Guide to Restaurant Chatbots (2025)

1. Taking reservations

Chatbots let customers reserve tables quickly and easily, offering instant confirmation without the need to call. In fact, booking chatbots are one of the simplest chatbots to build and deploy without vast technical knowledge.

2. Online ordering

Chatbots simplify takeout or delivery by guiding customers through the ordering process step-by-step on their preferred platform.

3. Order tracking

Provide real-time updates on order progress, from preparation to delivery, so customers always know what (and when) to expect.

4. Special offers and promotions

Chatbots can share tailored deals or promotions, such as happy hours, discounts, or seasonal menus, right when customers are most engaged.

5. Waitlist management

Chatbots manage walk-in waitlists by allowing customers to join the queue virtually and notifying them when their table is ready.

So no need to pass out beeping restaurant pagers to dozens of unwashed hands every evening, only for the battery to die mid-service. A win-win.

6. Event booking and reminders

Chatbots streamline the process of reserving space for private events or large parties, offering quick options for food, beverages, and additional services.

This can be baked into your typical restauarnt reservation bookings, but you'll want to build in another flow for the extra questions: are they bringing a birthday cake? Do they have a specific wine request?

7. Multilingual support

Chatbots communicate in the customer’s preferred language, making interactions smooth and inclusive for a diverse audience.

Most chatbot platforms provide this automatically, since LLM agents are powered by LLMs like ChatGPT (which offers services in 80+ languages).

8. Employee scheduling

Chatbots simplify shift management by allowing employees to check schedules, request changes, and receive updates on the go.

This is a very common feature of HR chatbots that are deployed to big companies that run on shift work. In fact, one of our partner organizations made an HR bot that predicts employee scheduling to a tee, including the number of upcoming sick calls.

9. Inventory management

Keep tabs on stock levels with chatbot alerts, ensuring staff are aware of low supplies before they become a problem.

10. Internal communications

Chatbots quickly notify staff and customers about emergencies, closures, or last-minute updates, ensuring everyone is informed in real time.

This is pretty similar to how hotels use chatbots — internal management resources between a large group of employees. [You can check out the impact of internal employee systems in hotels in our case study.]

11. Staff training

Another common feature of HR chatbots. Management can provide on-demand training tips or updates for staff, helping them stay informed about new menu items or policies.

12. Incident reporting

Allow staff to quickly report issues like maintenance problems or safety concerns through a chatbot for immediate action.

Domino's Dom: The Pizza Chatbot

The most well-known of the big chain restaurants, Dom has been on the scene since 2017.

Dom is accessible via Facebook Messenger – with no need to re-login into Domino’s. The bot aims to collect user preferences, design personalized conversations, and improve Domino’s social media impressions.

With tens of millions of Facebook impressions, Domino’s bot for ordering, tracking, and customer support is the perfect example of a straightforward success.

My Starbucks (Virtual) Barista

Starbucks’ chatbot, "My Starbucks Barista," is built into the mobile app to simplify ordering and enhance customer convenience. 

It understands natural language and allows customers to place orders by voice or text and pay through linked cards or gift cards.

My Starbucks Barista can also:

• Send orders to the nearest store for easy pickup
• Track rewards points and redeems offers through Starbucks Rewards
• Answer common questions like store hours and menu options
• Work on platforms like Amazon Alexa

TGI Fridays

TGI Fridays has added AI chatbots to its tech arsenal, making it easier for customers to place orders, find locations, and make reservations across platforms like Facebook Messenger and Twitter. These bots are all about keeping things simple and accessible for a fast-moving, digital-savvy audience.

“Today’s guests live in a digital world,” said Sherif Mityas, Chief Experience Officer. “Chatbot technology allows us to engage with our guests in a more personal way.” By partnering with Conversable, TGI Fridays is extending its signature social vibe beyond restaurant walls, letting guests interact whenever and wherever they want.

Integrate across channels

The best restaurant chatbots aren’t on websites – they’re WhatsApp chatbots, or Facebook Messenger bots, or accessible via other commonly-used channels.

Use sentiment analysis

Incorporate sentiment analysis to understand customers’ emotional tone. A chatbot can detect frustration during an interaction (e.g., delays in delivery) and respond empathetically or escalate to a human for resolution, enhancing customer satisfaction in critical moments.

This is becoming a popular feature for customer service chatbots, so that they can choose the appropriate course of action or tone (even if they don't come with real empathy. We can save that for the real hospitality employees).

Prioritize mobile optimization

Since most customers access chatbots via smartphones, ensure the chatbot is optimized for mobile platforms, offering smooth interactions on smaller screens.

Upsell with AI-powered personalization

There are endless ways to use AI for sales, and restaurants are no exception.

Train your chatbot to analyze past orders, preferences, and real-time interaction cues to suggest personalized recommendations. For example, if a customer orders pizza, the chatbot could offer a discount on a dessert they've enjoyed before or pair it with a drink that complements the meal.

Use predictive analytics for staff optimization

Leverage chatbot data to predict demand patterns, such as peak ordering times or popular items, and use it to schedule staff accordingly. This ensures the restaurant is prepared during busy hours while minimizing overstaffing during lulls.

Integrate AI-powered voice interactions

Go beyond text and enable voice-based chatbot functionality for hands-free customer interactions.

This way, customers can place orders while driving or cooking, making the chatbot more accessible and convenient in everyday scenarios. This also broadens appeal for users who prefer speaking over typing.

1. Define Objectives

Decide what you want your restaurant chatbot to achieve. Will it handle to-go orders? Take reservations? Allow customers to be escalated to a human?

Your objectives will shape the chatbot’s design and functionality. Most restaurant chatbots are LLM-powered agents, making them adaptable to a wide variety of tasks, like:

• Personalized recommendations
• Handling multilingual customer interactions

A clear set of goals will also guide your choice of AI platform and integration strategy.

2. Choose an AI Platform

Pick a chatbot platform that aligns with your objectives and offers the flexibility to scale. Look for features like:

• Integration capabilities for linking POS systems, delivery apps, and loyalty programs
• Support for your preferred LLMs or an LLM-agnostic framework
• Customization options to adapt to your restaurant’s branding and workflows

The right platform will set the foundation for a chatbot that fits seamlessly into your operations.

3. Integrate Core Systems

To make your chatbot truly effective, integrate it with essential tools like:

• POS systems for order processing
• Delivery apps like DoorDash or Uber Eats
• Reservation software for table bookings
• Customer loyalty programs 
• Analytics platforms 

These integrations will ensure your chatbot becomes a valuable part of your restaurant’s digital ecosystem.

4. Test and Refine

Run thorough testing before deployment to simulate real customer interactions. 

Test its ability to handle complex orders, provide accurate information, and escalate issues to human agents when necessary. 

Refine its workflows and prompts based on testing results to ensure smooth performance.

5. Deploy and Monitor

Once deployed, use chatbot analytics to track performance, like order accuracy and user satisfaction. Gather insights to make iterative improvements, adding new features or optimizing existing ones as customer needs evolve.

1. How do I connect my chatbot to existing systems if I use legacy POS software?

If you use legacy POS software, you can connect your chatbot using middleware tools like Zapier or custom-built API wrappers. This allows the bot to read from and write to the POS system without needing to rebuild it.

2. Is there a difference between a chatbot and a voicebot? Can both be implemented together?

Yes, there is a difference: a chatbot communicates via text, while a voicebot uses speech input and output, often using speech-to-text (STT) and text-to-speech (TTS) technology. However, both can be powered by the same AI engine and backend logic, and you can implement them together to support users across channels.

3. Do restaurant chatbots replace staff or just assist them?

Restaurant chatbots do not replace staff – they assist them by automating repetitive tasks like answering FAQs or booking reservations. This frees up human employees to focus on in-person service and solving more complex customer needs.

4. How can I use chatbots to boost customer loyalty or repeat business?

You can use chatbots to boost customer loyalty by remembering previous orders, offering personalized discounts based on past behavior, sending timely follow-ups or re-engagement messages, and simplifying loyalty point tracking and redemption – all of which encourage repeat visits and brand affinity.

5. How do I track and improve chatbot performance over time?

To track and improve chatbot performance, monitor metrics such as containment rate, average response time, order completion rate, user satisfaction (CSAT), and drop-off points. Use this data to iterate on conversation flows and retrain NLP models based on real customer interactions.