Measurement is the final piece of the offline to online (O2O) loop.
Sophisticated footfall tracking uses GPS, Wi‑Fi, and other signals to demonstrate that your online ads are converting to real people walking into your stores.
This provides the missing link. You have struggled to show offline impact but now you can. This is real ROI.
And it starts to answer the oldest problem in marketing. John Wanamaker is supposed to have said, “I know half my advertising works, I just don’t know which half.” You are finally able to know. You can connect that click on a Tuesday with a store visit on Saturday.
It also changes your entire budget conversation. You stop speculating and start investing in what you know is working.
You can read the full O2O explanation in our Local Online Marketing for Retailers guide.
How Store Visits Works
Google has a very large data set to be able to provide store visit tracking. It does not track everyone. Instead, it has a panel of users who have opted to allow “Location History” on their Google accounts.
The signals the system uses include:
- GPS signals: these satellite data points indicate they are near your store.
- Wi‑Fi signals: your store’s Wi‑Fi triangulates that they are in the building and not in the car park.
- Maps geometry: Google knows the coordinates and outline of your building.
- Query data: What the user searched before visiting.
Google’s systems then crunch all those signals and filter out obvious noise. It will remove people who visit but are not your customers (employees, for example). It can ignore people who pass by (very low dwell time).
Then it can extrapolate from the panel to estimate the true trends across the wider population.
Privacy and Aggregation
Privacy is a non-negotiable baseline. You never get a list of people who visited. You do not get names, emails, or device details. It’s all aggregated reporting.
Google will only report store visit data if there is sufficient volume to be able to maintain anonymity. That’s why small stores or low-traffic accounts can sometimes struggle to qualify. It is not a problem with your account. It’s the privacy control kicking in.
Assigning Value to Visits
Once you can track visits, the next step is to assign a value to each visit.
Leaving the value at 1 means the bidding system will treat each visit as if it’s worth £1. Over time, it will desist from trying to drive store visits when you are optimising for omni-channel bidding, because the value is too little and online sales will always drive more.
The easiest way to define a visit value is to use a simple equation:
Average Order Value (AOV) x In‑Store Conversion Rate = Visit Value
Example: Let’s say your average spend per customer is £50 when they make a purchase. You know that 20% of people who enter your store make a purchase. £50 x 0.20 = £10.
The value of a store visit for you is £10. Enter this into Google Ads and every recorded visit has a value. You can measure your return and make budget decisions with confidence.
Dynamic Values and POS Integration
A static visit value is a good starting point. The next level is a dynamic value.
By integrating with your Point of Sale (POS) system, you can match the click with a real offline receipt. This typically works by sending the Google Click ID (GCLID) and securely posting the final transaction value back to Google Ads.
A simplified flow looks like this:
- A user clicks your ad.
- Google assigns a GCLID.
- The user visits your store and buys a sofa for £850.
- Your POS system sends the offline purchase value back to Google Ads.
By closing the loop, you have removed any guesswork from the equation. You no longer have to estimate a visit value. You can see that a specific ad drove a specific offline sale.
It does require technical work and clean data. If your Merchant Centre setup and feeds are messy, then measurement is going to be difficult.
(See our Merchant Centre & Product Feeds guide)
Enhanced Conversions for Leads
If full POS integration is not an option yet, there is a useful middle ground: Enhanced Conversions for Leads.
This uses information provided by your customers, such as an email address, and uses it in a privacy-safe way. If a customer provides an email for a receipt or a loyalty programme, you can hash that email and send it to Google. If Google finds that that person has clicked an ad, it can safely attribute a conversion when there is a match.
This is not 100% attribution, but when you can’t match every transaction it can help improve accuracy.
Using the Data to Optimise
Once you have footfall tracking, that data becomes the lever to steer with. The data will often show you trends that are counter-intuitive.
For example:
- Mobile ads can have a higher CPC but a lower Cost Per Visit. Mobile users are ready to go.
- Weekends may generate more visits than weekdays. Shift budget into those stronger hours.
- Generic keywords (e.g., “furniture store”) may generate more new customers than brand terms. Prioritise prospecting.
Identify these insights and tweak your LIA strategy accordingly.
Check out our Local Inventory Ads strategy.
Case Study: Measure Up
We worked with a retailer who was only measuring online sales. They thought their local campaigns were a loss (because the online ROAS was 1.5x) and wanted to switch them off.
Once we turned on tracking we were able to complete the picture. For every £1 in online sales, the ads also drove £8 in offline sales. The true ROAS was 9.5x.
The campaign was not underperforming. It was their most profitable channel by a long way. The client tripled the budget instead of reducing it.
Read the full analysis of this 215% Increase in Store Visits.
Conclusion
Footfall tracking is the light at the end of the tunnel. It shows the value of your work and prevents well-performing campaigns being turned off for the wrong reasons.
You have a physical advantage. You have a store. Measure the footfall to that store. If you do not measure it, you cannot manage it. You cannot improve it.
Are you ready to calculate your true ROI?
We can audit your tracking setup and assess your Visit Value.