Are Attention Metrics On A Path To Becoming Advertising Currency?

The Advertising Research Foundation (ARF) kicked off a day-long attention workshop Tuesday by releasing the second phase of an “Attention Measurement Validation Initiative” analyzing 12 different research company approaches to measuring attention.

The analysis studied the impact of 60 ad creative executions utilizing a wide variety of measurement approaches, which the ARF found to be equivalent to neither their accuracy nor their inaccuracy, especially when compared to the way the respective advertisers ranked the success of their ads.

The definitions of attention used – whether active or passive – were judged by the ARF Chief Research Officer Paul Donato and Director of Research Programs Tracy Adams to be driven by each of the measurement techniques being used, including which reflected cognition, emotion, persuasion, memory and even sales predictability and combinations thereof.  



So, what are the signposts from this tough but balanced and fair test of approaches?  

The measurement methods and techniques used in this ARF comparative analysis are vastly different and need to be closely assessed and understood.  One suggestion was that perhaps a hybrid of approaches would produce the best results.  

The twelve different approaches exhibited consistent “signatures” for the creative executions assessed nad found all the vendors to be generally congruent.  

As such, attention metrics clearly provide a critical “gateway” to understanding that ad effectiveness – intertwined with other measures of marketing pressures – optimize brand outcomes.  However, how attention directly relates to “outcomes” appears to remain an open question.  

“If a silent ad is not seen there cannot be any effect,” Viomba CEO  Markku Mantymaa said, underlying the importance of understanding attention as measured by the complexities sensory perception signals.  

Two cornerstones to an ad being “seen,” he said are “eye fixations (with a minimum of 200-300 milliseconds) and “sacccades” (eye movements between fixations). 

Attention measurement is not only complex, but can clearly be expensive although Viomba is using AI efficiencies for predictive attention analytics.  

I believe Mantymaa heard my applause when he stressed that “viewable impressions,”-- which are often used as a proxy for “technically viewable” impressions – have no correlation to attention.  

This helped to set the stage for a panel entitled, “Are We Ready for Attention Standards?”  The subplot: “Are we ready for attention as a media currency?”  

The panel was mixed on both questions. Interactive Advertising Bureau Vice President-Measurement Angela Eng seemed wary of attention as a currency but liked the concept of establishing data elements of attention that can be defined and standardized.  However, she appeared to be oriented to device signal reports, perhaps to maintain the edge that “viewable impressions” gives social media via phones or desktops notably vs. long-form TV on big screens?  

Media Rating Council Executive Director and CEO George Ivie embraced the establishment of standards, underlining the care and attention needed to outline meaningful and valuable proxies or direct measures of attention. 

Referencing Media Science CEO Duane Varan, he suggested measuring inattention may be the best place to start.  He also stressed the importance of bringing the measurement of people into the research equation, which was particularly refreshing, and I believe long overdue.  

Offering an agency’s perspective, OMD Managing Director of Marketing Science Burak Kurtun emphasized the value of attention to improve the impact of media and ad effectiveness by modifying target audience “reach & frequency” with attention metrics.  Like many of us, he ultimately does see attention as a currency – albeit integrated with other data – due especially to the influence of attention as driven by media content.  

Attention measures related to media evaluation will be the focus of Phase III of the ARF’s attention measurement initiative.  

However, a major takeaway was surely that “viewable impressions,” which have no measurement of people whatsoever, will be finally dead as a media currency in the very near future.  

I would suggest that that cannot happen soon enough.

2 comments about "Are Attention Metrics On A Path To Becoming Advertising Currency?".
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  1. Ed Papazian from Media Dynamics Inc, May 16, 2024 at 3:32 p.m.

    Interesting--but perplexing, Tony.

    If appears that the ARF is melding together atentiveness to an ad---whether a member of tthe assumed "audience" looked at the ad message for a certain amount of time,with impact---what was the outcome. By doing that they are precluding such metrics from becoming standard in TV audience surveys not only because the sellers, who control the surveys, won't allow it but also because it goes beyond what can be resaonably expected of a media seller. While it's fair for a media buyer to consider factors like engaging program content. the degree of ad clutter in a break, whether a viewer is potentially interested in the product being promoted, etc. it's unreasonable for the seller to guarantee that the viewer will buy into whatever claims the advertiser is making and purchase his product ---or switch from their current brand to the one advertised. While the two--attentiveness and outcomes--- are, obviously reslated in that one comes before the other, if any of this is meant to have future application to national TV audience surveys, attentiveness should be dealt with first---and separately. 

  2. John Grono from GAP Research, May 23, 2024 at 3:56 a.m.

    First, I like the "If a silent ad is not seen there cannot be any effect".   Who'd have thunk that !!!

    When we started the OOH system in AU (called MOVE) we used the self same technology.   We had pretty accurate vehicle, pedestrian etc. passers-by which was OTS.   We then applied that technology on a sample of ages, gender, location etc. then could calculate the LTS.   In essence we down-weight the Opportunity (OTS) into having those who had seen 'some' of the billboard - thus we had the Likelihood (LTS) that they saw and cognitavely saw it.

    The key to that is that there were patterns in the behaviour, hence the likelihood and apply that data to reduce the OTS to the LTS (i.e. different LTS acroos the targets).   What we did NOT find that we could accurately report on Attention.   For example, the same billboard with different ads generated highly variable recall.

    The learning is that with OOH the 'better' the creative the better recall.

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