Smart Restaurant
How many guests per service, how many tables in use, how long is the wait at the counter? VIDEO.MA configures your cameras to measure these indicators anonymously and, if you wish, links them to your POS software.
A guest who sees a full room or a queue at the counter and walks away shows up in no report. Measuring wait times and occupancy per service makes these silent departures visible, along with when they happen.
A table that is free but not yet cleared is revenue that is not coming in. Tracking real table occupancy shows where turnover slows down and where service organisation can be adjusted.
Rotas are often based on instinct and on last week’s services. Knowing measured footfall hour by hour lets you match staffing to actual activity, without over- or under-staffing.
Restaurants & Cafés
Without footfall data by hour and day, staff rotas are built on estimates and rushes are endured rather than prepared for.
It is hard to know which tables turn over most, how long they stay occupied and when the dining room is genuinely at capacity.
A queue at the counter or a slow service is enough to make guests leave, yet the venue has no way to measure how often it happens.
Till figures show what was sold, but not how many people came in, waited or left without ordering.
VIDEO.MA
Anonymous entry counting by time slot to know the actual footfall of every service.
Detection of occupied and free tables and measurement of how long they stay occupied, based on zones drawn on the floor plan.
Estimated time spent in a waiting area, at the entrance or the counter, before being seated or served.
Alerts when the queue at the counter, drive-through or till exceeds a threshold set by the venue.
Time between a guest entering an ordering zone and leaving it, to track how smoothly service is flowing.
Aggregated activity analysis in prep and pass areas, with no individual tracking of staff. Feasibility depends heavily on the kitchen layout.
Combining video counts with actual transactions from your POS software to calculate average spend per guest or conversion rate.
Number of guests who came in during lunch, dinner or any defined time window, measured by video.
Share of tables in use at any moment and average occupancy duration, derived from video.
Average time spent in the waiting area before being seated or served, estimated from video.
Revenue and transaction counts from your POS software, never inferred from images.
Actual POS revenue divided by the number of guests counted by video.
Guests this service
218
Tables occupied
19 / 24
Average wait
4 min 10 s
Average time at table
38 min
Activity per hour
Events
Survey of the floor plan, existing cameras and their angles, and definition of the indicators that matter for running service.
Drawing table, waiting, counter and kitchen zones, and setting alert thresholds and service time windows.
Testing on contrasting services (weekday, weekend, rush) to validate accuracy and adjust zones and thresholds.
Dashboards go live, optional POS integration is set up and indicator quality is reviewed regularly.
In many cases some of your existing cameras can be reused, especially those with an elevated view of the dining room. The audit identifies blind spots and any additional cameras required.
Yes. The system follows anonymous silhouettes within a zone to measure how long they stay, with no facial recognition and no identity stored. Only aggregated durations and counts are reported.
No, that is not a standard offering. When kitchen analysis is included, it is limited to zone activity, such as congestion at the pass or how long dishes wait, and is subject to a prior study.
Depending on your software and its export options, an integration can be studied to combine guest counts with actual sales. Without it, dashboards are limited to video-derived indicators.
Get a quote tailored to your sites, cameras and metrics.