The till shows what left the store, but not when the queue formed, which aisles were skipped, or how many parked and never came in.
Footfall analytics shows, hour by hour and department by department, when the checkout queue forms, which departments customers skip and, with sensors, how long they stop at each campaign end. Checkouts, stocking and campaign spots can then follow the customers.
For the independent grocer and the supermarket chain. Anonymous and approved by a data protection authority.
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Three questions every grocer asks
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When does the checkout queue actually form?
Dwell at the checkout line, by the hour and by weekday, shows exactly when queues build and when lanes stand empty, so you can open checkouts on the flow instead of the rota.
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Which aisles get walked, and which get skipped?
The customer's route through the store and dwell per department (fruit and veg, deli, dairy, non-food) show where the visit slows down and which departments most visits never reach.
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Does the campaign end at the aisle head do anything?
Dwell at each campaign spot, measured with sensors, tells you which gondola ends stop people and which are passed at walking pace, so the best positions go to the offers that need them.
On this page
Footfall analytics for grocery stores shows when the checkout queue builds, which departments customers visit and, with sensors, how long they stop at campaign ends. It runs on the store’s existing Wi-Fi, with a 3D sensor at the entrance where exact counts matter. Bumbee Labs is the company behind the only footfall method in Europe approved by a data protection authority.
The short version
- Footfall analytics for grocery stores shows, hour by hour, when the checkout queue forms, which departments customers skip and, with sensors, how long they stop at each campaign end.
- Measurement uses the store’s existing Wi-Fi. A 3D sensor at the entrance adds exact counts, and no cameras above the aisles are needed.
- The same hourly curve guides checkout staffing, stocking hours and opening hours, whether the store is independent or part of a chain.
- Checkout data comes in through an integration with your own system and sits beside the footfall figures.
What can footfall analytics for grocery stores tell you?
At what hour does the checkout queue build, and are enough lanes open by then?
Dwell at the checkout line, read by the hour and the weekday, shows when the queue in a grocery store starts to build and when lanes stand empty. The store can then open checkouts on that curve and plan the staff behind them around it. The dwell figures come from the store’s own Wi-Fi people counting.
Self-checkout or staffed checkout: what is the right mix for our store?
Queue and dwell at the self-checkout and at the staffed lanes can be read side by side, hour by hour. A grocery store then sees which kind of lane builds the queue and when, and sets the mix of the two on that data. Where exact counts matter, 3D sensor counting adds them.
When is the store quiet enough to fill the shelves?
An hourly visitor count for every weekday puts the grocery store’s whole week in one picture: when the aisles are quiet and when they are full. Shelf stocking can then move to the quiet hours, away from the peaks, and breaks can follow the same curve.
How staffing is built on that curve, shift by shift, is on staff planning with footfall data.
Which departments do customers skip on their way round the store?
The customer’s route through a grocery store shows which departments are visited, in what order, and which ones most visits never reach. Dwell time per department, whether fruit and veg, deli, dairy or non-food, shows where the visit slows down. Both can be read hour by hour and, with sensors, aisle by aisle, like the checkout figures.
Do the offers at the aisle ends make customers stop?
Dwell at each gondola end and promotional bay, measured with sensors, shows which campaign spots stop shoppers and which are walked straight past. The best positions can then go to the offers that need them. Seeing whether a stop ends in a sale needs the till data, which a grocery store brings in through a POS integration.
A new store has opened nearby: is it taking our customers?
Weekly visit counts from before and after a competitor opens nearby show the dip and what won the traffic back. Independent grocers who bought the measurement for their own store have followed it this way, week by week. The weeks only compare fairly when both periods are counted the same way, which is what a footfall benchmark depends on.
Are our opening hours right for the street outside, morning, evening and weekend?
Compare the flow on the street outside with the opening hours: early morning, evening and weekend. Grocers we measure have shortened a slow morning when the store opened to an empty street, and extended evening or weekend hours when neighbours traded and they did not. Wi-Fi counts the street, and LiDAR people counting above the door gives exact entries.
After the rebuild, do customers go round the store better?
Dwell per department and total visit time, measured before the rebuild and again after it, show whether customers now go round the grocery store better. A retail heatmap for each period shows the route they take through the departments, so the old layout and the new one can be set side by side.
What else can supermarket footfall data tell a grocer?
- How many park and drive away without coming in?Flow in the car park and flow into the store, counted together, show how many arrive and what share comes in.
- I run my own grocery store and bought the measurement myself: do I get what a chain gets?Yes, an independent owner gets the same hourly curve, queue picture and department flow as a chain.
- What does the commuter rush look like in a convenience store?At a transport hub or a forecourt the visits are short and the peaks follow the commute. The forecourt side is covered on petrol stations and convenience retail.
- How busy is the unstaffed store?Entries and exits counted with a 3D sensor at the door show how many people the store holds, hour by hour.
- How far do our customers travel to reach us?Before a new store opens, the flow outside a planned location, or a catchment area taken from mobile network data, supports the choice of where to open.
- Where do the new hours go when margins are thin?The hourly curve for each store shows when customers arrive, which is where the few staff hours can be placed.
- Do drivers charge the car and then shop?Counting the car park and the store entrance together shows how many arrive and how many come in, and dwell shows how long they stay.
- How busy is the store when the online order pickers are in the aisles?Visits and occupancy show how full the store is at each hour of the day.
- Payday weekend and the end of the month: what does the month look like?Visits counted per day give the month’s rhythm as a daily curve for the store, on top of the weekly one.
- How do the other stores in the chain compare?A chain can compare its stores on the same measures, hour by hour. Retail chains have their own page on it.
How does a grocery store get started with footfall measurement?
Most supermarkets and grocers begin on their existing Wi-Fi, where the access points already in the building do the measuring. An entrance sensor goes in where exact in and out counts matter, and staff are filtered out of the counts. After the first month the store has its hourly curve, queue pressure and department flow to work from. A chain can add stores on the same setup and read the data in the dashboard or in its own BI through the API. If you are weighing a plain counter against full analytics, the guide People counter vs analytics compares the two.
Curious what this looks like for your venue?
What grocers do with the data
Grocers we measure have opened checkouts on the hourly queue curve instead of the schedule, moved shelf stocking to the quiet hours, and re-ranked their campaign spots on how long shoppers actually stop at them. Independent grocers who bought the measurement for their own store have used it to shorten a slow morning opening and to follow, week by week, what a new competitor nearby did to their traffic and what won it back.
At Ray our motto is customer success, and we are excited about our partnership with Bumbee Labs. Complimenting the seamless Wireless provided by Ray, our customers will now be able to leverage the deep analytics provided by Bumbee Labs and take informed business decisions to aid their growth.
Frequently asked questions
Our grocery store already has checkout data. Why measure footfall as well?
Checkout data shows who bought and when they paid. It doesn't show when the queue formed before that, how long the visit was, which departments were skipped, or how many people parked or walked past and never came in. Footfall analytics covers what happens before the till. Sales data comes in through an integration with your own system, so the two sit side by side.
How does footfall analytics show which campaign ends work in a grocery store?
Sensors at each gondola end and promotional bay measure how long shoppers stop there. The grocery store then sees which campaign spots hold people and which they pass at walking pace, and can keep the strongest positions for the offers that need them. Whether a stop turns into a sale needs the till data alongside, through a POS integration.
Can footfall analytics for a grocery store cover the car park and the entrance as well as the store?
Yes. Outdoor flow on the car park or the street and indoor flow in the store are measured together, so you see how many arrive, how many come in, and how the visit goes from there.
Can footfall analytics show what a new competitor nearby does to our grocery store's traffic?
Yes. Visits to the grocery store are counted week by week, so the weeks before the new store opened can be set against the weeks after. Independent grocers we measure have used this to see the dip in traffic and then what won it back. The comparison holds only when both periods are counted the same way.
Where this fits
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Industries and segments
Data protection:GDPR-compliant footfall analyticsThe IMY decisionGDPR CCTVEU AI Act