Measure the store visits a campaign actually caused
Foot-traffic marketing usually can't tell whether a campaign changed behavior or just counted people who were already coming. A member-keyed visit event and a randomized holdout replace the guess with a measured lift.
Store-visit attribution is a guess
Store-visit attribution is usually inferred from aggregate footfall or self-reported scans — no member identity, no control group — so the lift a campaign 'drove' is a guess. Without a member-keyed visit event and a real baseline, foot-traffic marketing can't tell an operator whether a campaign changed behavior or just counted people who were coming anyway.
A deterministic visit event, measured against a holdout
A deterministic store visit — a QR check-in or in-store redeem by a known member — fires a member-keyed, deduplicated event. A randomized holdout then measures the incremental visits a campaign actually caused, rather than a before/after guess. Privacy is by construction: consent and GPC gated, only derived visit events stored, never raw coordinates.
How it works
The mechanics behind store & location (lbs).
Member-keyed, deduplicated visit events
A visit only registers when a known member takes a deterministic action in store — a QR check-in or an in-store redeem. The event is keyed to that member and deduplicated, so the signal is an identified visit, not an anonymous footfall estimate.
Randomized holdout for true incrementality
Eligible members are split into a treated group and a randomized control that receives no campaign. Incremental visits are computed as the difference between the two — lift is measured against a real baseline, never a before/after comparison or self-estimated footfall.
Privacy by construction
Measurement is consent-gated and honors Global Privacy Control signals; only derived visit events are stored, never raw location coordinates. The method is built to prove lift without building a location-tracking dataset.
Methodology, not a claimed result: store-visit lift is computed against a randomized control from member-keyed check-in and redeem events — never a before/after guess or self-estimated footfall — with consent and GPC gates and only derived events stored. See the LBS module for how it's delivered.
Frequently asked
How is a store visit actually detected?
By a deterministic action from a known member — a QR check-in or an in-store redeem — which fires a member-keyed, deduplicated event. There is no ambient location tracking; a visit is an identified, opted-in action, not an inferred proximity ping.
How do you know a campaign caused the visit?
A randomized holdout. Eligible members are split into treated and control groups, and incremental visits are the measured difference between them — so the number reflects true lift, not people who were coming anyway.
What about privacy and location data?
Measurement is consent and GPC gated, and only derived visit events are stored — never raw coordinates. The design proves incremental visits without retaining a location-tracking dataset.
See it on your own numbers
Book a walkthrough, or model the LTV:CAC upside with the ROI calculator.