How is your OOH Media Measured? (Hint: there’s a better way)

by | Jun 29, 2020 | OOH Measurement

As the Out-of-Home (OOH) advertising ecosystem grows, so too does the demand for consistent and actionable media measurement. New technologies are emerging to meet this demand. But the OOH measurement service provider landscape is still fractured. Most traditional solutions are outdated, and new solutions use differing technologies. So, what are the differences, and which solution is best?

Well, it depends on a given marketer’s needs. Let’s take a look at what’s available.

The Current Standard

Traditionally, OOH media buyers and sellers have relied on a handful of established measurement providers to deliver impression reporting for their campaigns. How do these conventional providers quantify audience exposure? They analyze government-funded vehicular traffic studies and, with a bit of extrapolation, create impression estimates based on historical averages. A one-time impression estimate is then delivered to the buyer or seller, either before the campaign begins or after the campaign concludes.

This form of measurement is standard and consistent, but it has serious limitations. Impressions are roughly estimated based on data from traffic studies that are updated annually or, at best, quarterly. This methodology fails to take into account pedestrian foot traffic, meaning that impressions are almost always underreported. Changing traffic patterns, along with dips and surges in audience size, are missed completely. Reporting is not delivered in real-time (not even close-to-real-time), and performance metrics begin and end with impressions, making attribution next to impossible.

This method of reporting has been accepted because there was nothing better available. But with the rise of new technologies and access to actionable data sources, the dominance of old-school measurement providers is being challenged in a big way.

Let’s check out some alternative measurement solutions that are now offered in the marketplace.

Alternative Solutions

1. Panel Based Data (Digital Surveys)

Surveys have been around for ages and will always be valuable. They employ user-based self disclosures against desired outcomes to measure campaign performance. Surveys tend to yield accurate and deep responses, but the scale of data is dependent on sample size and frequency (poor scale), and they take a while to generate. Surveys are useful for long-term audience analysis, but they don’t allow for short-term/real-time impression measurement.


  • Accuracy (precision)
  • Depth of information


  • Sample size and frequency of panels limits amount of data (poor scale)
  • Delay in analysis from panel response (not ongoing/near-real time)
  • Not useful for measuring impressions

2. Wi-Fi Sniffing

Wi-Fi “sniffers” use Wi-Fi technology to scan (or ‘sniff’) mobile devices within 300 feet of an ad to measure exposure. Sniffers enable near-real time reporting with good accuracy and scale. But a Wi-Fi device must be installed on or near the ad, and users need to have Wi-Fi turned on and be visible. Sniffers are generally effective for measuring place-based ad exposure, but attribution is tricky to determine. Moreover, sniffers aren’t effective for measuring moving ads.


  • Accuracy (broad range)
  • Scale
  • Broadly available
  • Ongoing (real-time)
  • Measures Overall Impressions, Dwell Time, Frequency.


  • Requires user to have Wi-Fi turned on
  • Requires device installation
  • Accuracy is not precise for a subset of screens due to max range being 300’
  • Hard to capture mobile device IDs – attribution is difficult to measure
  • For moving ads: it’s very difficult for a moving person to capture the Wi-Fi signal from a moving ad

3. Geolocation Data (Time-Stamped GPS Pings)

Marketers can measure OOH ads by analyzing geolocation data from mobile devices. There are two main types of geolocation data:

  1. SDK location data – Delivered from apps where consumers opt in to allow access to their location information.
  2. Bid Stream location data – Delivered when a consumer is using a mobile app with location services turned on while viewing an ad in-app.

SDK location data delivers good accuracy and excellent precision, but scale is dependent on the volume of SDK installs. However, scale improves with enough data partners.

Bid-Stream location data tends to have poor accuracy and low precision. However, Bid-Stream data can add scale when combined with an SDK dataset.

Both SDK and Bid-Stream data enable near-real-time reporting.

With the right data partners, location data allows measurement for nearly all types of OOH media, and opens the door to easy attribution through the collection of device IDs.

SDK Advantages:

  • Accuracy
  • Excellent precision
  • Ongoing (near real-time)

SDK Disadvantages:

  • Scale limited due to user opt-in requirement
  • Frequency of location updates may be limited by device settings

Bid-Stream Advantages:

  • Scale
  • Ongoing (near real-time)

Bid-Stream Disadvantages:

  • Frequency of location updates may be limited (user must be viewing in-app ad at time of exposure)
  • Poor accuracy
  • Low precision

4. Bluetooth Beacon

This solution uses Bluetooth technology to scan mobile devices within 10-100 feet. It delivers excellent accuracy and precision. However, beacons have several drawbacks. Beacon devices must be purchased and installed on/around an ad. 100 feet is the maximum effective range of the beacon. Users must have Bluetooth turned on, be visible, and they must have downloaded the advertiser’s app. These caveats drastically reduce scale. Due to these drawbacks, beacons aren’t ideal for measurement, but they do enable attribution. They are most effective when measuring smaller place-based ads in high pedestrian traffic areas.


  • Accuracy (precision in geo)
  • On-going (near real-time)
  • Directional configuration and data capture
  • Opens gateway to Attribution


  • Scale
  • Beacon cost
  • Requires physical installation of sensors on Vehicle/Screens.
  • Requires app to read beacon signal
  • User Bluetooth must be turned on
  • 100-foot maximum measurement radius
  • For moving ads: it’s very difficult for a moving person to capture the beacon signal from a moving ad

5. Camera Sensor

Innovations in camera and AI technology make camera sensors an attractive choice for marketers seeking to measure their OOH ads. Modern cameras use vision algorithms to anonymously analyze users passing an OOH ad, making it easy to measure impressions in real-time. Accuracy and precision are both very good, although scale is dependent on camera installs (camera sensors are expensive and must be installed on the ad). Moreover, camera sensors don’t enable attribution. Camera-based measurement begins and ends with impression reporting, albeit very good impression reporting.


  • Ongoing (real-time)
  • No opt-in required
  • Accuracy
  • Precision


  • Requires physical installation of sensors on Vehicles/Screens.
  • Camera Cost
  • Does not enable attribution
  • Tendency to Double/Triple Count impressions for transit/moving ads


So, which solution is best? It depends on your goals as a marketer. When choosing a measurement solution, ask yourself: What type of media do I want to measure? How deeply do I need to measure? Do I only care about impressions, or am I trying to prove attribution? How quickly do I need reporting?

Each solution has its advantages and tradeoffs, so a combination of solutions might be the answer. If you are seeking to accurately measure impressions and attribution at scale for a large digital billboard or a double-decker bus ad, geolocation data combined with camera sensors could be your best strategy. It just depends on what you’re trying to accomplish. Consider the cost, scale, accuracy/precision, depth and delivery time for every option to find the solution (or solutions) that’s best for you.

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