tells an advertiser how many people could have seen their ad, but there is no way of knowing whether anyone actually took any notice.
The problem with impressions
In the context of digital advertising, there are good reasons why attention metrics are quickly gaining popularity over the current system.
Served impressions represent the number of times an ad is loaded on a webpage. Traditionally, advertisers would pay a price based on the number of served impressions their ad would achieve.
Initially, this presented a step up from the readership figures used in the days of print publishing. After all, it guaranteed that a user had actually seen the page on which an ad was placed, which meant the ad must have been in their line of sight, right?
Wrong. A served impression only guarantees an ad was loaded, not that it was ever in view.
The nature of scrolling webpages and the negligible cost of creating additional digital space meant bad actors could place endless digital ads at the bottom of a page that appeared so far down they would never come into view. This meant that while advertisers were paying good money for genuine impressions, their creatives would never actually see the light of day.
To combat this issue, the Interactive Advertising Bureau (IAB), Association of National Advertisers (ANA), and the American Association of Advertising Agencies (4A’s) founded an initiative called Making Measurement Make Sense (3MS). This initiative led to the introduction of a Viewable Impressions system, in which an impression only counts if at least 50% of the ad’s pixels are in the viewable portion of a browser for at least one continuous second.
This was, of course, a move in the right direction, but it doesn’t reveal whether a user gave that content the time of day. Attention metrics go a step further towards achieving that goal.
What are attention metrics?
Attention metrics describe ways in which attention can be measured.
There is no single measurement of attention as it depends on what is being consumed and how (more on this below). But, invariably, they revolve around time – that is, how long someone has spent doing something, and more specifically, the exact actions they performed during that time.
In the digital world, when compared to impressions alone, attention metrics can give advertisers and publishers a much more accurate idea of how users are interacting with their content.
How do you measure attention?
There are countless ways to measure attention online. These vary according to exactly what your definition of attention is, which is likely to be influenced by the device on which content is being consumed, the design of the platform, the format of the content, and the nature of the business among other things.
While these detailed metrics can vary enormously between individual cases and analytics software, below are some general examples of how to measure attention.
Active time in view
On the most basic level, active time in view could describe the amount of time a piece of content or an advertisement is viewable in a foreground browser tab.
To gain a more accurate attention measurement, activity can also be considered. Cursor position, touch rate, scroll rate, and scroll depth can all be recorded to determine whether the user is interacting with the page when the content is in view (and, indeed, if they are interacting with the content itself).
For example, by using image-streaming technology that features interactive elements such as Hyper Zoom and full-screen viewing, it is possible to gain useful insights into the way users are interacting with images and where their attention is focused.
In the case of video content, rather than simply recording the number of plays, considering the number of plays to completion or the number of plays with audio can give a better idea of overall content performance.
The above attention metrics can be recorded in real time, in the real world, with real users, which has its benefits from a logistical and monetary standpoint. However, they could never provide a 100% accurate measure of attention. For that, lab-based methods are required.
Lab-based research
Eye tracking
One of the most accurate ways to measure attention is through eye tracking. This is where technology is used to record the movements of a user’s eyes, revealing exactly where they are looking on the screen.
This offers an unrivaled insight into user attention, such as how a user interacts with a piece of content, whether or not they notice on-page ads, and how easily they navigate a user interface.
Facial coding
Facial coding is the process of using computer software to automatically recognize facial expressions via a webcam. This technology can provide valuable insights into how a user is feeling when they are viewing a piece of content.
Why use attention metrics?
The world of digital advertising is an extremely nuanced environment; what works in one place might be disastrous in another.
By using attention metrics to measure performance and inform advertising, content, and user experience (UX) strategies, it is possible for advertisers and publishers to walk that fine line between hard sales and user experience.
In each of the cases below, attention metrics can and have been used to provide a level of insight that allows publishers to optimize their UX and advertisers to enjoy higher-quality placement, ultimately giving the user a better online experience.
Creative
Dentsu’s Attention Economy Program Phase 2 Research found quality of ad creative to have the largest effect on user attention, impacting recall by up to 17%.
However, it is not just advertisers who can benefit from this insight. The same metrics can be used to guide branding and web design by revealing how design affects a user’s engagement with a publisher’s content.
Page clutter
While it’s easy to assume that a higher number of different images, CTAs, or advertisements will present the user with greater choice and lead to a better user experience, the opposite can often be true.
For instance, Miller’s Law states that the average person can only keep between five and nine items in their working memory, and with analysis paralysis an ever-growing part of our digital lives, maybe less is more?
Ad size and format
The size of an ad, and whether it makes use of a still or moving image, can have a significant effect on the extent of attention it attracts, and also the reasons for that attention.
For example, a huge pop-up advertisement may well be noticed, but is it being noticed for the right reasons? Learning how users interact with that content can provide a better idea of its overall performance.
On-page ad positioning
It is widely acknowledged that an ad’s position on a page makes a big difference to the amount of attention it gets. But what position is best?
Prominent leaderboard ads may be front and center when a user arrives on a page, but that doesn’t necessarily mean they get the most attention. Indeed, banner blindness could mean they are completely overlooked.
Research from Chartbeat shows that 65.7% of engagement takes place below the fold, which means that ads positioned further down a page, and even at the end of an article, are likely to gain more attention than those displayed elsewhere.
Page content
The use of served impressions to measure ad value created an online world where the priority for many publishers was simply page visits. As long as the ad was served, they got their money, and little regard was ever paid to the user. This gave rise to clickbait headlines linking to pages characterized by low-quality content and high bounce rates.
Research suggests that users who spend 15 seconds or longer viewing a piece of content are 25% more likely to recall a brand than those who view it for 10 seconds, which makes clear the negative effect such practices can have on ad performance.
While this has undoubtedly been bad for users and advertisers, the publishers are now also paying the price. The lack of quality content online has eroded trust and devalued inventory, and with the third-party cookie soon to disappear, a huge focus is being placed on contextual advertising.
All things considered, ensuring ads appear in context among engaging content has never been more important.
Forced advertising vs voluntary advertising
Finally, whether an ad is forced or chosen can make a large difference to its success. Research shows that forced advertising needs double the amount of time to deliver the same impact as voluntary ads. Therefore, paying a premium for a 10-second compulsory pre-roll video ad might not be the most cost-effective strategy.
The future of attention metrics
With mounting evidence that the current digital advertising performance measurement model is broken, combined with the fundamental changes being brought by the death of the third-party cookie, attention metrics are set to play an increasingly important role in the new era of digital advertising.
For example, Dentsu’s previously mentioned Attention Economy Program Phase 2 Research found that when a client optimized their advertising for attention, it garnered 3.7 years of greater attention in one month than it did when optimized for reach and frequency at the same budget.
For this reason, the sooner and more extensively advertisers and publishers implement these analytics and begin using attention metrics to inform strategies and price points, the more they stand to gain.
Learn how SmartFrame’s interactive controls can provide valuable user attention data with the Insights image analytics tool
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