The attention economy has been in existence for almost five decades now, longer than the World Wide Web has been around. The ability to measure attention, however, is relatively new – especially for brands looking to understand the impact of their campaigns.
Promising to enable access to more accurate information about consumer behavior without the use of personal data, attention metrics are fast becoming a priority for advertisers, especially as a cookieless world looms large. But the technology requires more standardization before it can reach its full potential.
What sets attention measurement apart from existing metrics?
While traditional metrics can be measured in real-world conditions, it is harder to do so when it comes to attention. However, a variety of technologies are in development, such as eye tracking, MRIs, skin conductance, EEGs and head-movement tracking, alongside monitoring a user’s active time on a screen while they interact with an ad.
These tools have the potential to be both more accurate and more revealing than existing metrics, such as impressions and click-through rates. Eye tracking, for instance, provides more detailed information about consumer preferences, motivations, beliefs, affective states or decision-making processes, which can all be used to personalize ad experiences for the consumer.
What approaches and metrics are being used to measure attention?
There are a number of different attention vendors seeking to provide advertisers with meaningful ways of measuring attention. Beyond eye tracking, some attention measurement companies track indicators such as gaze points, fixations, how long it took the person to notice a particular element and the order in which they looked at different elements.
Kim and Lee (2021) even used some of these metrics to gain information on emotional responses and concentration while browsing, choosing and buying products in the virtual environment.
On top of this, some use AI technology to measure emotional responses through facial coding, and Neurons – a consumer neuroscience database platform – now suggests AI-based modeling is 95% accurate in predicting human attention.
The upshot of the variations in what is being measured – and how they are measured – is that a number of proprietary metrics relating to attention have been created. These include the IAB’s attention per thousand impressions, which is calculated as the percentage of people looking at ads multiplied by the average time spent looking at ads multiplied by 1,000.
Adelaide has developed Attention Units (AU), which show the potential for an ad to deliver an attentive impression. TVision, in collaboration with eye-tracking research provider Lumen, has developed aPM (attentive seconds per thousand impressions). Meanwhile, Dentsu, also in partnership with Lumen, has come up with effective attention cost per thousand (EACPM).
The plethora of standards means making comparisons between providers and the results of different studies is tough.
Additionally, even when attention is successfully measured, there is no clear-cut relationship between attention and tangible results, such as sales and ROI.
Could attention metrics be used as currency for ad deals?
While advertisers can buy attention through some demand-side platforms (DSPs), including The Trade Desk, MediaMath, Avocet and Google DV360 – meaning they can bid on high-attention display and video inventory in real time – they may feel that more clarity is required before assigning their budget in this way.
Attention metrics certainly have the potential to uncover insights that inform strategy, but the challenge of coming up with standardized measurements currently stands in the way of using them as currency for ad deals. Delegates at a recent conference hosted by the Advertising Research Foundation agreed that it is too soon to try and set an attention currency, though a growing number of companies say they are deriving value from various metrics.
Still, there’s a need for further investigation to fully understand all of the factors that impact attention – and without this understanding, standardized metrics still look to be some way off.
A better, more standardized ecosystem
While attention metrics are still in the early stages of development and, therefore, subject to constant change, marketers can address the attention economy today by adopting a consumer-first approach that prioritizes personalization.
Personalized marketing not only reduces customer acquisition costs and lifts revenues, but it can also increase marketing ROI by as much as 30%. Personalized ads demand attention because they provide value, and with 72% of customers solely engaging with ads that have personalized messaging, tailored campaigns are also more likely to encourage brand loyalty.
Overall, attention metrics have the potential to be highly accurate and powerful tools that can help us understand consumer behavior and inform campaign strategy. However, they need significant development before they can be used effectively.
In the meantime, leading industry and media players must come together to create a consumer-first strategy that equally benefits advertisers and consumers, creating a more collaborative ecosystem.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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