TV and offline attribution
TV, radio, and print have no click, so their attribution is built from indirect evidence: correlating exact spot airtimes with spikes in site traffic and search, dedicated vanity URLs and promo codes, self-reported surveys, and — most rigorously — geo or matched-market experiments that compare regions with and without the buy. Each method trades precision for the reach these channels uniquely deliver.
Indirect response signals
The classic offline read is spike analysis: overlay minute-by-minute site visits and branded searches on the exact times spots aired. A repeatable bump in the minutes after airtime is evidence the spot drove response.
Vanity URLs and promo codes add deterministic credit for the subset who act on them, and surveys recover those who convert later via search or direct.
Experiments for causal proof
Spike correlation can be confounded by other activity, so the rigorous approach is a geo or matched-market experiment: air the campaign in some regions and hold out comparable regions, then compare outcomes. The difference, net of baseline, is the causal effect.
This is the same incrementality logic used online, applied to markets — which is why TV measurement increasingly borrows matched-market and difference-in-differences methods.
- Spike analysis: align traffic/search to spot airtimes
- Vanity URLs and codes capture the subset who act
- Geo / matched-market tests give the causal read
How it appears in analytics and logs
A traffic or search spike aligned to spot airtimes is directional evidence of response; a geo or matched-market test is the stronger, causal read.
Diagnostic use case
Measure a TV or radio campaign by combining minute-level traffic spike analysis with vanity URLs, codes, and a geo holdout.
What WebmasterID can help detect
WebmasterID's first-party, timestamped traffic lets you align direct and search spikes to known spot airtimes without third-party tracking.
Common mistakes
- Reading a single post-airing spike as proof without a control.
- Crediting only coded response and ignoring spillover demand.
- Confounding airtime spikes with concurrent campaigns.
Privacy and accuracy notes
Spike analysis uses aggregated traffic timing; experiments compare regions, not individuals. Educational, not legal advice on broadcast measurement.
Related pages
- Matched market testing
Matched market testing measures causal impact by pairing geographic markets with similar historical behavior, running a campaign in the test market while holding out its matched control, and attributing the post-period difference to the campaign. It is the practical workhorse for offline and channel-level incrementality where user-level randomization is impossible — closely related to geo experiments and the synthetic control method.
- Vanity URL attribution
A vanity URL is a short, memorable address (like brand.com/show) that a person can hear and type, used in podcasts, radio, TV, and print where no link is clickable. When typed, it redirects to a landing page carrying campaign parameters, so an otherwise untrackable offline exposure becomes an attributable visit. It trades reach for measurability: only listeners who remember and type it are captured.
- Geo experiments for measurement
A geo experiment divides geographic regions into a treatment group (which sees a media change) and a control group (which does not), then compares outcomes between them. Because assignment is at the region level rather than the user level, geo experiments measure incremental effect without needing cookies, device IDs, or per-person attribution — making them a privacy-resilient complement to touch-based models.
- Website observability
Timestamped first-party traffic for spike analysis.
Sources and verification notes
- Google — Geo experiments methodology (research paper)Geo-based causal measurement applicable to offline media.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.