The impression multiplier, explained

The number a beauty DOOH buyer pays against — the audience impression — is not counted, it’s modelled. One ad play on one screen is projected to the people who could have seen it via an impression multiplier. Understanding this one mechanic explains why DOOH impressions are estimates, why they vary between vendors, and why you should report them as estimates, not measured viewers.

The formula

DOOH’s core counting mechanic is simple to state. A play is one airing of the creative on one screen; an audience impression is one estimated viewing by one person. Because several people can be in front of a screen during one play, the conversion is (Broadsign — primary):

served impressions (ad plays) × impression multiplier = audience impressions

Broadsign’s canonical example makes it concrete: 10,000 plays × a multiplier of 4 = 40,000 audience impressions — “estimated to have reached an audience of 40,000 people.” The plays are measured; the 40,000 is a model.

It’s per-screen and publisher-set

The multiplier is not a constant. It is customised per screen by the media owner, derived from that screen’s own audience data — proprietary surveys, anonymised mobile-location data, third-party research (Geopath/Nielsen), or camera/sensor counts — and it varies by hour, day and placement (Broadsign — primary). A flagship mirror screen in a high-traffic salon carries a different multiplier than a back-room display. Crucially, Broadsign states the multiplier is “not standardized, rather customized per screen” — so the ”× 4” in the example is one illustrative value, not a norm to copy.

One subtlety from the programmatic standard: the multiplier can be greater or less than 1 — fractional values such as 0.32 impressions per play are common, because it’s statistical modelling, not a head count (IAB Tech Lab — primary). In OpenRTB 2.6 it rides on the imp.qty object (imp.qty.multiplier / sourcetype / vendor).

The standardised inputs

The OAAA’s exposure methodology standardises the inputs to the estimate, even though the output multiplier isn’t fixed — three required variables (OAAA — primary):

Venue data — what and where the screen is.
Movement data — how people flow past or dwell in the exposure zone.
Ad-play data — what ran, when.

The core metric is the opportunity to see. And one honesty point the methodology itself stresses: presence is not an impression. Mobile-location data establishes that a device was nearby — the most basic qualification — but it “is not the same as an impression, in which case a person would have to actually look at a display.” Presence is at best a good proxy once filtered for the cone and direction of exposure.

The 20–30% variance — why vendors don’t agree

Because the multiplier is publisher-set and modelled, different vendors model it differently — and the gap is material. DOOH impression methodologies vary by roughly 20–30% between vendors, depending on how exposure, dwell and audience movement are modelled, and there is no universal data standard for programmatic DOOH the way there is for display (directional — repeated consistently across trade sources). The practical consequence: two “40,000-impression” figures from different vendors are not the same media. Don’t compare impression counts across sources as if interchangeable, and don’t treat a modelled total as a measured one.

How to report it honestly

For an advertiser or operator, the discipline is the same:

Report impressions as a disclosed estimate — name the multiplier and its data source, and label it an estimate, not a measured viewer count.
Report plays and proof of play as fact — those are measured.
Don’t borrow another vendor’s multiplier for your screens — it’s screen-specific.
Frame attention separately — even a real impression isn’t an “eyes-on” guarantee (see attention benchmarks).

This is also why there’s no shortcut to a beauty impression benchmark: every credible number is a per-screen estimate built from that venue’s own data. (The full measurement chain is in Measuring & reporting to clients.)

Methodology & caveats

Verified (primary): the impression-multiplier formula and the 10,000 × 4 = 40,000 illustrative (per-screen, non-standardized) example from Broadsign; the one-to-many / fractional-impression model and imp.qty carriage from the IAB Tech Lab (OpenRTB 2.6); the OAAA exposure methodology (venue + movement + ad-play data; OTS) and the “presence ≠ impression” caution from OAAA / DPAA materials. Directional: the ~20–30% inter-vendor methodology variance and the lack of a universal pDOOH data standard (repeated consistently across trade analyses). Not asserted: any standard/universal multiplier value — ”× 4” is Broadsign’s illustration, not a norm — and any beauty-specific multiplier or impression benchmark, which would be per-screen and modelled regardless.