See the service your guests experience
Cameras count who walks in, who leaves without ordering, how long guests wait and how quickly tables turn. Compared with POS bills, that's your real conversion rate.
Camera AI powered by DeepObserve.ai
What it replaces
The paper, calls and spreadsheets this takes off your team's plate.
How it works
Footfall and conversion
Entrances count walk-ins and group size. Divided into POS bills, you see how many visitors actually became customers.
- Walk-ins and walk-outs
- Group size estimates
- Conversion by hour and day
Waiting and service speed
A table seated with no order after a set time, or a queue longer than your limit at a QSR counter, notifies the floor manager.
- Seat-to-order time
- Queue length at counters
- Table turn time
Staffing to demand
Hourly footfall sits next to the roster, so you can see which hours are understaffed and which are overstaffed.
- Footfall by hour on the roster
- Service speed against staffing
- Weekday patterns
Getting started
The order we set it up in.
Mark entrances
And tables or counters.
Set limits
Wait and queue thresholds.
Link POS
For conversion.
Review
Daily and hourly patterns.
What changes
What teams using Footfall and Service Speed should expect to see.
- A real conversion rate, not an estimate
- Slow service noticed during service
- Rosters matched to busy hours
Questions
Does it identify customers?
No. Footfall counting counts people and groups; it doesn't identify customers.
Does it work for QSR counters and dine-in?
Yes. QSRs usually focus on queue length and order time; dine-in on seat-to-order time and table turns.
Can it count delivery riders separately?
Riders can be counted in a separate pickup zone and compared with aggregator orders.
See DeepRestaurantAI with your own outlets
We'll connect a sample of your POS data and walk you through sales, purchasing, food cost and DeepObserve.ai camera AI for your format.