Technology OMD Martech

What we have learned in 6 years of measuring attention

By Jean-Paul Edwards |



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November 1, 2021 | 5 min read

Attention is a hot topic right now – this wasn’t the case six years ago when we started our attention journey in Finland with visual attention martech company Viomba.

OMD on how technology and data has evolved our focus on visual attention martech.

OMD on how technology and data has evolved our focus on visual attention martech

After years of working with digital attribution models, it was clear that there was too narrow a view of marketing effectiveness. The click/conversion approach had flaws, and all manually-set weighted models did not tell the entire story.

Our first attention measurement with real campaign data, real panelists and connected eye tracking in 2015 showed visual attention levels were, on average, only 21% – so almost 80% of the carefully-crafted story was at risk of not making an impact.

In digital media, vast budgets are invested for opportunities to be seen. The more marketers start analyzing attention levels, the more competitive strategies they can create. Using attention martech to instantly predict what proportion of impressions and creatives will be visually seen in live media, for how long and at what cost, brands can now competitively stand out from the attention clutter.

Over the years, the visual attention data pool has expanded to over 1m impressions, on different ad formats, various site placements and markets, allowing us to define principles for brands seeking to maximize their digital marketing effectiveness with attention.

Insight 1: different channels, different challenges to solve

Viomba data shows that social media channels deliver, on average, high initial attention levels as horizontal news feeds don’t require our eyes to work as hard. However, focused attention drops if the brand is not recognized, or the ad can’t create sufficient attention pull with other users.

It also highlights how varying screen sizes create different visual environments. Instant attention levels on mobile average higher, and there are less low-attention placements. On desktop, despite our eyes working harder to detect objects, they have more freedom to maneuver, meaning focused attention and memory impact is often more intensive and longer than mobile. TV’s full-screen ad messages mean attention only competes with the surrounding environment.

Insight 2: media selection and ad format are powerful levers

Attention varies greatly, with almost 10x between the best and worst media selection and almost 5x between the best and worst desktop ad format on desktop. The differences on mobile are lower. There is no correlation between media prices and high attention levels, as formats are priced by size/length and opportunity to see, not on what is visually more likely to be detected.

Long-term attention data across various markets shows media environments that require a fundamental rethink. On regularly used sites, visitors have learned to browse to avoid ads. On the buy side, a greater variety of sites and more dynamic formats should be considered to gain higher attention levels. On the sell side, ad formats and media-specific placements should be shuffled regularly to keep visitors curious.

Insight 3: there are attention golden hours

People’s attention levels differ throughout the day – such as early morning, when our visual attention responses are above average.

Insight 4: attention benchmarks differ across markets

Comparing attention data between markets shows significantly different levels of attention for campaigns with similar parameters, with a strong correlation between heavier advertising levels and lower attention levels. In markets with higher ad loads, attention metrics should be optimized against local benchmarks – it is critical to use tactics learned from continuous attention measurements to stand out.

Insight 5: two distinct creative challenges

Creative assets face two related but distinct challenges – to capture and to keep our attention.

There are clear learnings to help marketers capture initial attention – for example, DCO tools test different creative approaches and find above-benchmark attention levels.

The challenge is how initial visual attention progresses to continued engagement that is specific to the brief – one day memory impact requires three seconds of focused attention. Since successfully attended display ads generate less than three seconds fixated gaze time, impactful exposure frequency is required to reach efficient memory impact. With actionable and well-integrated attention, martech marketers can understand exactly how to develop their creative and buying strategies to keep attention levels strong – providing initial attention is captured.

Visual attention martech has evolved in the last six years. Attention data has been enhanced with artifical intelligence (AI) algorithms, and the empirical data is constantly looped with AI to keep up with ever-changing media. Partnering with Viomba, we’ve integrated its industry-leading attention martech into our local media buying systems to fit buyer’s existing work routines. Attention data is driving better attribution modeling and high attention ad inventories, as the new digital marketing currency moves away from theoretical CPM and toward real attention-based aCPM (seen). Marketers should only be considering ads that realistically capture existing KPIs.

Jean-Paul Edwards, chief product officer at OMD, with editorial input from Teemu Neiglick, chief executive at OMG Finland, and Markku Mäntymaa, chief executive and founder at Viomba.

Technology OMD Martech

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