The travel industry has always included digital technology to improve services. Travel is becoming enjoyable and simpler with the rapid advancement of technology. The latest successful examples are Airbnb and Uber.
The potential of machine language is public knowledge today. The travel industry is not the first to introduce machine learning. We, therefore, can examine old successful examples to assess their applications and expectations in detail.
Here are five of the ways machine learning is changing the travel industry.
1. Customer Support
Response speed is key to customers in the travel industry. AI tools can help streamline customer support processes. In a recent survey, the tools were found to improve efficiency with excellent results. For example, what makes an experienced customer support professional between 15 to 20 minutes took under one minute for an AI tool to complete.
To build trust and loyalty, it is necessary to combine human staff with the virtual assistants. Speed is not the only thing required in a business with customer relations. Physical interaction is of vital importance because it provides confidence to the customers. A passenger who lost a bag would be confident when they report to a human assistant who uses the virtual tool to find it in the shortest time.
2. Intelligent Travel Assistants
For a long time, travel bookings have been the focus of heavy automation and digitization. Most travel companies around the globe in both developed and third-world countries have automated bookings.
AI introduces intelligent programs that are trained to perform specific tasks on a traveler’s request. Today, there are 4 million monthly active users in chatbots. The chatbots are an efficient and enjoyable way to build strong customer relations.
The technology has been used before in the hospitality industry. With 24/7 mobile support, human staff help to facilitate the processes. Large travel companies such as Hipmunk and Kayak have successfully installed the technology.
They are used as mobile travel companions to solve several problems. For example, they provide answers to issues such as knowing the nearest business lounge, baggage allowance, gate numbers, and how long it takes to the airport.
3. Optimized Disruption Management
Automated disruption management helps to resolve actual problems that emerge in the way. It has been used successfully on the corporate level. Since disruption management addresses time-sensitivity. It requires instant responses to arising issues. There are numerous possibilities that may cause delays or cancellation of flights.
The disruptions may cause huge inconveniences. For example, you may be stranded in Europe at odd hours of the night when you need to arrive in Tokyo in time for timely meetings. This could lead to huge losses.
It is now possible to predict disruptions. This knowledge helps travelers mitigate the loss prior to the incident. For example, the 4site tool has successfully enhanced efficiency of enterprise travel. Apart from travelers, the tool also serves travel management firms by giving real-time management solutions.
4. Offers for Most Valuable Customers
The loyalty of customers is essential to travel companies. They help retain customers to help the business grow consistently. AI-based personalization helps to boost loyalty programs.
Members of loyalty programs are the most valuable customers. The travel industry needs to identify these clients, and this is why machine learning is critical.
Providing tailored offers for different types of unregistered users helps to track their behavior. With the information, it is easy to make predictions based on the patterns of their travel behavior. This historical data helps make accurate forecasts that retain customers. They help reduce the chances of churn.
5. Facial recognition
Scrutiny of travel documents at every entry point by different authorities can be exhausting. Of course, it is necessary for security purposes, but the process can be enhanced to save on travelers’ time. Artificial intelligence coupled with blockchain allows storage of travelers’ data for easy identification in airports, restaurants, and entertainment facilities.
Introduction of Artificial Intelligence is the latest development. It is the third major phase of revolutionizing the travel industry. It is used to predict destination choices, customize services, book, and make post-trip assessments.
References:
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
