DOOH Audience Impressions White Paper

Executive summary

Quividi is the largest independent international digital out-of-home audience measurement provider in the world, measuring billions of advertising audience impressions every month.

Standards definition

Quividi meets or exceeds the highest standards of online and out-of-home audience measurement (IAB/3MS, ESOMAR and DPAA) and is future-compatible with the upcoming cross-platform audience standard (IAB/3MS). This is demonstrated in the context of audience measurement standards history as well as the cross-platform roadmap of the future.

Quividi has adapted online audience standards to out-of-home, which requires extending the definition of a “viewable impression” to consider audience facing direction and the maximum viewing distance of a DOOH display.

Methodology disclosure

Quividi employs privacy-safe computer vision algorithms to detect faces in a video stream from a standard web camera. Using a proprietary visibility adjustment methodology, the detection metric (faces) is converted into a cross-platform audience impression in a way that adapts for all screen sizes, camera resolutions, camera angles and venue types. This audience data is then married with CMS ad playback data to determine the audience of a particular ad.

Quividi’s entire methodology, from face detection to conversion into standard impressions, is documented for scrutiny by all media stakeholders (advertisers, agencies, platforms, publishers, auditors, accreditors). This includes the parameters of performance and the method to ensure the highest level of data fidelity and human validity.

Comparison checklist

Quividi’s level of advertiser accountability is compared using a 10-point checklist with alternative methods such as mobile “bidstream” data and traditional out-of-home measurement based on surveys and historical circulation data.

While mobile bidstream data is not as good as computer vision data for measuring impressions, it is a great complementary data set that can be used to solve marketing problems such as affinity targeting, footfall attribution and reach vs frequency calculation.

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