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The Attention Dimension: Why attention metrics are poised to become a top priority in 2022
More than ever before, advertisers are looking to attention metrics to increase the transparency of media quality. Three key factors are driving increased attention to attention: fragmentation of reach, decay of identity signals critical for attribution, and lower cost of capturing and analyzing attention signals. Once a selling point, the malleability of digital media, and the resulting fragmentation of reach, has become a burden as digital has shifted from an experimental medium to a critical one. This movement has necessitated more accurate measurement than viewability.
Attribution, a crutch that helps advertisers mitigate fragmentation of reach, is also under pressure, as regulators, tech platforms, and consumers chip away at the identity signals required to connect ad exposures to outcomes.
Finally, enabled by cost-efficient machine-learning and better hardware, the collection, analysis, and measurement of attention metrics has moved from academic research in labs to scaled applications.
Privacy-friendly attention metrics use an evidence-based approach to create quality measures that are correlated to advertiser outcomes. They provide a multidimensional perspective of quality, helping advertisers uncover optimization opportunities that maximize media spend and improve impact.
In a 2020 study conducted by Forrester Consulting, more than 50% of US marketers said they plan to use attention metrics to understand brand lift, drive more sales, better test creative, and demonstrate media value. The following year, the industry group The Attention Council reported that the number of advertisers using attention metrics to measure media quality increased by 34%.
These trends have set 2022 up for a substantial update in how media quality is measured. It’s what Adelaide, a leader in the field of evidence-based media quality measurement, is calling The Attention Dimension.
Adelaide has partnered with dozens of clients to prove the effectiveness of our attention-based metric, AU, an omnichannel media quality score that takes into account thousands of signals and their weighted contribution to outcomes. A few of these signals include in-view duration, clutter, a placement’s size relative to the screen, and position, as well as eye-tracking and outcomes data.
To get a better handle on the impact that attention metrics are having, Marc Guldimann, CEO of Adelaide, sat down with Mike Fox, senior director of Marketing at Akili Interactive, a prescription digital medicine company that combines scientific and clinical rigor with the ingenuity of the tech industry. Here’s what Fox had to say.
How do you envision attention metrics playing a role in Akili Interactive’s strategy in the future?
At Akili, our media strategy is rooted in digital first activations that are focused on improving the level of attention captured by our ads wherever they run. We partnered with Adelaide to get closer to understanding the quality of the media we’re buying using their attention-based metric, AU, which provides an apples-to-apples quality score across formats, channels, and devices. Having a real, cross-channel understanding of media value means we can make better investment decisions based on which elements of our campaigns deliver the most efficient attention.
“Having a real, cross-channel understanding of media value means better investment decisions based on which elements deliver the most efficient attention.”
For our first campaign with Adelaide, we measured AU across four distinct channels, then analyzed these results alongside media cost data to understand cost per AU (CPAU). Initial findings showed that by eliminating OLV domains with above-average CPAU, we could significantly reduce costs. Similarly, our most expensive digital ad format cost 38% more than the cheapest, indicating even more room to optimize toward more efficient sources of attention.
Coming out of this initial test, we plan to use AU and CPAU data to find these types of efficiency opportunities and periodically evaluate our media mix. By focusing our strategy on improving attentive reach and performance against the benchmarks we’ve established, we can also improve downstream brand engagement.
What are some challenges that attention metrics are helping to solve for you?
Existing media measurement tools don’t really give us a full understanding of an ad placement’s quality. It’s kind of a black box. Just because something is viewable, by any number of industry definitions, doesn’t mean someone actually paid attention to it.
“Just because something is viewable, by any number of industry definitions, doesn’t mean someone actually paid attention to it.”
Attention to, and engagement with, our advertising is what we’re looking to achieve at the end of the day. Stated simply, attention metrics help us understand how to get more attention on our ads and the media costs associated with doing so. For example, we might choose to optimize away from placements or formats with below average AU, or shift our media spend in favor of partners that deliver higher average AU across domains.
How do you see attention metrics transforming the media industry?
Right now, the digital media ecosystem is not designed with attention in mind. The incentive is for publishers to fit as many viewable ads on the page as possible because more ads = more impressions = more money. It’s a nightmare for advertisers and oftentimes results in a terrible user experience for the person browsing the page.
Attention metrics help buyers understand what elements of their media buys display on sites that offer a distracting user experience. As brands like Akili continue to seek out high-quality inventory, I would expect that publishers will design better user experiences and users will experience ads as they’re intended—to engage and inform audiences.
What are you looking to gain from advertising attention measurement?
We’re looking to efficiently commercialize our products with digital-led strategies. While the digital ad ecosystem might be more efficient than antiquated mediums, we still think there’s a better model and AU is helping uncover improvement in our ad buys—where we can save money, which publishers and channels deliver the best ad experiences for our audiences. We’re also interested in finding the optimal mix of devices across desktop, tablet, and mobile and identifying opportunities to capture consumer attention that we may have overlooked, given the limitations of traditional metrics. Advertising attention measurement opens the door to all that.
How will attention metrics help you achieve better results?
The data we’ve collected with Adelaide thus far has given us a good foundation to build on. While the results of our first campaign show that Akili media outperformed the Adelaide AU benchmark across every channel measured, we still identified opportunities to further improve attentive reach and cut costs.
As the new year kicks off, we’re optimizing toward AU regularly and measuring the downstream impact of key brand lift metrics. Based on analysis coming out of our test at the end of last year, we anticipate these optimizations will lead to driving more attention to our ads while eliminating any underperforming placements, and ultimately, better business outcomes for our brand.
