By Jeremy Kanterman, Vice President of Research & Insights, IAS
Integral Ad Science has been on the forefront of defining and advancing the concept of Attention in digital advertising. Based on extensive advertiser campaign data and groundbreaking AI, IAS has already built a first-of-its-kind Attention model, which found that Attention is a function of visibility, situation, and interaction and must drive business results.
Today, IAS is taking another major leap forward in expanding the industry standard for effective Attention measurement by announcing that we are now working with Lumen Research to bring cutting-edge eye-tracking technology and predictive attention models to the market. This marks the first-of-its-kind integration between a major media quality company and an eye-tracking firm.
By combining IAS’s unparalleled technology and actionable data with Lumen’s expertise in eye-tracking, our customers will have an even more powerful way to accurately track which ad impressions have captured attention and are likely to lead to a business result. We chose to partner with Lumen Research because of their unique approach to creating predictive attention models derived from years of eye-tracking research on web browsing that can be used to measure the expected attention of a digital ad campaign.
Mike Follett, Lumen’s CEO, shared his crisp, clear philosophy: “We know that attention-first advertising drives better results, helps create better ads, and ultimately gives consumers a better experience.”
IAS + Lumen Attention & Media Quality Analysis
Earlier this year, we partnered with Lumen and a major sports retailer to understand the relationship of IAS’s viewability and time-in-view data with Lumen’s attention data set. In this study, we examined the impact of media quality and attention on the sports retailer’s advertising campaign running in a global sporting event.
In order to do this, we measured the attention each ad received by combining Lumen’s focus data (eye-tracking) with IAS’s viewability data.
We found that in-view ads amounted to 64 times higher attention than those that were not in-view. Additionally, we saw that ads with time-in-view rates longer than 15 seconds experienced the highest attention in the study. And, of course, context played a critical role too. URLs with content most aligned to the campaign strategy generated 2.5 times higher attention for the advertised brand compared to other content categories.
Eye-tracking and IAS’s Attention model
Eye-tracking will be a key component of IAS’s first-of-its-kind Attention model. After analyzing millions of advertising data signals, our research team identified three crucial signals that can predict the likelihood an impression will lead to a result: visibility, situation, and interaction.
Visibility signals, which include metrics like viewability and time-in-view, measure the validity of the impressions being served. Situation signals describe the environment in which impressions are served and include measurement of the number of ads on a page and the percent share of voice (SOV) an ad has on a page. Finally, interaction signals are indicators of consumer activity in the presence of ads, monitoring activity like scrolling, volume, video player play/pause, and eye-tracking.
With the use of Lumen’s proprietary eye-tracking technology and attention tags, IAS will have even greater insight into the interaction Attention signal, helping marketers understand exactly where consumers fixate in the presence of ads. Lumen’s tech will add even greater value to our Attention model through the use of one of the world’s largest consumer panels for the most accurate picture of attention, as well as Lumen’s data-backed predictive models.