How many visitors walk out without buying at peak times?
Without reliable counting at the entrance, there is no way to know how many visits never turn into sales. Comparing measured footfall with your till receipts shows when that gap widens.
Smart Retail
Measure footfall and customer flow with the cameras you already have
VIDEO.MA turns existing or new cameras into data sensors: visitor counts, zone-by-zone traffic, checkout queues and space occupancy. Every project starts with an on-site feasibility study, then indicators are configured around your commercial objectives.
What it is costing you today
Simulate my lossesHow many sales do you lose when checkout queues get too long?
Shoppers who abandon their basket in front of a long queue leave no trace. Measuring queue length by time slot lets you open another till at the right moment, not after the fact.
Which aisles take up floor space without drawing anyone in?
Revenue per aisle does not tell you whether shoppers walk past without stopping. Measuring activity by zone helps decide where to rearrange, move a range or strengthen displays.
Retail & Commerce
Industry challenges
Footfall you can only guess
Without reliable entrance counts, you cannot tell whether a drop in sales comes from fewer visitors or from weaker in-store conversion.
Queues that drive customers away
Checkout peaks are rarely anticipated. Shoppers abandon their baskets and extra staff arrive too late.
Aisles and zones with unmeasured appeal
Layout, merchandising and promotion decisions often rely on instinct rather than on traffic and dwell data per zone.
Stores that are hard to compare
Across a store network, the lack of consistent indicators makes it difficult to benchmark performance objectively and spread best practices.
VIDEO.MA
What VIDEO.MA delivers
Visitor counting
Per projectAnonymous counting of entries and exits per door and per time slot, using counting lines configured on entrance cameras.
Customer flow analysis
Per projectAggregated measurement of movement between store zones to reveal the busiest aisles and the areas shoppers overlook.
Queue detection
Per projectEstimated number of people waiting at each checkout, with alerts when a configured threshold is exceeded so another till can be opened in time.
Store occupancy
Per projectTracking of how many people are present at the same time in the store or in a given zone, useful for managing peaks and capacity limits.
Aisle and zone activity
Per projectAnonymous, aggregated measurement of passes and dwell time in front of an aisle, end cap or promotional area.
Potential out-of-stock signal
Feasibility studyVisual detection of empty or depleted shelf space at defined locations. This is an alert signal to be confirmed against your stock data, not an inventory measurement.
POS reconciliation
Feasibility studyConversion rate (POS transactions / visitors) by hour or day, subject to integration with your point-of-sale system.
Self-service multi-store benchmarking
Coming soonConsolidated dashboards comparing indicators across several stores, planned for the upcoming VIDEO.MA SaaS platform.
Example metrics
Visitors per hour
Video dataNumber of entries counted per time slot, derived from video analysis of the entrances.
Estimated checkout wait time
Video dataEstimated number of people queuing and how long they wait, calculated from video.
Occupancy by zone
Video dataAverage and peak number of people present in each configured zone.
Average aisle dwell time
Video dataAverage time spent in an aisle zone, measured anonymously and in aggregate.
Actual sales and transactions
Business integrationRevenue and transaction counts from your POS software; these figures are never inferred from video.
Conversion rate
Video + business dataPOS transactions divided by counted visitors, obtained by combining POS data with video counts.
Dashboard preview
Dashboard · Downtown Store — TodayDemo data
Visitors today
1,284
Peak occupancy
142 people
Average checkout wait
3 min 40 s
Conversion rate
27%
Activity per hour
Events
- Queue > 6 people — Checkout 2
- Footfall peak — Main entrance, 5:30 pm
- Shelf possibly depleted — Beverages aisle
- Promo zone: traffic rising since 3 pm
Deployment approach
- 1
Audit and feasibility study
Store visit, inventory of existing cameras, review of angles, lighting and network, and definition of priority indicators.
- 2
Zone and indicator configuration
Setup of counting lines, checkout and aisle zones, alert thresholds and, where planned, the connection to your POS system.
- 3
Single-store pilot
A test phase in one store to check counting accuracy against manual counts and fine-tune the parameters.
- 4
Rollout and follow-up
Extension to other stores or zones, team training and regular monitoring of data quality and indicators.
Prerequisites, limitations and privacy
- Counting accuracy depends on camera position and angle, lighting and crowd density; an overhead camera at the entrance usually gives the best results.
- The potential out-of-stock signal is a visual aid: it does not replace a stock count and must be confirmed against your inventory data.
- Conversion rate requires integration with your POS system; without it, only video-derived indicators are available.
- Analysis is anonymous and aggregated, with no facial recognition. As data controller, the retailer must complete the formalities required by Moroccan Law 09-08 with the CNDP; VIDEO.MA can help prepare them.
Frequently asked questions
Can we use the cameras already installed in our store?
Often yes, provided their resolution, angle and video stream are usable. The feasibility audit determines which cameras can be reused and where additional equipment, such as an overhead counting camera above the entrance, is recommended.
How accurate is people counting?
It depends on camera placement, lighting, reflections and crowd density. That is why we measure accuracy during the pilot, comparing results with manual counts, before any large-scale rollout.
Are shoppers identified?
No. The proposed solutions count people and measure flows anonymously, with no facial recognition or biometric identification. Processing can run locally on an Edge AI device to limit how far images travel.
Can the data be connected to our POS software?
It can, depending on your POS system and its export options (API, files, database). The integration is assessed in a dedicated study and makes it possible to calculate conversion from actual transactions.
Does it work for a chain of stores?
Yes. Deployment can be carried out store by store with consistent indicators. Self-service multi-site dashboards are part of the upcoming SaaS platform; today, consolidation is set up on a per-project basis.
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