Measurement
Part of Out of home advertising measurement works when the method matches the decision
Out of home advertising benchmark research explained without jargon
How to compare out of home advertising benchmark research with your own campaign data, set tolerances early and report results without overclaiming.
What to take away
Out of home advertising benchmark research means comparing your campaign's measured results against published or peer norms, then judging the buy against that reference point.
- A benchmark is only useful when the unit matches: impressions, reach, cost per thousand, or footfall, not a mix of all four.
- Record the source and date of every external figure you quote, because norms drift with site supply and season.
- Agree tolerances before you open the results, so a small miss does not trigger a rewrite of the plan.
- Publish the comparison next to your own figures, not instead of them, so buyers can see both.
Match the unit before you match the number
A benchmark compares like with like. If your buy is priced on impressions, compare cost per thousand impressions, not cost per site. Mixing units is the fastest route to a flattering but useless conclusion.
Once the unit is right, the harder question is which metric the decision needs. Out of home advertising measurement and reporting sets out how reach, frequency and delivery measures fit different briefs.
Place-based schedules often cross several local authority areas. Geographies rarely line up neatly between media. The RAJAR mapping data linking listening to geographies is useful here, because it lets you compare a place-based buy with a radio schedule covering the same travel-to-work area.
Season and supply matter too. December inventory in a city centre does not behave like a quiet February. Note the period each published figure covers, and label your own data with the same care.
Where the numbers come from
Most teams work from three sources: their own campaign history, platform delivery data and published norms.
Internal history is the strongest, because the unit and the audience are already defined. It is also easy to misread, since a small run of past buys can look like a pattern.
Platform data gives delivery and estimated audience figures. Treat those estimates as estimates, and check how the platform defines a completed impression before you set a target.
Keep personal data out of a benchmark pack unless you have a lawful basis. The ICO guidance on direct marketing and privacy and electronic communications sets out the consent and soft opt-in rules for following up a campaign with named contacts.
Check the rules before you repeat a result in a sales deck. The ASA's AdviceOnline library gives marketers detailed guidance, including on out of home advertising, so a claim does not become a compliance problem.
Set tolerances before you open the numbers
Decide in advance how far a result can sit from the benchmark before it counts as a miss. For example, a team buying £400 a month of roadside space might accept anything within 15 per cent of its own ten-week average.
Tolerances stop small fluctuations from driving big decisions. They also make the comparison easier to explain to finance, because the threshold is agreed before anyone sees the result.
A decision table for three common situations
| Situation | Choose | Avoid |
|---|---|---|
| First benchmark, no internal history | A published norm for the same format, labelled with its source and date | A supplier headline reach figure with no definition |
| Small campaign, fewer than fifty sites | Simple reach and cost per thousand, reviewed monthly | Regression or modelled attribution |
| Client wants a media-neutral comparison | Matched geographies and matched weeks | A two-week burst compared with a quarterly average |
Treat the table as a starting point, not a rule.
Reporting the comparison
A benchmark is only as good as the report it lands in. A dashboard that shows the benchmark band beside actual delivery saves a meeting.
Teams that track delivery, the benchmark band and variance spot problems early, so an out of home advertising reporting dashboard is worth setting up before the first campaign closes.
Common questions
Why do benchmarks differ between sources?
Sources define impressions, viewability and audience differently, and they cover different periods. A benchmark from a quiet quarter will not match one drawn from a peak season, so always name the period.
How often should a benchmark be refreshed?
Refresh internal history each quarter and re-check any published norm when you reuse it. Site supply and pricing move, and an old figure can quietly mislead a new plan.
Can a benchmark replace a control?
No. A benchmark shows what is typical, not what your buy caused. Use a control or a holdout when you need to claim a causal effect.
