Most of us love travel and staying home the past months has us dreaming of hitting the road again and experiencing a new place or revisiting a piece of beloved geography. With the adoption of artificial intelligence (AI) across industries, new services are also emerging, changing the travel experience. Before you plan your next trip, read on to learn more about how artificial intelligence can help and might shape your next big vacation. 

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Recommendations based on data of past searches or purchases have become relatively commonplace. AI algorithms employ machine learning to “learn” preferences based on past behavior and make future predictions. Travel sites employ this technology too and are using it to help make recommendations on hotels, rentals cars, activities, and so forth based on the data they’ve collected from their consumers. 

Beyond recommending a good restaurant, a turtle-watching tour, machine learning algorithms can also suggest when to book a flight based on past prices and seasonal fluctuations.  KAYAK’s website uses this technology and explains it the following way: “Our scientists develop these flight price trend forecasts using algorithms and mathematical models. Predictions based on past history can never be perfect, so we can't guarantee they'll be correct, which is why we also let you know the confidence of the statistical analysis.” Analyzing over a billion requests for travel information on KAYAK's websites and mobile apps every year, is a tremendous effort. This is where machines come into play to help sift and sort through such massive quantities of data to give relevant statistics that enable flight price predictions.

Personal Travel Assistants

With fully-automated online bookings dominating the travel and tourism industry, “smart” travel assistants have become popular and even an expected feature on most platforms. Chatbots have learned to field complex customer questions through machine learning algorithms that teach the bots how to find the information the customers are seeking.  Airlines, rental car agencies, and other tourism organizations use chatbots to quickly answer client queries and assist with finding travel information. 

Google has an app called SARA- Your personal Travel Assistant that will summarize your entire trip, can handle online check-ins, store documents, personalize travel information such as weather, and even send a message to your host letting them know your arrival time.  

Voice-activated devices such as Alexa offer kits to integrate voice assistants with outside services such as travel websites. Kayak skill is one such service that allows users to track flights, book accommodations and explore travel options all with the power of voice. 

Personalization

A recent study found that 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations. The travel industry is no exception. Airlines are customizing their services to their clients in the hopes that customers will remain loyal to their brand. Subsequently, they are developing apps that help clients with their booking, boarding, meal selection, rewards programs, and flight information. The personal touches go a long way. 

Air Canada’s app has everything from purchasing or viewing plane tickets to entire vacations and even cargo functions. Even better, it also allows you to watch movies from the app on Air Canada Rouge flights. 

United Airlines uses data from its customers and more than 150 variables to create customer segmentation and reactive UX that responds in real-time with a customized web experience based on the user’s segment. The airline unveiled the new site in 2018, “Each one of our customers is unique and has different needs for his or her travel, and personalizing our digital offerings is just another step toward giving our customers the experience and the products that they ask for,” said Digital Products and Analytics VP Praveen Sharma on the airline’s website. According to data, this personalized approach has already increased United’s year-over-year ancillary revenue by about 15 percent.

Saving With Predictive Pricing 

There are many apps and websites that offer price predictions for airline flights that use the help of AI and algorithms for predictive analysis. With advice on when to book, these platforms take some of the pricing guesswork out for travelers. There are even more savings to be had for those with flexible dates— and again this is due in large part to the work of AI. Hopper is one such example. Users can enter a destination and the platform will use years of past data to generate a calendar for the entire year with dates that have color-coded pricing.  Possibly the best feature is the platform’s price predictor, which shows information about the price of a flight such as when it will rise and by how much.  This technology lets travelers decide whether to book a flight now or wait until later. 

Airlines are not the only travel industry players to use machine learning for predictive analysis. Hotels are also using this technology to set pricing for their properties. By analyzing a user’s data alongside other relevant factors like weather, time of year, hotel capacity in the past, and so on, a hotel can adjust the price of its rooms to create a higher level of conversions. Offering fluctuating and adjustable pricing is one way that hotel websites are staying competitive.

In 2015, Starwood Hotels developed a predictive analytics tool. The hotel chain spent more than $50 million over several years to create what it calls a revenue optimization system (ROS). The system is capable of functioning automatically, and choosing the best pricing based on data points and user information, but is overseen by a human director of revenue management (DORM) who can adjust rates. 

AI and Travel: Parting Thoughts

Artificial Intelligence is a broad swath of fast-growing technology shaping the way we conduct our travel plans and spend our vacations. From recommendation services to “smart” personal assistants to predictive pricing, data is being used to optimize experiences for consumers, help them save money and simultaneously drive profits for the travel and tourism industry. 

 

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KEY TAKEAWAYS

  1. The travel industry is applying machine learning algorithms to make recommendations based on clients’ previous behavior and to use chatbots as personal travel assistants for users.
  2. Companies, particularly airlines, are customizing their services to their clients in the hopes that customers will remain loyal to their brand.
  3. Apps and websites that offer price predictions for airline flights with the use of AI and algorithms for predictive analysis to help travelers save money.

 

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