Measure what makes your retail destination pull
Footfall analytics shows a retail park where its visitors come from, how they move between the tenants and which stores carry the place, so owners can grow and value the destination on measured visits.
Catchment and tenant flows, privacy-first.
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Why retail destinations choose Bumbee Labs
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See your real catchment
Cellular 4G/5G network data extends the picture to where visitors travel from and how far the destination's pull reaches, beyond the site itself.
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Reveal the flows between tenants
Cross-shopping and zone correlation show which anchors pull traffic to their neighbours and which are false anchors visitors come to and leave.
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Destination-wide, no personal data
The counting is built to be anonymous and has a data protection authority's approval, so you can measure the whole destination, from car park to anchor, with a clear conscience.
Retail park footfall analytics measures the retail catchment, the flows between tenants and the visits to each unit. Wi-Fi counts the site, from the car park approach to the main tenants, and mobile network data covers the area beyond. Bumbee Labs is the company behind the only footfall method in Europe approved by a data protection authority.
The short version
- Retail park footfall analytics counts visits to an out-of-town destination as a whole, to each tenant and to clusters of stores, and shows the flows between them.
- Mobile network data, read by district, gives the retail catchment, and Wi-Fi counts the site itself, anonymously.
- The six questions below run from where visitors come from to the case for a new location, and ten shorter ones follow.
Which questions can retail park footfall analytics answer?
How far will people drive to our retail park, and which districts do they come from?
Mobile network data shows, by origin district, where visitors come from, how far a retail park’s pull reaches and where people go beyond it. Over time, the counts show which districts send a growing share of visitors and which a shrinking one. Hybrid people counting adds Wi-Fi counts on site, so origin and on-site visits sit in one system.
Do visitors walk on from the big stores to their neighbours, or straight back to the car park?
Cross-shopping is the share of one store’s visitors who go on to another, read by zone correlation from Wi-Fi people counting. Across the open ground of a retail park, it shows which large stores send visitors on to their neighbours and which ones visitors come to and then leave. A retail heatmap draws the flows between zones.
What is each unit on the retail park worth, given the visitors it gets and the visitors it sends on?
Visits and passers-by for each unit on a retail park, with its capture rate, show the traffic a location gets and generates. Where a large unit with its own entrance from the shared car park sits beside small ones, these figures are the basis for rents, tenant mix and leasing. Footfall data for lease negotiations covers the negotiations.
From the car park to the door: how many cars arrive, and where do they park?
LiDAR or AI camera counts at a retail park’s car park entries and exits give occupancy against capacity by zone, with arrivals and stay length by hour. Read together with the flow on to the stores, occupancy shows when the car park fills and which entrances drivers use. Parking occupancy measurement sets this up for car parks and forecourts.
Our tenants pull in different directions. How do we get them to work for the whole place?
Give owner and tenants one visit series for the whole retail park, through the People counting API or dashboards each stakeholder can read, with peaks and trends for shared staffing and marketing. Compare joint campaigns with comparable periods, as benchmarking footfall does, to see whether they lifted the whole place or only one unit.
We are weighing an extension or a new retail park. Is the evidence enough to decide?
Check the flows before committing. Mobile network data shows at district level whether an area carries the visitors an extension or a new retail park needs, with no hardware at a site you do not yet occupy. Read it against your existing park’s measured catchment and flows, as site selection analysis does.
What else do retail park owners and managers ask their footfall data?
- Do queues build on the access road at the big holiday weekends?Hourly vehicle counts by direction show when traffic peaks and give the municipality figures to work from; see traffic counting.
- How do the spring peak and the Christmas trade look at the retail park?Visits per week across the year show the seasonal curve that staffing, marketing and upkeep can follow; see the retail year in visitor numbers.
- Can cleaning, security and snow clearing follow how the area is used?The visit count by day and hour shows when the area is busy and when it is quiet; mall analytics answers the same question for a shopping centre.
- Which routes do people take between the stores and the car park?Visitor paths across the area trace them, and desire lines explains why they differ from the designed ones.
- Our outlet village draws visitors who travel far. Where do they come from, and how long do they stay?Mobile network data gives their districts of origin, and Wi-Fi on site gives their dwell time.
- Did the car show, the market or the opening lift the whole retail park or only the event space?Zone-level counts show the event area and the rest of the park separately; see measure event impact.
- Is it worth keeping the whole area open on Sundays and evenings?Visits by hour, for the area and for each store, show which hours carry traffic and which stores draw it; see staff planning with footfall data.
- Fast chargers, fast food and drive-thrus: does passing traffic turn into visitors?Vehicle counts on the road and visits at the stores sit in the same platform, so the two can be read side by side.
- A new competitor opens nearby. Are we losing part of our catchment?Visits by origin district over time show whether a drop sits in one district or across the whole retail catchment.
- Our anchor is leaving or switching units. What happens to the stores around it?Counting visits to each neighbour the same way before and after the move makes the two periods comparable.
Curious what this looks like for your venue?
Approved and validated
The method is approved by a data protection authority and proven with academia, partners and customers. It gives you insight across the whole destination with nothing personal in the data.
We are very happy to announce this partnership with Bumbee Labs to boost our Wireless solutions portfolio and bring what we believe is the future for retail businesses, measured by trustful data. What can't be measured, can't be improved.
Frequently asked questions
Can footfall analytics show where a retail park's visitors come from?
Yes. For a retail park, Wi-Fi on site is combined with cellular (4G/5G) network data to map its catchment: the places its visitors actually travel from.
Can footfall analytics tell which tenants on a retail park really pull traffic?
Yes. Zone correlation records where visitors go once they have left a store. A tenant whose visitors carry on to the neighbouring stores is a true anchor, and one whose visitors go no further is a false anchor.
Does footfall analytics for a retail park need to cover the whole site?
No. Measuring the entry and exit points and the anchor locations is usually enough, because an anonymous alias is recognised again when a visitor reaches the next measured zone. Gaps in coverage between them do not break the picture.
Where this fits
Industries and segments
Metrics
Methods
Platform and integrations
Data protection:GDPR-compliant footfall analyticsThe IMY decisionGDPR-compliant vs approved