Trade customers arrive at seven in the morning and families on Saturday, on the same rota. A door counter does not see the yard.
A builders' merchant serves trade customers and families on one site, indoors and out. Footfall analytics gives each group its own hourly curve and counts the yard and the drive-in beside the store, so opening hours, staffing and layout can follow the customers you have. No one is identified.
For the builders' merchant, the DIY warehouse and the paint shop. Anonymous and approved by a data protection authority.
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Questions DIY and hardware retailers ask
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When is it trade, and when is it consumers?
The store gets two hourly curves, one for the early trade rush and one for the weekend consumer wave, so opening hours and staffing can be set per customer type.
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What happens in the yard and the drive-in?
Outdoor flow on the yard and drive-in is measured separately from the store. You can then judge the site as a whole and staff the collection point when queues actually build.
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Which aisles does nobody walk down?
Dwell by department (plumbing, electrical, garden, paint) shows which corners of a large floor are dead and which aisles carry the visit, so the layout can be re-planned on evidence.
On this page
Footfall analytics for DIY and hardware stores shows trade and private customers by the hour, yard and drive-in lane flow, queues at collection and cutting, and dwell by department. It counts on the site’s Wi-Fi, with an optional entrance sensor for exact figures. Bumbee Labs is the company behind the only footfall method in Europe approved by a data protection authority.
The short version
- Footfall analytics for DIY and hardware stores reads trade and private customers as two hourly curves, so you can set opening hours and staffing per customer type.
- The yard, the drive-in and the car park are measured beside the store. So are queues at the collection desk and the cutting service, and dwell by department.
- Measurement starts on the Wi-Fi already on site, with an optional entrance sensor for exact counts. Nothing identifies an individual.
- The visitor curve shows the spring peak and the autumn decline week by week. A campaign leaflet is judged on visits in the week after it compared with the weeks before.
What can footfall analytics tell a builders’ merchant or a DIY store?
Do trade customers and families need different opening hours and rotas?
Yes, because they come at different times. A single door counter blends them into one curve that fits neither. Footfall analytics reads the two separately, and opening hours have been set per customer type once the curves showed trade arriving before opening and families still there after closing. Staff planning with footfall data turns the curves into a rota.
How many of the customers on the yard and in the drive-in come inside?
Arrivals on the yard, in the drive-in and in the car park are counted beside the store’s own entries. You see what share of the people who arrive come inside and where on the site a queue forms. The drive-in can be staffed on its own flow. The yard is covered by the same Wi-Fi people counting as the store.
How do we staff garden and outdoors for the spring peak and the autumn decline?
Follow the visitor curve week by week. It shows the spring peak building and the autumn decline setting in, and merchants we measure have raised garden and outdoor staffing as the customers arrived. The footfall calendar of the retail year sets that season beside the rest of the year.
Are the collection desk and the cutting service staffed when the queues form?
They can be, once each desk has its own hourly curve. Footfall analytics reads dwell at the collection desk, the cutting service and customer service by the hour, so you see when a queue builds at each one and can staff it from measured queue times. The time a customer spends at a desk is the dwell time.
Which corners of our big floor are dead: plumbing, electrical, paint or garden?
The ones where time spent stays low. Dwell per department, from plumbing and electrical to timber, paint and garden, shows where a large floor is dead and which aisles the visits run through. Merchants have re-planned dead corners once the numbers showed where the visit stalled, and retail heatmaps show the same picture on the floor plan.
What share of our customers are trade, and what share are private?
The mix of trade and private customers can be estimated on site from the vehicles that arrive, and the yard and the store planned around it. No individual is identified, and the figures are aggregate flow. At the entrance, LiDAR people counting adds exact counts where they are wanted.
Did the leaflet we sent out bring more people to the store?
Put the visitor count for the week after the leaflet beside the weeks before it. If more people came, the leaflet worked at the door. Dwell in the department it advertised shows whether they went there. A merchant can then judge a leaflet on visits as well as on sales.
What else do builders’ merchants, DIY warehouses and garden centres ask of their footfall data?
- Is a simple counter enough for a paint shop with one entrance?One such shop has set its rota on an entrance count and the hourly curve, and 3D sensor counting can give that count.
- Trade customers order in the app and come to collect: does the collection desk keep up?The count reads dwell at the desk by the hour, so you see when the queue builds there.
- Is the loading zone or the car park jammed at the trade peak?Flow on the yard and in the car park is measured beside the store by the hour, so you see when they fill.
- Which of our warehouses gets it right?A chain measures every site the same way, so one site can be set against another.
- We are planning a new warehouse: how large is its catchment area?Mobile network data gives a catchment area for a planned site before it opens.
- First snow: does the rush for shovels and grit show up in the visit count?A weather peak appears in the hourly curve, and the rota can be read against it.
- A retail park draws a crowd: how many of them come to us?Footfall analytics reads the visits to your store, and setting them beside the flow around it shows the share that comes in.
- Mother’s Day, Valentine’s Day, Christmas: how many come in each hour?A florist or a garden centre reads the peak days as an hourly visit count and sees how the rush spreads across the opening day.
- A garden centre in April: how busy are the outdoor area and the shop together?Both are measured together, week by week through the spring peak.
- A small florist with one or two staff: is an entrance count enough?An entrance count and the hourly curve show when the shop is busy and when it is quiet.
How does a builders’ merchant or DIY store get started?
A site can start on the Wi-Fi already in the building, where an access point or two covers the yard outdoors. An entrance sensor adds exact in and out counts where they matter, and staff and delivery drivers are left out of the counts. After the first month you have the two hourly curves along with yard flow and dwell by department. The results appear in the dashboard or go through the API into your own BI.
Curious what this looks like for your venue?
What builders' merchants and DIY chains do with the data
Builders' merchants we measure have set trade and consumer opening hours on two separate hourly curves and staffed the collection desk and the cutting service on measured queue times. They have also re-planned dead corners on a large floor after dwell per department showed where the visit stalled. Several follow the spring peak week by week on the visitor curve, so garden and outdoor staffing rises with the customers. One of them measured the share of trade and private customers on site from the vehicles that arrived, and planned the yard and the store around it.
Telia's partnership with Bumbee Labs is important for us to expand our business. It allows us to develop our use cases for location and movement insights to be even more granular. By combining our anonymized and aggregated mobile network data with Bumbee Labs solution of GDPR-safe Wi-Fi probe data, we ensure that the collection of data follows the strictest guidelines of GDPR compliance all the way.
Frequently asked questions
Can footfall analytics measure the yard and the drive-in of a DIY or hardware store?
Yes. Outdoor flow on the yard, the drive-in and the car park is measured alongside the store, so you see arrivals, the share that comes inside, and where on the site queues form.
Can footfall analytics tell trade customers from consumers at a builders' merchant?
In practice the hourly curve separates them well: trade comes early on weekdays, consumers in the evenings and at weekends. On some sites the mix has also been measured from arriving vehicles. Nothing identifies an individual, and the output is aggregate flow by hour and by zone.
Does a campaign leaflet show up in footfall analytics for a DIY store?
Yes. Visits in the week after a leaflet or offer are compared with the weeks before, so you see whether the campaign brought people in and, with sensors, whether they went to the aisle it promoted.
Does footfall analytics for a DIY or hardware site need cameras?
No. The measurement is approved by a data protection authority. Counting runs anonymously on the Wi-Fi the site already has, even across a large site. A sensor at the entrance adds exact counts where they are wanted, and staff are left out of them.
Where this fits
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Data protection:GDPR-compliant footfall analyticsThe IMY decisionGDPR CCTV