How Quividi Fuels DOOH Programmatic Trading

How Quividi Fuels DOOH Programmatic Trading

In November 2018, IAB released OpenRTB 3.0 which contains the programmatic pipe adaptations necessary to handle digital out-of-home transactions. The change in question was to add the impression multiplier field, which indicates how many audience impressions will be generated by an ad exposure – in other words, to indicate to how many people the ad was viewable.

Quividi has two methods by which a DOOH publisher can easily get standards-compliant audience impressions data ready-to-use by programmatic platforms:

  • Server-side: Export/import using historical data;
  • Client-side: Real-time API using live data.

In this article, we will also compare Quividi’s data to an alternative digital measurement method using mobile bidstream data.


The most common method today for a DOOH publisher to indicate their screen’s audience is to provide a table which contains, for every location and every hour of the week, the impression multiplier to use for the programmatic auction. Quividi calculates the impression multiplier by averaging the audience for that location/week-hour and taking into consideration the duration of the proposed ad.


We call this export the Average Unit Audience, where unit is referring to the “ad unit”, sometimes referred to as a slot or spot duration.

In the above example, a 15 second advertising running a Monday at 10AM on screen 48338 will likely generate 2.314 audience impressions when it will run. This number can further be broken down by gender and age group.

Demographics Segmentation

The Average Unit Audience (AUA) Export can also be further segmented into genders (male, female) and each gender into age groups (<17, 18-24, 25-34, 35-44, 45-54, 55-64, 65+).

Note: demographics segmentation is not yet supported in the OpenRTB standard, though the data may otherwise be used by programmatic platforms such as for direct buys.

Period of study and Refresh Frequency

The period of study can be as little as 3 weeks of data for newly deployed locations to 3 months. The refresh frequency could be as frequent as monthly for quickly growing networks to annually for already ingested locations.

Any import- and export-based data model will unfortunately always be based on outdated data and is vulnerable to inaccuracies such as missing seasonal audience shifts.


With a sufficient sample size and proper random selection methods, measured locations’ data can be extrapolated to non-measured locations to give them audience coverage as well. The extrapolated locations audience are modeled after the averages of the sampling locations.

Quividi’s method involves having some locations equipped with always-on measurement and others which are virtually measured (using averages). This approach, with the right sampling size, guarantees that the extrapolated results for each screen will be +/-20% of reality in 95% of the cases.


In order to deliver the same level of advertiser accountability that is standard online, Quividi provides a highly local, highly recent measurement solution tuned for the needs of DOOH. Programmatic SSPs use the so-called Predictive API to make use of Quividi audience data in the construction of their real-time bidding (RTB) bid requests. Think of it as a pre-bid request.


For example, most RTB auctions are for the current ad slot, but in DOOH it may be auctioning the next slot in the playback sequence. Quividi’s API allows for these types of near-time queries. 

The protocol of live data exchange between the DOOH SSP and Quividi VidiReports. the DOOH SSP uses the audience report from Quividi to build its bid request for programmatic RTB auction.

The predictive audience estimate is generated using a local database of current and historical data and is far more dynamic (sub-second granularity and latest audience trend) than server-side equivalents (hourly granularity and averaged trend).


Another unique feature of local measurement is it enables post-campaign audience analysis in DOOH – something that is usually only available with online media. This is possible due to an integration with the 3rd Party CMS used by the DOOH Publisher to operate their network. By integrating with the content playback data, Quividi is able to scope measurement to the airtime of a single ad play. The protocol of live data exchange between the CMS and Quividi is illustrated below.

The protocol of live data exchange between the DOOH CMS Player and Quividi VidiReports. If the CMS supports receiving audience reporting (step 3), its reporting can later be verified against Quividi’s.


While the online programmatic world is based on standards that require a live client-side data protocol, out-of-home has historically been based on historic averages and server-side audience. Quividi adapts to both, which makes it compatible with DOOH-oriented programmatic as well as its online programmatic counterparts.

Quividi provides to DOOH publishers two methods by which they can get audience data so they can start trading:

  • Server-side: using historical data;
  • Client-side: using live data.

While the server-side method is the most common one method of exchanging this data today, the client-side method is most future-safe method, since it meets the highest standards of audience measurement online. Mobile bidstream data cannot currently provide this level of digital standards compliance.dictive

Understand why Quividi is the best audience measurement platform for your company.