Debunking DBAMs: Why Advertisers Should Focus on the Probability of Attention Over Duration

In pursuit of more precise media quality measures, advertisers have gravitated toward attention metrics. While many have seen success using attention metrics to drive incremental outcomes, some have fallen victim to the pitfalls of Duration-Based Attention Metrics (DBAMs).

What are DBAMs?

DBAMs, which emerged around 2015, measure or predict attention to advertising based on the duration of attention, usually in seconds. Initially, these metrics were hailed as game-changers. After all, researchers had proven that longer durations of attention led to increased impact through the marketing funnel. On the surface, this made sense: the longer someone spends with an ad, the better the outcome. So, it seemed logical for advertisers to assess media quality and optimize campaigns based on attention duration. Unfortunately, as Goodhart’s law forewarned, “When a measure becomes a target, it ceases to be a good measure.”
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The Consequences of Maximizing Attention

Marketers who deployed DBAMs as KPIs quickly discovered they weren’t just optimizing media—they were also optimizing creative and audience to the maximum attention. 

Optimizing creative towards duration of attention can create a bias for more salacious or eye-catching content. While effective for increasing time spent with an ad, this approach doesn’t always elicit the kind of attention that delivers positive outcomes. Optimizing impressions towards the audience likely to pay attention the longest is even riskier. Data shows that older demographics, individuals who are already brand aware, and even those under the influence spend more time viewing content—a phenomenon Adelaide termed The Attentive Audience Paradox.
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The Solution? The Probability of Attention

Attention metrics that extract the impacts of creative and audience can help advertisers avoid the effects of The Attentive Audience Paradox and achieve better advertising outcomes. 

We believe a media placement’s job is to create an opportunity for attention, which creative then capitalizes on. Therefore, measures of media quality should focus on a placement’s probability of capturing attention versus how long it sustains attention. 

Above all, marketers should use attention data to inform media investment decisions rather than as a campaign target, allowing them to tune algorithms to drive the best possible outcomes.