How AI Can Help Your Restaurant Get More Customers

How AI Can Help Your Restaurant Get More Customers

Running a restaurant means balancing service, staffing, bookings, reviews and marketing - often at the same time.

But valuable opportunities can be lost in the gaps: a phone call missed during service, a former regular who is never contacted again, a quiet midweek evening, or an online review that goes unanswered for too long.

This practical session will explore how accessible AI tools can help independent restaurants get more customers and create better guest experiences - without adding another complicated system for your team to manage.

What you will learn

You will leave with practical ideas for using AI to:

• Capture more booking enquiries, including when your team is busy.
• Respond to common guest questions more quickly and consistently.
• Reduce no-shows with automated booking reminders.
• Reconnect with past diners using personalised, timely campaigns.
• Promote quiet nights to the customers most likely to return.
• Respond to Google reviews faster while retaining human oversight.
• Reduce repetitive admin and give your front-of-house team more time for guests.

Live TablePulse demonstration

The session includes a live demonstration of TablePulse, a conversational AI and guest-engagement platform designed for independent restaurants.

You will see how a restaurant can set its booking rules, opening hours, menu information, FAQs, tone of voice and escalation preferences - then use AI to handle routine guest interactions while ensuring staff remain in control of anything requiring human judgement.

TablePulse can help restaurants:

• Answer routine calls and booking questions 24/7.
• Direct guests to booking options and capture enquiries that might otherwise be missed.
• Send booking reminders and follow-up messages.
• Identify and reactivate lapsed guests.
• Run campaigns for quieter periods.
• Monitor reviews, draft responses in the restaurant’s voice, and flag sensitive feedback for staff.

This is a practical demonstration and discussion - not a requirement to purchase anything.

Who should attend

This event is designed for:

• Independent restaurant owners.
• Restaurant managers and general managers.
• Front-of-house and operations leaders.
• Hospitality marketing and customer-experience teams.
• Café, bar, pub and casual-dining operators.
• Local business and community leaders interested in practical AI adoption.

No technical or AI experience is required.

Event details

Date: Monday 19 October
Time: 11:00am–1:00pm
Venue: Fishy Delishy Restaurant, 13A–14 Newham Parade, Cheshunt, EN8 9NU
Cost: Free
Format: Practical discussion, live demonstration and questions

What to bring

Bring the questions you are already asking about your restaurant:

• Are we missing bookings when the phone rings during service?
• Which past customers should we try to bring back?
• How can we reduce no-shows without creating more staff workload?
• How quickly should we respond to online reviews?
• Where could AI save time without losing the personal touch?

Hosted by

Hosted as part of the Google Data Center AI Fellowship Basecamp, with participation from Google Fellows, local business and community leaders, and the TablePulse team.

N/B:

This event may be photographed, recorded, or otherwise documented by the event organizer and/or Watson Institute. By registering for and attending this event, you acknowledge and consent to Watson Institute and the event organizer photographing, recording, or otherwise capturing your image, likeness, voice, name, and participation during the event and using such media for educational, promotional, reporting, fundraising, and other institutional purposes, including use on websites, social media, digital and print publications, and other marketing materials.

If you prefer not to appear in event photography or recordings, you must indicate your preference during registration. Event organizers and their photographers or videographers will make reasonable efforts to avoid capturing or using identifiable images of participants who opt out.