You know how many prescriptions were dispensed. You don't know how long people waited, or how many came in for the shelves and never reached the counter.
A pharmacy has two visits in one room, the prescription counter with its queue and the self-care shelves with their own rhythm. Footfall analytics shows both, hour by hour, without identifying anyone, so pharmacist hours, opening hours and the shop floor follow the customers.
For the pharmacy chain and the independent pharmacy. Anonymous by design, approved by a data protection authority, no cameras.
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Three questions every pharmacy asks
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When does the prescription queue build?
Dwell in the counter zone by hour and weekday shows when waiting time climbs and when the counter stands quiet, so pharmacist hours follow the queue rather than the schedule.
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How many come for the shelves, and how many for the counter?
The share of visitors who stay in self-care and the share who reach the counter, by hour, so the shop floor and the counter are staffed as the two visits they are.
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Can this be done without a privacy debate?
Yes. Nothing about what anyone buys or collects is measured, no images are stored, and the method is the only footfall method in Europe approved by a data protection authority.
Two visits in one room
A pharmacy is two shops sharing a door. One is the prescription counter, where the customer waits, and where a queue is felt more sharply than in any other kind of store. The other is the self-care floor, which has its own rhythm and its own customers, many of whom never reach the counter. Dispensing figures describe only the first. Footfall analytics for pharmacies shows both, hour by hour and zone by zone, without identifying anyone or recording anything about what they came for.
What you see, pharmacy by pharmacy
- Waiting time at the counter: dwell in the prescription zone by hour and weekday, the earliest sign of a queue.
- Counter visits and shelf visits: the share of visitors who reach the counter and the share who stay in self-care.
- The hourly curve: when the pharmacy fills and empties, so pharmacist and floor hours follow the customers.
- Capture rate in a centre: for a pharmacy in a shopping centre, the share of the centre’s flow that comes in.
- Peaks beside a clinic: for a pharmacy next to a health centre, visitor peaks against clinic hours.
- Pharmacy against pharmacy: the same measures across a chain, so staffing norms are set on real flow.
How the hourly curve becomes a rota is on staff planning with footfall data; what the method does and does not collect is on GDPR footfall analytics.
What pharmacies have done with it
Things pharmacies and pharmacy chains we measure have actually done:
- Moved pharmacist hours onto the measured queue curve at the prescription counter.
- Staffed the self-care floor separately after the split between counter visits and shelf visits by hour became visible.
- Set evening and weekend hours on the flow outside the door rather than on habit.
- Measured capture rate from a shopping centre’s flow and judged the location on it.
- Followed clinic hours in the visitor curve next to a health centre and staffed accordingly.
- Used flow data when a pharmacy was moved or a new one opened.
- Set staffing norms across a chain on the real hourly flow of each pharmacy.
Getting started in a pharmacy
Most pharmacies start on the Wi-Fi already in the premises, with an entrance sensor added where exact counts are wanted, and staff filtered out of the counts. Nothing about what anyone buys or collects is measured, no images are stored, and the output is aggregate statistics only. The method is the only footfall method in Europe approved by a data protection authority, which is why pharmacies can start without a privacy debate. The first month gives the counter waiting picture, the self-care split and the hourly curve; a chain adds pharmacies on the same setup, in the dashboard or through the API into its own BI.
How the method was approved → How Wi-Fi people counting works →
We are very excited by this collaboration with Bumbee Labs as their data expertise will complement our IoT know-how providing an unparalleled service to our clients across several verticals, industries and markets in the Middle East.
Frequently asked questions
What exactly is measured in a pharmacy?
Anonymous flow only, how many people are in the pharmacy, in which zone, for how long, and by the hour. Nothing about what anyone buys, collects or asks is measured, no personal data is created, and no images are stored. The output is aggregate statistics.
Can you measure waiting time at the prescription counter?
Yes. Dwell in the counter zone by hour is the waiting-time picture, and it is the earliest sign that pharmacist hours and the queue are out of step. It is measured without identifying anyone.
Does this work in a shopping centre or beside a health centre?
Yes. In a shopping centre the pharmacy's capture rate from the centre's flow is visible; beside a health centre the visitor curve follows clinic hours, and staffing can follow it.
Do we need cameras?
No. The core measurement runs on the pharmacy's Wi-Fi, anonymously, and it is the only footfall method in Europe approved by a data protection authority. A small 3D sensor or LiDAR unit above the entrance adds exact in/out counts where wanted, still without storing images of anyone.
What pharmacies do with the data
Pharmacies we measure have moved pharmacist hours onto the measured queue curve at the prescription counter, staffed the self-care floor separately after the share of counter visits and shelf visits by hour became visible, set evening and weekend hours on the flow outside the door, and used flow data when a pharmacy was moved or a new one opened. Pharmacies in shopping centres have measured their capture rate from the centre's own flow, and pharmacies beside health centres have seen the visitor peaks follow clinic hours. Several chains run the same measurement across their pharmacies and set staffing norms on the real flow rather than on sales alone.