With the progression of chatbots in the hotel industry in recent years, it's quite easy to be left behind.
Using the hotel chatbot example on this page we will see first hand how a hotel chatbot works in hotel front office operations, can help improve hotel revenue and for general use in a hospitality business.
At any time during this article just click the button in the bottom right of the screen to see for yourself.
Here are some use cases (with live examples) of how you can use a hotel chatbot to supercharge your hotel website.
These AI hotel chatbots can switch from query to query (intent to intent) and get your guests the answers they want quickly and efficiently using your hotels voice.
In the image above you can see the chatbot handling 2 queries. (one about wifi, then the other about breakfast)
We can also go into more detail regarding each query. See below:
Pretty much any booking engine can be integrated (or any webpage actually) or a seamless transition from chat or query to checking prices and even completing a booking.
The hotel chatbot solution will, thanks to NLP processing (and our thorough pre-launch training) detect queries and many many variants such as:
"Do you have a room available next Friday?"
"I need to know the prices..."
"How much are your double rooms?"
In our hotel chatbot example we use a couple of external API's to make it kinda more interesting.
Our bot can give the current weather conditions.
It's set up for Lisbon but we have access to all the data using the Open Weather Map API
This opens up virtually limitless possibilities to retrieve live data from API endpoints to enrich your bot's responses.
Google Sheets can also be leveraged as a database where information can be both entered and retrieved by your chatbot.
Chatbot analytics is the process of analyzing historical bot conversations to gain insights about chatbot performance and customer experience.
Our work as a chatbot developer doesn’t end once the bot goes live.
Due to increasing competition in every industry, guest experience has become the key driver in gaining a competitive edge.
After we deploy a hotel chatbot, it is time to track how people are using it by...
1. Creating better guest experiences
2. Optimising Response Effectiveness
3. Understanding User Behaviors
4. Increasing User Satisfaction, Engagement, and Conversion
5. Better handling mundane and/or time-consuming tasks so that front office staff can spend more time creating personal relationships with guests
6. Handling inquiries faster and more efficiently
7. Ensuring more accurate service that reduces costs and risks of human error
8. Identifying unique cross-selling and upselling opportunities
Reports on traditional analytics metrics:
Engagement and Retention
Users and Sessions
Build insight via conversational data specific reports:
NLP response effectiveness
Top Messages and Intents
Live person takeover
Alerts & triggers
You basically have 2 options:
1. Upskill your current team with the skills and knowledge to build and deploy an AI hotel chatbot solution or:
2. Engage a chatbot developer with the necessary conversation building, tools and programming knowledge.
Being honest, building a basic FAQ chatbot isn't that difficult.
For example, Google's Dialogflow has endless tutorials online and the learning curve isn't that steep.
It only starts getting complicated when you want to add functionality and webhooks.
(Like in our ai hotel chatbot example: checking the weather, checking prices and availability, live receptionist hand off, booking tours, sending confirmation emails, etc)