What it does
Know what sold, what almost sold, and what caused the difference.
- Regulars and lapsed regulars
- Visit patterns are tracked over time, so a guest who used to come fortnightly and has not been in for five weeks is something you find out about rather than something you notice a year later.
- What they order
- Preferences build from real orders, which is what lets the menu and the recommendations know a vegetarian is a vegetarian without asking every visit.
- Consent is part of the record
- Marketing only reaches guests who opted in, and that opt-in travels with the profile. Nothing is sent on the strength of an email address alone.
- One guest, not five rows
- The same person across visits, devices and orders is one profile, so counts and averages are not quietly inflated by duplicates.
See it
Example data
Guest #1247
Fortnightly for nine months. Vegetarian. Always books a Thursday.
- Visits
- 19
- Average bill
- £54
- Lifetime
- £1,026
- Last seen
- 34 days
A win-back with a personal code for a free starter, in your voice, to this guest and the eleven others whose visits stopped the same way. Ready to send or bin.
Where it sits
One system, five pillars
Guest intelligence is part of revenue & insights.
Know what sold, what almost sold, and what caused the difference. It runs on the same menu, the same tables and the same bill as everything else here — nothing to integrate, nothing to reconcile.
Take the order at the table, the counter or the kerb, and get it to the kitchen.
QR ordering · Digital menus · Live orders · Kitchen display · Guest payments · Dish recommendations · Sage AI waiter
Fill the diary — and give a forgotten table a chance to be sold again.
Bookings & events
Cost the menu on what you are actually paying for the food.
Stock & purchase orders
Compare what you ordered, what arrived, and what you were billed for.
Supplier control
Build the rota, publish it once, and know who did what on the floor.
Team & shifts