Using Mobile Location Data to Measure Billboard Foot Traffic

For businesses with physical locations, the question isn't "did people see my billboard?" but "did they come in?" Foot traffic attribution uses consented mobile location data to estimate how many people who passed your ad later visited your store. It's one of the most useful tools for proving out-of-home works, if you use it properly.

This guide is part of our guide to measuring billboard, TV and radio advertising.

How it works

1. Data collection: some mobile apps collect location data from users who have agreed to share it.
2. Exposure: the provider identifies devices that passed within viewing range of your billboard or transit ad during the campaign.
3. Visits: it identifies which of those devices later visited your locations.
4. Control group: it builds a comparable group of devices that didn't pass your ads.
5. Lift: it compares the visit rate of exposed devices with the control group. The difference is the estimated lift.

Example: if 2.0% of exposed devices visited your store versus 1.5% of the control group, the estimated visit lift is about 33%.

Why the control group matters

Without a control, you'd count visits that would have happened anyway, like people who pass your billboard on the way to your store because they're already customers. Any report without a control group comparison is showing exposure and visits, not impact.

Questions to ask providers

• Where does the data come from, and how is consent obtained?
• Is data aggregated and de-identified?
• How is the control group built? Does it match on geography and behaviour?
• How is "exposure" defined (distance, direction of travel, visibility)?
• How large is the sample in my area?
• How are store visits defined (minimum dwell time, location boundaries)?
• What's the confidence range around the lift estimate?

Privacy and compliance

Location data is sensitive. In Canada, organizations handling personal information must follow privacy law. PIPEDA applies federally in many cases, Quebec's Law 25 adds stricter requirements, and some provinces have their own laws. Use reputable providers, rely on aggregated and de-identified reporting, and never try to identify or contact individuals from location data. We'll cover the broader rules in privacy laws for marketers.

Making the most of foot traffic data

• Set a baseline of visits before the campaign.
• Run long enough to collect a meaningful sample. Short campaigns at small locations may not produce reliable numbers.
• Compare placements: which boards drove the most lift?
• Combine with other signals: promo code redemptions, "how did you hear about us?" answers and sales data. See QR codes, promo codes and vanity URLs.
• Translate visits into revenue using your conversion rate and average sale, then feed that into your billboard ROI calculation.

Limitations to keep in mind

• It's a sample-based estimate, not a head count.
• Accuracy is lower in dense areas with multi-storey buildings or small storefronts.
• It measures visits, not purchases.
• It can't capture people who don't share location data.

Used as one input among several, it's powerful. Used as the only truth, it can mislead.

Where it fits

Foot traffic attribution is most valuable for retail, restaurants, auto dealers, clinics, gyms and entertainment venues, anywhere a visit is a strong step toward a sale. It pairs naturally with good location choices (billboard advertising guide) and directional calls to action. If exposure is high and visits are flat, read why ads get attention but not sales.