Measurement
Part of Out of home advertising measurement works when the method matches the decision
Build an out of home advertising reporting dashboard without the vanity metrics
How to build an out of home advertising reporting dashboard: define the decision, choose count and reach metrics, set a rubric and keep evidence traceable.
What to take away
- Start from the decision the buyer will make at the next review. A dashboard for a Manchester bus shelter campaign should answer one question: renew, shift budget, or stop.
- Report counts and reach together. Poster sites deliver impressions, but a retail client cares about footfall near the store, so pair OTS figures with a location measure.
- Keep every number traceable to a source, a date and an owner. Untraceable figures do not belong on the dashboard.
- Score each metric against a written rubric before launch, so nobody argues about weighting after results land.
Decide the decision before the chart
A dashboard fails when it is built backwards from available data. The useful order is decision, metric, source, then visual.
Ask the buyer what action follows the report. For a six-sheet England roadside campaign, the likely actions are extend, reweight sites, or reallocate to another format. Each action needs a different number.
Write the decision at the top of the dashboard file. It keeps the build honest when someone asks for one more chart. The wider method for linking evidence to choices is set out in out of home advertising measurement and reporting.
Choose metrics that survive scrutiny
Counts are the base layer: plays, impressions, and site days delivered against site days booked. Reach and frequency sit above them, usually modelled rather than observed.
Location measures sit alongside. For a grocery client, a drive-time or footfall band around each site often matters more than gross impressions.
If the campaign uses dayparting, mirror the planning schedule logic. Google Ads Help explains the principles of ad scheduling, which transfers to time-targeted OOH buys.
Build the dashboard in four steps
- List the decisions from the kick-off meeting and CAP the list at five.
- Map each decision to one primary metric and no more than two supporting metrics.
- Record the source, refresh date and owner for every field in a data dictionary.
- Draft the layout on paper, then build only what the paper version needs.
The data dictionary is the part teams skip. It is also the part that saves a review meeting when a number is challenged.
Where the data comes from
Route counts, play logs and site schedules come from the media owner. Audience models come from the measurement supplier. Post-campaign research comes from the fieldwork agency.
Label modelled figures as modelled. A modelled reach figure is an estimate, not a census, and the dashboard should say so next to the number.
How to keep it auditable
Version every refresh. Note who changed what and when. If a client asks why reach moved between weeks, the answer should be in the log, not in someone's memory.
Score results against a rubric
A rubric turns a pile of metrics into a defensible verdict. Agree it before launch and keep it short.
| Criterion | Weight | What good looks like |
|---|---|---|
| Delivery against booked site days | 25% | Within 5% of plan |
| Reach against target audience | 25% | Meets or beats the agreed threshold |
| Location fit | 20% | Sites sit inside the agreed catchment bands |
| Cost per thousand delivered | 15% | At or below the planned rate |
| Data completeness | 15% | No unexplained gaps in the refresh log |
Weights are illustrative. A brand campaign may shift weight towards reach; a retail campaign may shift it towards location fit. Set thresholds from out of home advertising benchmark research rather than a hunch, because a rubric with invented targets collapses under challenge.
Score each criterion out of five, multiply by the weight, and total. A score below the threshold triggers a review, not automatic cancellation.
Handle privacy and complaints properly
Any dashboard that ingests movement or location data needs a lawful basis and a data protection impact assessment. The ICO's guidance on designing products that protect privacy sets out the privacy by design principles that apply to digital OOH products.
Complaints about a creative or a site sometimes end in an ASA ruling. If a party disputes the outcome, the independent review process for ASA decisions explains how that challenge works.
Keep complaint records and ruling references in the dashboard archive. They are evidence for the next buy.
Common questions
How many metrics should a dashboard show?
Aim for five to seven headline metrics tied to decisions. More than that and the review becomes a reading exercise.
Should modelled reach sit next to observed counts?
Yes, but label them differently. Observed counts and modelled estimates carry different confidence, so unlabelled mixing misleads the reader.
How often should the dashboard refresh?
Match the refresh to the buying cycle. Weekly suits short flights; monthly suits long-format tenancies. A refresh nobody reads is wasted effort.
What belongs in the archive?
Source files, the data dictionary, the rubric and any complaint or ruling correspondence. An archive that cannot be reconstructed six months later is not an archive.
