Edmonton case
Edmonton restaurant AI booking scenario
A composite of local eateries that wanted faster replies, steadier bookings, and less prep waste—without adding staff or new hardware.
Starting point
Phones rang during dinner service, walk-ins stacked up, and callers often waited for answers on hours, menu, or dietary notes. Reservations landed in notebooks, so reminders were inconsistent and no-shows spiked on busy weekends.
What we implemented
- • Web and social assistant answering menu, hours, parking, and taking bookings in real time.
- • SMS reminders with a one-click reschedule option to backfill empty tables quickly.
- • Simple demand cues: day-of reservations, weather, and local events to flag prep quantities and staffing.
- • A single view of bookings so front-of-house and kitchen shared the same numbers.
Outcomes to aim for
These are planning targets, not promised results. Actual outcomes vary by baseline no-show rate, booking volume, menu, season, and team adoption.
- • Faster web and social replies during peak service windows.
- • Fewer no-show gaps when reminders include an easy reschedule path.
- • Better prep planning when booking volume and event signals are visible earlier.
- • Less owner time spent on phone tag and manual confirmations.
Timeline & effort
Week 1: intake, menu FAQ, and booking flow. Week 2: SMS reminders and shared calendar. Week 3: demand cues and staff training (two 45-minute sessions). All on month-to-month tools—no new hardware.
Why this worked
AI handled repeat questions and captured bookings while the team focused on guests in the room. SMS kept tables filled and demand cues reduced over-prep on slow nights.
Try a pilot
Start with chat + SMS reminders for two weeks, then layer in demand cues once the team is comfortable.
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