Using attention metrics to optimize frequency & recency

AU, a new metric created by Adelaide, takes an omnichannel approach to a per-placement scoring model which can be used by marketers to replace or augment viewability or video completion rates. AU is expressed on a scale from 0-100, generated by machine learning which is tailored individually for each channel measured, and can also be used to measure against other marketing placements such as audio, CTV, and linear TV.

Reach, frequency, and recency are foundational themes in advertising efficacy that have been discussed ad nauseum since the dawn of mass media. Even as the technology to track advertising approaches surveillance levels, effective reach and frequency remain central to advertising and media planning.

The continued discourse is fueled, in large part, by the fragmentation of media and the proliferation of ad formats, which chip away at some of the model’s original assumptions. Even when media channels were more consolidated and consistent than they are today, researchers understood that varying levels of attention needed to be accounted for. Definitions of effective...

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