Sure, people see a lot of ads, but are any of them paying attention?
In recent years, advertisers have tried to answer that question, investing in measurement tools that go beyond the industry’s typical standard of viewability and impressions, which track whether ads actually appeared and whether anyone saw them.
Lumen Research, Adelaide, Playground XYZ, and others have worked with companies like AB InBev, Coca-Cola, Mars, Kia, and HP to embed digital campaigns with something called attention metrics, which aim to measure the *jazz hands* quality of the media that advertisers are buying by combining eye-tracking data with web-page layout information.
May I have your attention, please?
The growth in attention metrics in the adtech space is likely the result of two somewhat contrasting trends in the industry. First, according to experts we spoke to, advertisers are tracking their dollars more diligently and evaluating impressions to ensure there’s a return on investment, and second, the tightening privacy landscape means that traditional attribution models (aka the fancy math that ties a customer’s online journey with behavior and purchases) are becoming less reliable as there’s simply less consumer data available for those models to use.
“As we lose the ability to track individual consumer actions…it comes down to media quality,” Ed McElvain, EVP of digital platforms and data-driven media at Mediahub, told Marketing Brew. “Attention is one of those quality signals we have considerable confidence in.”
Though there are some subtle differences in the methodologies they use, most attention metrics are grounded in eye-tracking data, which is pulled from panels and studies. That data is then applied to the geometry of a web page to determine where ads appear, their size, and how they fit alongside the page’s other content.
Those metrics can point out the obvious conclusions—bigger ads tend to get more attention than smaller ones, and a heavy ad load can distract consumers and hurt attention.
'Gold beneath the fold'
Attention metrics can also provide surprising insights, like, McElvain said, the fact that “leaderboard” banner ads at the top of websites don’t get as much attention as advertisers had previously thought, because “everybody knows that’s going to be there, [and] nobody’s looking at it.”
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One of the “big learnings” from attention metrics, is that “there’s gold beneath the fold,” Mike Follett, CEO of Lumen Research, told Marketing Brew. “When people are reading articles and really deeply engaging with the content, as they scroll down the article, that’s when they notice the ads more,” he said. In other words, high-quality content can mean higher attention.
Lumen’s attention metric can be applied post-bid to programmatic buys to estimate the audience a campaign got, and it can also be used to understand how effective ad placements are on a publisher’s site. “You’ve got a million ads: 500,000 were in view, but only 100,000 got looked at, that sort of thing,” Follett explained.
The metric can also be applied pre-bid using whitelists or custom algorithms designed to programmatically bid on high-attention inventory, he said.
Opting in
Interest in the tech appears to be growing among DSPs, and companies like Lumen and Adelaide are integrated with programmatic partners like Amazon and the Trade Desk to allow advertisers to use attention metrics to influence bids if they want to.
Crucially, though, attention can’t be—and isn’t—everything, Marc Guldimann, the founder and CEO of Adelaide, told us. If a campaign is optimized solely on the basis of attention, it could “create incentives” that lead to targeting slower readers (like older audiences or even drunk audiences), he explained.
Ultimately, he said, attention metrics should be one of many considerations in a broader marketing strategy.
“The amount of attention you pay to something is an outcome of the quality of the media, the creative, and the audience,” he said. “The outcome that advertisers should be focused on is the amount of sales they get, and they should be using attention as an input.”