How DOOH audiences are measured: impressions, OTS, reach and frequency

In online advertising, an impression is a served event, logged by the platform with an audit trail. In digital out-of-home the equivalent is less clear-cut: there is no straightforward way to know whether the person who walked past looked at the screen, noticed it or was within viewing distance. DOOH is still bought and sold on impressions, often quoted in the millions, and the gap between that metric and the people it stands for is a central challenge.

The short version

• Impressions, OTS, reach and frequency all start from how many people were near the screen; a DOOH impression is an estimate of potential exposure.
• A modelled audience is estimated from a traffic model or census data; a measured audience is counted at the location, hour by hour.
• Unique visitors and reach within a single day are counted without opt-in; reach over a campaign period, frequency across days and return visits need visitor opt-in.
• Footfall shows how many people were near a screen and when; it does not show how many looked at it.

Why is there no universal DOOH measurement standard?

Several competing methodologies are in use and there is no universal standard, so impressions from one network may be calculated on a substantially different basis from impressions on another. That makes cross-channel comparison unreliable, and the industry has been trying to solve the problem for years.

Even the impression multiplier, the number that turns plays into impressions, is not a standardised formula or a fixed value. In the UK, Route works with likelihood to see; in the US, Geopath publishes likelihood-to-see impressions.

Straits Research valued the global DOOH market at around $31 billion in 2025, spread across roadside billboards, metro systems, airports, bus shelters and in-store retail media networks.

What are audience currencies, and where does measured footfall fit?

Audience currencies are national measurement systems that advertisers, agencies and media owners jointly agree to trade on. In the United States that body is Geopath, which publishes audited impressions, reach and frequency for OOH inventory. In the UK it is Route, the joint industry currency for out-of-home, owned collectively by advertisers, agencies and media owners.

A currency gives one market a shared basis for trading, but each methodology still starts from an estimate of how many people were at a location. Measured footfall is that number counted on site. Any audience model needs it as input, whichever currency a market trades in, and buyers can use it to check modelled numbers.

What are the core DOOH metrics: impressions, CPM and the impression multiplier?

In DOOH, an impression is a potential exposure: an estimate of how many people had a plausible opportunity to see a play. The impression multiplier is the estimated number of people who see one play, and a DOOH CPM is the price of a thousand impressions.

Impression multiplier. Because one play on one screen reaches many viewers, the multiplier converts play counts into impression counts, and programmatic DOOH pricing depends on it. It needs real footfall data as its input.

CPM. Media cost divided by impressions, multiplied by one thousand. What varies is the impression count in the denominator: a CPM computed from measured impressions is a reliable price, while one computed from inflated impressions makes the media look cheaper than it is.

Plays (or spots) and loop. A play is one showing of an ad. Screens run a loop (a repeating sequence of ads of fixed length), so an ad’s share of the loop determines how many plays it receives per hour of screen time.

Share of voice. The proportion of a loop, or of a network’s total plays, that one advertiser occupies.

Dwell time. How long people stay near a screen. It determines how much of the loop an audience has time to see: a metro platform where people wait for minutes is a different proposition from a corridor they cross in seconds, even at identical footfall.

How is OTS calculated?

Opportunity-to-see (OTS), one of the most widely used DOOH metrics, starts from a traffic or footfall count and asks how many of those people were in a position to see the ad. The calculation involves assumptions about viewing angles, minimum legible distances, average movement speed and the share of passersby likely to glance at a screen.

Those assumptions vary by methodology, but the input has to be right for any adjustment to mean anything: a figure based on an outdated traffic model, or estimated from census data instead of measured, carries an error that later adjustments are unlikely to correct.

Does it matter whether a DOOH audience is modelled or measured?

Yes. A modelled audience is estimated from a traffic model or census data, and a measured audience is counted at the location, hour by hour. Either can feed an OTS calculation or an impression multiplier, and an error in that input passes through every adjustment.

It matters most in programmatic DOOH, a growing share of inventory, where deals are priced per impression and a multiplier is applied to each play. On a modelled traffic figure the multiplier passes the model’s error to every buyer in the chain; on measured footfall it gives counts that stand up when buyers further along check them. Operators and advertisers should ask for verified footfall counts for the screen location, ideally by time of day and day of week, plus any dwell or proximity data showing how long people were near the display. They should also keep raw circulation figures and adjusted OTS estimates apart: both have their uses, but they are different numbers.

Measured counts can come from sensing at the location, such as Wi-Fi-based sensing, or from mobile network data at outdoor locations such as high streets, transport interchanges, open squares and motorway services. Operators process aggregated, anonymised data about device presence, which can be turned into counts of people in a defined area and time window, with nothing installed at the screen. Because it counts presence in an area, it covers pedestrians, cyclists, motorists and transit passengers alike, and it does not show which of them looked at the screen.

How are reach and frequency measured in DOOH?

Reach is the number of distinct people who passed a screen during a campaign period, and frequency is how many times the average person in that audience was exposed. In Bumbee Labs’ measurement, unique visitors and reach within a single day need no opt-in; reach over a campaign period, frequency across days and return visits require visitor opt-in.

Both need a counting method that tells repeat visits from unique visitors; across several days, that is what requires opt-in. Reach and frequency carry over well from online into DOOH, and together with exposure duration they are the basis of credible OOH impressions reporting. Footfall data can support both within those limits.

At high-footfall locations like transport hubs or shopping districts, the same people pass through again and again. A commuter who passes the same concourse display five days a week counts as five impressions in a raw OTS figure, and as one reach unit with a frequency of five only with opt-in. Planners building campaigns with reach objectives need that distinction.

How can you tell whether a DOOH campaign moved anyone?

Anonymous, aggregated measurement can show a campaign’s impact on footfall at the population level. It cannot do individual-level attribution (tracing a specific person from a screen exposure to a store visit), and claims to the contrary deserve scrutiny, especially in Europe.

Measure footfall at the destination before, during and after the campaign, and compare it with a baseline that accounts for weekday rhythm and seasonality. The campaign’s effect appears as a deviation from what the location would have done anyway. It is the same before-and-after method used for measuring event impact. The claim it supports (footfall rose by this much while the campaign ran) is more modest than an attribution chain, but it stands up, and no individual can be identified in the data behind it.

Events create a different challenge: a market, a festival, a concert or a product launch can temporarily multiply the audience at a location well beyond its baseline. The time-stamped counts in the data deliverables show when those spikes occurred and how large they were, so they can be used to measure an event’s effect on DOOH exposure as well as on commercial footfall.

Does footfall data show who looked at the screen?

No. Overclaiming is a recurring problem in DOOH measurement. Footfall counts tell you how many people were near a screen and when; they do not tell you how many looked at it, how long they spent looking, or whether the creative registered.

Attention measurement, which points camera sensors at passersby, is a separate category with its own privacy implications and stricter regulatory requirements across Europe. A footfall-based OTS figure is the more modest but more defensible claim: this many people were in a position to see the screen. Stated accurately, it is a useful planning number, and inflating it erodes advertiser trust in the medium.

The measurement is anonymous throughout. Mobile network data and Wi-Fi-based sensing both produce aggregate statistics (counts and patterns) rather than records of individuals, with no profile attached to any passerby, no journey reconstructed and no identity inferred.

How do you measure your own DOOH screens?

If you own or sell DOOH inventory and want these numbers for your own placements, the page on DOOH audience measurement shows how they apply to individual screens and placements: what is measured per screen and slot, and how it is delivered.

Sources

• Straits Research (2026). Digital out-of-home (DOOH) advertising market size, share & trends report, forecasts 2026–2034. Last updated 24 August 2026. https://straitsresearch.com/report/digital-out-of-home-advertising-market
• Route Research (n.d.). About Route. https://www.route.org.uk/about-us.php
• Geopath (n.d.). Geopath audience measures & API outputs. https://geopath.atlassian.net/wiki/spaces/GEOP/pages/2323447870/Geopath+Audience+Measures+API+Outputs
• Mason, Q. (2024, 29 October). DOOH impression multiplier: What it is and how it enhances digital out-of-home ad measurement. Broadsign. https://broadsign.com/blog/the-impression-multiplier-what-is-it-and-how-does-it-apply-to-dooh/
• European Data Protection Board (2020). Guidelines 3/2019 on processing of personal data through video devices (version 2.0). https://www.edpb.europa.eu/system/files/documents/files/file1/edpb_guidelines_201903_video_devices_en_0.pdf