Travel is the category where chatbots finally earned their keep. Booking intent is high, questions are repetitive, and the cost of a human agent answering “what time is my flight?” for the hundredth time is real money. The bots on this list are not mock-ups or lab demos. Every one of them shipped to production and is still live at time of writing.

We pulled the list from public case studies, vendor disclosures, and our own work on travel accounts. Each entry describes what the bot does, which channel it runs on, and why it converts better than the web form it replaced.

12 travel chatbot examples from brands that publish their numbers

1. Expedia — Messenger booking assistant

Expedia ran one of the earliest large-scale travel bots on Facebook Messenger. Users type a city and dates; the assistant returns hotel options with live prices and deep-links to checkout. Average conversation time is under 90 seconds.

2. HotelTonight — last-minute deal bot

HotelTonight built a bot around the app’s signature speed: three taps to a room tonight. The assistant asks for city, budget tier, and party size, then returns three hand-picked options with a book button.

3. Skyscanner — flight search on Skype and Messenger

Skyscanner’s bot handles “where can I fly for $300 next weekend?” style prompts. It is a genuine discovery tool, not a form wrapper, and it kept conversation rates above 40% during its first year.

4. KLM — BlueBot (BB)

KLM’s BlueBot manages booking confirmations, boarding passes, and flight updates inside Messenger. The airline reported handling over 16,000 conversations per week with a CSAT above 4.5 out of 5.

5. Lufthansa — Mildred and Elisa

Lufthansa runs two bots: Mildred for fare discovery and Elisa for post-booking service. Elisa alone deflects roughly 40% of call-center volume during irregular operations, according to Lufthansa’s tech blog.

6. Marriott — ChatBotlr on Slack and Facebook

Marriott’s ChatBotlr lets Bonvoy elites request room service, housekeeping, and late checkout through chat. It is one of the few travel bots built for in-stay, not pre-stay, and it reduced front-desk phone volume at pilot properties by double digits.

7. Booking.com — native messaging assistant

Booking.com integrated an AI assistant directly in the app to answer “is breakfast included?” and “can I cancel?” questions without pinging the property. It cut refund disputes and moved support SLA from hours to seconds.

8. Kayak — Alexa and Messenger bot

Kayak exposes its search API through voice and chat. “Alexa, ask Kayak how much to fly from Boston to Miami in June” returns a live price range. Handy for repeat travelers who do not want another tab.

9. Amtrak — Julie

Amtrak’s Julie handles schedules, fares, and station info over web chat and voice. Amtrak reported an 800% ROI on the project within the first year, and bookings through Julie carry a 25% higher average ticket value.

10. Hipmunk — Hello Hipmunk

Hipmunk’s bot worked over email and Slack, parsing travel dates from a forwarded calendar invite and replying with flight and hotel suggestions. A clean example of a chatbot meeting users where they already plan trips.

11. MakeMyTrip — Myra and Gia

India-focused MakeMyTrip runs two bots: Myra for post-booking support and Gia for pre-booking discovery. Together they handle millions of conversations per month and push a third of support traffic away from agents.

12. Hyatt — concierge SMS bot

Hyatt’s SMS concierge lets guests text the front desk for restaurant bookings, spa slots, or amenity requests. The same number works across 900+ properties, which is the kind of detail that separates serious production builds from weekend projects.

What the winning travel chatbot examples have in common

• They solve one job well — discovery, booking, or in-stay — never all three at once.
• They hand off to a human the moment the conversation smells like a complaint.
• They live where the user already is: Messenger, SMS, Slack, or the brand’s own app.
• They publish numbers, which keeps the internal team honest about ROI.

If you are scoping a bot and the team wants it to do everything on day one, point them at this list. The strongest travel chatbot examples started narrow and only expanded after the first use case was paying for itself.

How we approach travel bot builds at WebCoreLab

Our default stack for a new travel client is a rules-first flow on top of an LLM for the fuzzy parts. Rules handle dates, cities, and prices because a hallucinated fare is a lawsuit. The LLM handles paraphrasing, FAQ, and the “what is the weather in Lisbon?” side chats that keep the conversation human.

We ship in three-week sprints, measure deflection and attach rate, and kill branches that nobody uses. That process is the same one that produced the travel chatbot examples on this list. Nobody gets 3x conversions from a big-bang launch. They get it from trimming.