A campaign produces activity that is easy to count, such as impressions, shares and attendance, and outcomes that are hard to establish, such as understanding, trust or safer practice. Campaign evidence is the discipline of measuring each level honestly and claiming no more than the design supports. This page sets out how reach, learning and outcomes are measured, why attribution is difficult, how metrics distort practice, and which evidence funders, agencies and evaluators can rely on.
GCRI · Established · service level R0
Campaign evaluation is the measurement of what a campaign reached, what people understood and what they did differently, claiming no more than the design supports. Reach and impressions are easy to count; understanding and safer practice are hard to establish, and attributing them to a campaign needs a comparison group.
Urban demand centres and the hubs that anchor digital and data infrastructure, shown for Indonesia as an example geography for this subject.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Campaign evidence · Wave 2 · Campaign area North
| Prepare a water reserve | A | 61 | Keep |
| Know your warning levels | B | 57 | Revise |
| Check on neighbours | A | 74 | Keep |
Learning metrics and demonstrable outcomes. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Exposure, attention, comprehension, intention and action are separate levels, and evidence at one does not establish the next. A logic model states which level each measure speaks to, so that impressions are not reported as learning or intentions as behaviour.
Change during a campaign coincides with news, prices, seasons and other programmes. Without a comparison group, a credible counterfactual or a pre-registered design, a before-and-after difference cannot be credited to the campaign, however large it appears.
When a measure becomes a target it stops measuring well. Campaigns optimised for engagement reward provocative content, platforms change how they count views, and easy metrics crowd out harder evidence. The choice of metric shapes what the campaign becomes.
Effects found in one country, medium or period often do not replicate elsewhere. Positive evaluations are published more often than null ones, so reviews of the literature can overstate what campaigns achieve. Context has to travel with every result.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Deduplicated reach | The number of distinct people a campaign reached, counting each person once across channels. |
| Pre-registration | Publishing an evaluation's design and analysis plan before results are known. |
| Null result | A finding of no detectable effect, which still informs future campaigns when published. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Deduplicated reach | persons or accounts reached | per campaign | Platform and site analytics | ESTIMATED |
| Message recall | percent of a sampled audience recalling the message | per survey wave | Post-campaign survey | REPORTED |
| Comprehension gain | difference in test scores before and after | per cohort | Pre and post assessment | OBSERVED |
| Intention to act | mean score on a validated scale | per survey wave | Survey instrument | REPORTED |
| Observed protective action | proportion of a sample observed taking the action | per study | Observation or administrative records | OBSERVED |
| Effect estimate | standardised difference with confidence interval | per evaluation | Controlled or quasi-experimental evaluation | ESTIMATED |
| Pre-registration status | registered or not, with registry and date | per evaluation | Trial and study registries | DECLARED |
| Cost per person reached | currency per person | per campaign | Budget and reach records | ESTIMATED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| 3ie Development Evidence Portal | Impact evaluations and systematic reviews of development interventions, including communication | Free to read |
| Campbell Collaboration systematic reviews | Reviews of social interventions with stated methods and certainty of evidence | Open access, CC BY |
| AEA RCT Registry | Pre-registered randomised trials in the social sciences | Free to read; metadata openly available |
| OSF Registries | Pre-registered study designs and analysis plans | Free to read; metadata CC0 |
| Meta Content Library and API | Public content and engagement data from Facebook and Instagram, the successor to CrowdTangle | Access by application for qualified researchers |
| OECD DAC Evaluation Resource Centre | Evaluation reports from development agencies | Free to read |
| Platform transparency reports | Reach, moderation and enforcement data published by platforms, including under the EU Digital Services Act | Free to read; reuse per platform terms |
Nexus Campaigns prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Funders and foundations | Whether to continue, scale or stop funding a campaign | Outcome records by level; effect estimates with intervals; quality of the evaluation design |
| Public health and communication agencies | Which channels and formats to use in the next campaign | Comprehension and recall evidence; cost per person reached; context of each result |
| National audit offices and evaluation units | Whether public spending on campaigns met its stated aims | Logic models; pre-registration records; observed action measures |
| Platform research and transparency teams | Which data to make available to independent researchers | Documented researcher access needs; gaps in published transparency data |
Knowledge, intended action, trusted sources or behaviour, chosen to match the campaign's aim.
The baseline and, where feasible, a comparison group, so change can be attributed with care.
Whether effects persist after the campaign or fade within weeks.
Which groups the campaign did not reach and why.
Reach is easy to count and weakly linked to effect. Impressions and views say little about understanding. Evaluation research distinguishes outputs (what was delivered), outcomes (what changed for people) and impact (longer-term change attributable to the campaign).
Attribution is the hard part. Other messages, events and policies move the same measures. Without a baseline and some form of comparison, a campaign may claim credit for change it did not cause or miss effects it did have.
Publication bias distorts learning. If only successes are reported, the field learns little. Recording null and negative results is as valuable as recording successes, and it protects the next campaign team from repeating an approach that has already failed elsewhere.
Measures also shape behaviour. A team rewarded for reach will optimize for reach. Agreeing measures of understanding or action before launch keeps attention on the public purpose.
| Method | What it shows | Its limit |
|---|---|---|
| Baseline and follow-up surveys | Change in knowledge or intentions | Self-report and attrition |
| Comparison designs | Effect relative to a group not reached | Often hard to arrange ethically or practically |
| Administrative data | Behaviour such as service uptake | Many confounding influences |
| Qualitative follow-up | Why the campaign worked or did not | Not generalizable on its own |
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.