What marketers need to know about measuring attention metrics

Attention metrics are gaining popularity as marketers seek ways to diversify their data and measurement strategies:

• 47% of US brands and agencies will be somewhat or significantly more focused on attention metrics in 2024, according to November 2023 data from the Interactive Advertising Bureau (IAB).
• Nearly a quarter (24%) of US agency and marketing professionals plan to use attention metrics to mitigate measurement issues, per March 2024 data from IAB.

Breaking it down: Attention metrics can be made up of one or more of the following, according to the IAB’s Attention Measurement Explainer:

• Visual or audio tracking (e.g., eye tracking, facial coding)
• Physiological or neurological tracking (e.g., heart rate, blood pressure)
• Data signals (e.g., ad placement, publisher metadata)
• Survey-based methods (e.g., focus groups, brand health studies)

Collecting biometric data like facial coding or heart rate usually requires a device, which can be a barrier to adoption. Plus, techniques for observing and analyzing this data are contested among providers and could pose privacy risks, according to our Attention Metrics 2023 report.

But data signals, which include how an ad looks on a screen and the actions a user takes while watching an ad, don’t require any additional hardware to collect.

The signals leverage existing device signals and publisher data, collected through technologies like JavaScript Tags, the Open Measurement Software Development Kit (typically used in mobile app environments), and server-to-server/API integrations.

The benefits of attention metric measurement: Tracking attention metrics provides marketers with immediate feedback on ad performance, helping them optimize campaigns while in-flight, per the IAB’s Explainer.

• Attention metrics scale across campaigns and audiences.
• Using attention metrics, marketers can benchmark performance across industries, verticals, platforms, campaigns, and time frames.
• Attention metrics offer a way to measure performance without relying on cookies or device IDs.

The drawbacks: While data signals help marketers understand how consumers interact with ads, they give little insights into user motivations and sentiments.

• Access to data signals may be inconsistent, limited, or restricted across certain environments, devices, or channels. Podcasts, smart TVs, or walled gardens, in particular, can present challenges for marketers.
• There’s also room for potential bias. For example, a user fast-forwarding or muting an ad doesn’t necessarily indicate a change in sentiment or negative correlation.

The bottom line: Attention metrics can be an effective way to gauge campaign performance, especially as data signals like third-party cookies face an unknown future.

Signal-based attention metrics are just one part of the measurement mix—especially when it comes to walled gardens or connected TV (CTV).

• Marketers may consider attention metrics that incorporate panel-based biometric data for these specific channels or services.
• But across the board, data-collection methods should comply with privacy regulations, especially with more states enabling comprehensive privacy laws.

This was originally featured in the EMARKETER Daily newsletter. For more marketing insights, statistics, and trends, subscribe here.