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Hospitality Chatbots: Everything You Need to Know in 2024

Updated on Feb 5
4 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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According to PwC, the hospitality industry is the one that can charge the second-highest premium for excellent customer experience with a 14% premium margin.1 Fast and easy-to-engage digital channels are part of the excellent customer experience.

Engaging with many customers 7/24 via live agents is not an efficient strategy for the hotels. Therefore, they can leverage their customer service with hospitality chatbots. Nevertheless, many hotels still do not use chatbots. 

This article aims to make hotel managers reconsider their investment strategies regarding hospitality chatbots. In this regard, we introduce:

  • Types 
  • Benefits 
  • And use cases of hospitality chatbots.

What is a hospitality chatbot?

Hospitality chatbots (sometimes referred to as hotel chatbots) are conversational AI-driven computer programs designed to simulate human conversation. By responding to customer queries that would otherwise be handled by human staff, hotel chatbots can reduce cost of customer engagement and enhance the client experience.


Salesforce is the CRM market leader and Salesforce Contact Genie enables multi-channel live chat supported by AI-driven assistants. Salesforce Contact Center enables workflow automation for many branches of the CRM and especially for the customer service operations by leveraging chatbot and conversational AI technologies.

Which communication channels can hotels deploy chatbots?

Hospitality chatbots can be deployed on different channels such as:

What are the types of hotel chatbots?

There are two types of hospitality chatbots which are:

  1. Rule-based chatbots: These chatbots provide predetermined answers for certain questions. Since they cannot understand user intent, they are suitable for automating frequently asked questions. The main advantages of rule-based chatbots are their relatively easy deployment and lower price compared to AI chatbots.
  2. AI chatbots: These chatbots can handle more sophisticated customer queries for hotels thanks to their NLPNLU capabilities. For instance, AI-driven chatbots can make bookings for customers. AI chatbots cons’ on the other hand are the greater time and cost needed for deployment.  

Top benefits of hospitality chatbots

Work around the clock

According to Deloitte, one of the most important metrics customers use to assess the effectiveness of customer service is the length of time it takes to resolve a query (see Figure 2). Response times can be crucial in the hotel industry, as customers may engage with hotels from all time zones possible. This problem can be mitigated by hotel chatbots since they never:

  • Tire
  • Need to sleep
  • Feel hunger
  • Feel boredom etc.

Therefore, hotel chatbots can provide 24/7 customer service.

Figure 2: What modern customers expect from customer services.

According to Deloitte, personalization, speed and resolution outcome of the customer service are the most important capabilities that customers demand.

Multi-language support

You may offer support for a variety of languages whether you utilize an AI-based or rule-based hospitality chatbot. Because clients travel from all over the world and it is unlikely that hotels will be able to afford to hire employees with the requisite translation skills, this can be very helpful.

Particularly with AI chatbots, instant translation is now available, allowing users to obtain answers to specific questions in the language of their choice, independent of the language they speak. By being able to communicate with guests in their native language, the chatbot can help to build trust.

Top 5 use cases of hospitality chatbots

1. Personalized recommendations via intent recognition

AI-powered hospitality chatbots can replicate the offline travel planning process, including the advice of travel agents. Nowadays, chatbots are able to provide individualized advice by learning about the user’s:

  • Personal hobbies (do they enjoy diving, for example?).  
  • The number of individuals they are traveling with (business, honeymoon, etc.).
  • The number of individuals they are traveling with.

Figure 3 illustrates how the chatbot at House of Tours takes all these aspects into account when arranging customers’ vacations to maximize their enjoyment.

Figure 3: Personalized travel planning via hospitality chatbots.

Image is a screenshot of a conversation between a client and hospitality chatbot. Chatbot asks questions to the customer to suggest a suitable vacation.
Source: Haptik

2. Checking visa eligibility

Some citizens must obtain a visa in order to travel to specific nations. But visa refusal is a frequent occurrence. For instance, over 15% of visa requests in 2021 were rejected by Schengen countries.3 Visa denial might ruin your clients’ travel plans, result in financial losses (non-refundable prepayment ), and lower customer satisfaction.

Chatbots can be used by hospitality businesses to check their clients’ eligibility for visas (see Figure 4). Additionally, chatbots provide details about the paperwork consulates require, upcoming visa appointments, and may typically assist consumers through this challenging and perplexing process.

Figure 4: Chatbot helps customers to have a visa.

Hospitality chatbots can assist users during visa applications.
Source: Haptik

3. Making hotel reservations

Hotel chatbots can browse possible rooms and book a suitable one for the clients. Via various communication channels (such as WhatsApp, Facebook Messenger, and mobile apps) Users can inform chatbots about their destination and travel dates as well as specific criteria such as: 

  • Non-smoking rooms 
  • Budget constraint 
  • The number of people that will stay in the room 
  • All-inclusivity, etc.

Hospitality chatbots use these criteria to find suitable room options. Then, bots send options to the customer. If customers like any of the options they can proceed with the booking. 

For instance, in Figure 5, a client can browse hotels in and near Amsterdam and verify availability at particular times using Oyo’s WhatsApp chatbot.

Figure 5: Oyo’s chatbot browses hotels in Amsterdam.

In the image a hotel chatbot helps a customer for booking.
Source: Haptik

4. Answering FAQs

IBM claims that 75% of customer inquiries are basic, repetitive questions that are quickly answered online. If hotels analyze guest inquiries to identify FAQs, even a rule-based chatbot can considerably assist the customer care department in this area.

No doubt AI-driven chatbots can also handle FAQs for instance, As seen in Figure 6, AI-powered Omar (Equinox hotel’s chatbot) answers frequently asked questions such as the availability of towels in the hotel room.

Figure 6: Equinox Hotel’s chatbot answers FAQs.

Source: Haptik

5. Sending personalized notifications

It is possible to send personalized notifications such as:

  • Payment details.
  • Booking details.
  • Personalized discounts.
  • Delays in the flights.
  • Schedule of travel (if it is a business trip).

For such tasks we specifically recommend hotels deploy WhatsApp chatbots since 2 billion people actively use WhatsApp, and firms increase the chance of notification getting seen. 

If you wish to have a hotel chatbot but were unable to find a suitable provider, you can read the articles below:

  1. WhatsApp Business Partners: Everything You Need to Know.
  2. Conversational Commerce Platforms: Data-driven Benchmarking.
  3. 50+ Chatbot Companies To Deploy Conversational AI.

You can read our Restaurant Chatbots: Use Cases, Examples & Best Practices article to learn more about restaurant bots.

Finally, if you have further questions about hospitality chatbots you can reach us:

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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