The till tells you what left the store. It doesn't tell you when the queue formed, which aisles were skipped, or how many parked and never came in.
A grocery store runs on rhythm, the morning rush, the after-work peak, the Saturday wave. Footfall analytics shows that rhythm hour by hour and aisle by aisle, so checkouts, shelf stocking and campaign ends follow the customers instead of the schedule.
For the independent grocer and the supermarket chain. Anonymous, 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 checkouts open on the flow, not on the rota.
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Which aisles get walked, and which get skipped?
The customer's route through the store, dwell per department, fruit and veg, deli, dairy, non-food, shows 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 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.
A grocery store runs on rhythm
Nowhere in retail is timing as decisive as in food. The same store is empty at ten, queued at five and a different place again on Saturday morning. The till records every basket but nothing about the queue that formed before it, the aisle that was skipped, or the shoppers who parked, looked at the line through the window and drove on. Footfall analytics for grocery stores measures that rhythm anonymously, by the hour and by department, and turns it into checkout staffing, stocking hours, opening hours and campaign placement.
What you see, store by store
- The hourly curve, every weekday: when the store fills and empties, so checkouts, stocking and breaks follow the flow.
- Queue pressure at the checkouts: dwell at the checkout line by hour, including self-checkout against staffed lanes.
- The customer’s route: which departments are visited, in what order, and which are skipped.
- Campaign spots: dwell at each gondola end and promotional bay, so the best positions carry the offers that need them.
- Arrivals: flow on the car park or the street outside, and the share that comes in.
- Conversion and basket: visitors against transactions, brought in through an integration with your own checkout system.
- Store against store: the same measures across a chain, so stores are compared like for like, by hour and by department.
How staffing is built on the hourly curve, shift by shift, is on staff planning with footfall data.
What grocers have done with it
These are things grocers we measure have actually done, from independent single stores to chains:
- Opened checkouts on the queue curve instead of the schedule, and moved stocking to the quiet hours.
- Shortened a slow morning opening after the flow showed the store opened to an empty street, and in other stores extended evening or weekend hours after the flow outside showed neighbouring stores trading while theirs was closed.
- Re-ranked campaign spots on how long shoppers actually stopped at each one.
- Re-planned the store and measured before and after: dwell per department and total visit time.
- Compared self-checkout and staffed lanes on queue and dwell, and set the mix on the data.
- Measured the car park and the entrance together with the store, to see how many arrived and how many came in.
- Followed a new competitor nearby week by week, saw the dip, and saw what won the traffic back.
- Measured convenience stores at transport hubs and forecourts, where visits are short and the peaks follow the commute; the forecourt side of that is on petrol stations and convenience retail.
Getting started in a grocery store
Most grocery stores start on the Wi-Fi already in the store. Measurement runs on the access points you have, with an entrance sensor added where exact in/out counts matter, and staff are filtered out of the counts. The first month gives you the hourly curve, queue pressure and department flow for that store; a chain adds stores on the same setup and compares them like for like, in the dashboard or straight into your own BI through the API. The method is anonymous by design and is the only footfall method in Europe approved by a data protection authority, so nothing about it needs to be explained to a customer or a works council.
How Wi-Fi people counting works → People counter for stores: see what happens before the till →
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
We already have checkout data. Why measure footfall?
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 fills in everything before the till, and the sales data is brought in through an integration with your own system so the two sit side by side.
Does this work for a single independent store?
Yes. Many of the grocers we measure are independent owners running one store. They get the same hourly curve, queue picture and department flow as a chain, and use it for checkout staffing, opening hours and campaign placement.
Can you measure 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 unfolds from there.
Do we need cameras above every aisle?
No. The core measurement runs on the store's Wi-Fi, anonymously, and it is the only footfall method in Europe approved by a data protection authority. Exact entrance counts come from a small 3D sensor or LiDAR unit above the doors where you want them, and staff are filtered out of the counts.
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. Several chains run the same measurement across their stores and compare them like for like.