DOOH footfall attribution answers one question: did people who were near your screen ads visit your store more than people who were not? Nobody clicks a sidewalk panel or a TV in a bar. So instead of counting clicks, footfall attribution compares two groups of people and looks for a difference in visits.
That sounds simple. The details decide whether the number you get is useful or misleading. This guide walks through how it works, what the report means, and where it can go wrong. It is one part of measuring digital out of home advertising. The other parts, like impressions, QR scans, and geo-lift tests, are covered in how DOOH advertising is measured.
What "footfall" and "attribution" mean
Footfall is foot traffic. People walking into a place: a store, a restaurant, a clinic, a showroom.
Attribution is giving credit. When a sale or a visit happens, attribution tries to say which ad, if any, helped cause it.
Put together, footfall attribution gives an ad credit for store visits it helped cause. Not every visit. Only the extra ones that would not have happened without the ad.
How footfall attribution works, step by step
The method has five parts. Most measurement companies use some version of it.
- Draw a boundary around the screens. The system knows where each screen that played your ad is. It draws a small area around each one, the zone where a person could realistically see it.
- Find who was exposed. Using anonymized location data from phones that have location sharing turned on, it counts devices that were inside those zones while your ad was playing. That is the exposed group.
- Draw a boundary around your store. The same idea, around your location. This is often called a geofence: a virtual fence on a map. The basics of that are in what is geofencing advertising.
- Count visits in a time window. For a set period after exposure, such as 7, 14, or 30 days, it counts how many exposed devices later showed up inside your store's boundary. That period is the lookback window.
- Compare against a control group. It builds a second group of similar devices that were not near your screens, and counts how many of them visited too. The difference between the two visit rates is the lift.
The comparison in step 5 is the most important part. Without it, you are only counting people who walked past a screen and later walked into your store. Many of them were coming anyway.
Visits vs. lift: the number that matters
A footfall report usually shows two kinds of numbers. They mean very different things.
| Number | What it counts | What it tells you |
|---|---|---|
| Attributed visits | Exposed devices that later visited | How many visitors had a chance to see the ad. Not proof the ad caused anything. |
| Visit rate (exposed) | Visits divided by exposed devices | How often exposed people visited |
| Visit rate (control) | Visits divided by control devices | How often similar unexposed people visited |
| Lift | The gap between the two visit rates | How much more likely exposed people were to visit. This is the closest thing to the ad's real effect. |
| Incremental visits | Extra visits implied by the lift | Visits that likely would not have happened without the ad |
If a report only shows "attributed visits" with no control group, treat it with care. A screen right outside your door will "attribute" every regular customer who walks past it, whether the ad did anything or not.
Where footfall numbers can mislead
Footfall attribution is useful, but it is modeled. These are the limits to know.
The data is a sample
Only some phones share location, and only some of those show up in any given data set. The report scales that sample up to an estimate. A bigger campaign and a busier store give a more stable number. A small campaign at a single shop may not produce enough matched visits to say much.
The control group has to be fair
If the control group lives farther away, or shops at different times, the comparison is skewed. Good providers match the control group on things like home area and past visit habits. Ask how the control group was built.
Location is not exact
Phone location can drift by a few meters or more, especially indoors and between tall buildings. A device in the coffee shop next door can be counted as a visit to yours. Small stores in dense blocks feel this the most.
The window changes the answer
A long lookback window catches more visits, but also more visits the ad had nothing to do with. A short window is stricter. Neither is wrong. What matters is that you compare campaigns using the same window.
Close screens can look better than they are
Screens right next to your store will show lots of "visits," because the people near them are already near you. That is not bad. It just means you should read lift, not raw visits, before deciding a close screen is your best one.
Other ways to measure visits
Footfall attribution is one tool. It works best next to simpler ones you control yourself.
- QR codes and short links. Every scan is a person who took your ad to their phone. Clean and countable.
- A code or a line at the counter. "Mention the screen for a free coffee." Low tech, and very clear.
- Calls to a tracked number. A phone number used only on the screen ad.
- Before and after. Compare visits, sales, or calls in the weeks the ad ran against similar weeks when it did not.
- On and off areas. Run the ad in one area and hold it back in a similar one, then compare. This is a geo-lift test, the most careful version, covered in how DOOH advertising is measured.
None of these is perfect on its own. Two or three together give a picture you can trust.
How to set up a campaign so footfall can be measured
- Have a physical location people can visit. Footfall needs a place to count visits at.
- Pick an area that matches your trade area. The screens should be where your customers live, work, and walk. Formats that sit close to the door, like bars, gyms, and waiting rooms, are covered in in-venue TV advertising. The wider list is types of DOOH advertising.
- Run long enough. A few days rarely gives enough visits to compare. Plan for several weeks if you want a stable lift number.
- Keep the area steady while you measure. If you change the area every day, the exposed group keeps changing too.
- Add a direct response path. A QR code or a short link on the end card gives you a second, countable signal.
- Write down your normal. Know your usual weekly visits or sales before the campaign starts, so you have something to compare against.
Questions to ask about any footfall report
- Is there a control group, and how was it matched?
- What lookback window was used?
- How many visits were matched in total? Is it enough to mean something?
- Is the number "attributed visits" or "lift"?
- Where does the location data come from, and is it collected with consent?
- How is privacy handled? Is the data anonymized and grouped, not tied to a named person?
A good provider will answer all six plainly.
How this works on Glo
On Glo OOH, your ad plays on screens in the area you pick, from one block to a whole city. You can see the screens near you before you spend anything. Glo picks the screens based on time of day and what is bringing in calls and visits, and every screen shows up in your dashboard with its own spend, plays, and results. That makes it easy to compare one screen against another, and to pull budget from the ones that are not working.
Put a QR code or your address on the end card so you have a direct signal too. If you do not have a video yet, Glo Spark makes three free concepts.
Glo is self-serve advertising for every screen, screens first. Plans start from $17/day on Glo pricing, with no contract. You are charged only on days the ad runs, and you can pause anytime. Streaming TV at home is an add-on through Glo commercials. For the full cost picture across screens, read how much DOOH and CTV cost.
Questions people ask
What is footfall attribution in DOOH?
It is a way to measure whether people who were near your screen ads later visited your store more often than similar people who were not. It uses anonymized phone location data and compares an exposed group with a control group.
How accurate is footfall attribution?
It is an estimate, not an exact count. It depends on the size of the location data sample, how well the control group is matched, and how precise phone location is near your store. Larger campaigns and longer runs give more stable numbers.
What is the difference between attributed visits and lift?
Attributed visits are exposed people who later visited, whether or not the ad made a difference. Lift compares their visit rate with a control group's visit rate. Lift is the better measure of what the ad actually caused.
What is a lookback window?
It is the period after someone saw the ad during which a visit still counts, such as 7, 14, or 30 days. Longer windows catch more visits but also more that would have happened anyway. Use the same window when comparing campaigns.
Is footfall attribution private?
Reputable providers use location data from people who opted in to location sharing, remove names and personal details, and report only grouped totals. Ask any provider how the data is sourced and protected.
Can a small business use footfall attribution?
Yes, but a single location with a small budget may not produce enough matched visits for a confident lift number. Pair it with simple signals you control, like a QR code, a tracked phone number, or a code at the counter.