DOOH Audience Measurement

Compare reach and exposure across DOOH sites.

Measure circulation, reach, and exposure in one workflow. P2ACH AI selects Vision AI or Wi-Fi for the site and keeps metric definitions visible in every report. Where camera views allow, add viewing and dwell signals.

Request a DOOH measurement demo

Start with one site to see which reach, exposure, and reporting views it can support.

Busy urban intersection with pedestrian and vehicle circulation — We design the measurement scope around each site, media position, and operating environment.

Audience circulation
Reach & exposure
Viewing & dwell
Site comparisons

Give buyers a clear basis for comparing DOOH sites

Start with one commercial question: site pricing, location comparison, or delivery reporting. Every result stays tied to its definition and validation conditions.

Audience

Show when and where the audience is present

Compare traffic by location and period, then define the circulation and exposure metrics needed for the media decision.

Delivery

Explain the path from circulation to exposure

Use media position, sensing coverage, and site definitions to separate nearby traffic from the agreed exposure signal.

Reporting

Compare sites with one set of definitions

Give sales and operations the same dashboard view, reporting output, and interpretation rules.

Design the measurement around one media question

Connect the commercial question to a site-appropriate method and a repeatable reporting format.

01
Scope the medium and audience question
Review location, media geometry, operating hours, traffic patterns, and the decisions the data must support.
02
Design sensing and metric definitions
Select an appropriate Vision AI or Wi-Fi configuration and document how each reported metric is calculated.
03
Build the site reporting plan
Compare results with a site-specific baseline, then define the reporting format and conditions for expansion.

On-device Vision AI for DOOH measurement

For camera-based measurement, task-specific Vision AI models run person detection, tracking, and viewing or dwell inference at the media site, then turn those signals into the agreed circulation, reach, and exposure metrics. Transmission, retention, and access are defined separately for Vision AI and any Wi-Fi data used.

Models are configured to the field of view, media geometry, traffic pattern, and reporting definition for each site.
Video, derived images, events, and aggregate metrics are separated in the documented data flow.
Where video export requires masking, it follows a separate review and approval workflow from audience measurement.

See the reporting outputs behind each metric

The demo connects each reporting view to its metric definition and measurement method.

Circulation, reach, and exposure metric definitions
Site, period, and media comparison views
Vision AI and WiFi coverage assumptions by environment
Viewing and dwell signals where camera coverage supports them

AI AGENT Integration review

Define the questions an AI Agent should answer

DOOH AI Agent access is not enabled by default. During the demo, we review whether approved site, period, circulation, reach, and exposure data can connect to an AI Agent approved by your organization—and define the questions before an integration is scoped.

Questions for an integration review

Compare circulation, reach, and exposure by site over the last four weeks.
Which sites and time bands changed the most, and which measurement conditions should we check?
If proof-of-play records are connected, separate them from reach and exposure in an advertiser summary.

Availability depends on the connected dataset, approved data-access permissions, and agreed integration scope. Sampling, coverage, and metric definitions remain visible, while CPM and pricing decisions stay with the responsible team.

Concept illustration showing authorized data flowing through an access boundary to an AI reasoning layer and evidence-backed answers — Concept illustration of permission-scoped data and evidence-backed answers

P2ACH ONTOLOGY · CROSS-SOLUTION REVENUE INTELLIGENCE

Connect data from four solutions to assess revenue impact.

P2ACH Ontology connects advertising, visit, path, and shelf data from all four solutions and analyzes them alongside integrated POS and sales data. In an integrated deployment, AI Agent uses observed relationships and defined business rules to assess revenue contribution and loss drivers by campaign, store, and product, then recommends the next commercial and operational priorities.

Compare which media sites and time bands are most likely to contribute to store visits and revenue, then prioritize sales packages and campaign inventory.

Questions to settle before DOOH measurement

Do all sites need both Vision AI and Wi-Fi?

Vision AI and Wi-Fi serve different measurement needs. We select the method based on field of view, coverage, traffic speed, installation constraints, and the target metric.

How do you address Wi-Fi sample bias?

Wi-Fi signals are treated as a sample rather than a universal census. Site review documents the sampling assumptions, coverage, calibration, and comparison baseline.

Can these metrics support CPM and media pricing?

Circulation, reach, and exposure can inform a commercial measurement model. Before using them for CPM, the network defines its denominator, calibration, coverage, and reporting rules.

Start with one DOOH site and one reporting question

The demo maps the site conditions, measurement options, metric definitions, and reporting plan.