How AI & Machine Learning is Improving the Summer Traveling Experience

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As we head into Memorial Day Weekend, we’re only days away from the unofficial start of the busy summer travel season. In fact, according to AAA more than 39 million Americans will travel 50 miles or more from home this upcoming Memorial Day Weekend.

Given our expertise in the travel and hospitality sectors, we wanted to take a look at how two of the biggest trends in technology (Artificial Intelligence and Machine Learning) are helping airlines, hotels, cruise lines and other travel services better serve their customers this summer.

Simply speaking, Artificial Intelligence (AI) is the computer-driven ability to perceive environments and take actions to maximize chances of achieving a goal. Machine learning can fit under that broad definition with the best examples displaying an ability for software to learn without needing to be programmed to do so.

While we believe better human interactions assisted by this technology is the future of the travel industry, there are all types of applications popping up across the hospitality landscape.

Improving Destination Discovery

Wherever a summer traveler’s ultimate destination is, the first step in his or her journey takes place long before they board a plane, walk into a hotel room, or step onto the sand. The trip truly begins at the planning phase.

Today, much of that planning takes place on a mobile device. Google notes that 40 percent of total travel traffic comes through mobile visits. So it’s not surprising that Google’s latest foray into the travel industry with Google Trips combines both mobile and AI.

The Google Trips app makes it easy to discover all types of destinations and sightseeing activities as you plan your vacation by analyzing popular searches and your own interests. In addition, its intelligent data gathering ability automates the process of getting all of your travel information in one place. For instance, if train, flight or bus tickets are sent to your Gmail account, Trips can parse those out and bring information into the app to give you a full overview of your travels.

Discovery can also be improved on the backend with machine learning to ensure that travelers aren’t confused by the locations or lodging they are stumbling across. For instance, Kayak uses machine learning to ensure there are not duplicate listings in travelers’ search results.

Facebook could also be a new entrant on the discovery side of the trip planning process. The “DeepText” AI engine it launched last year can actually take meaning out of what you post or message to your friends on Facebook Messenger. By analyzing this information in real-time, Facebook can connect you with friends or others that may be able to help you plan trips based on their own experiences – or maybe even your own travel agent chatbot (more on that in a second).

Streamlining Booking & Customer Service

Once upon a time, booking a trip meant making a call to a travel agent—often someone with whom the customer had previously interacted and forged a personal connection with. But today, the digital evolution of the travel sector has pushed most travel sales and service into impersonal digital and contact center interactions. Luckily, new data-driven processes can inject some much needed personalization back into these customer interactions.

The team at Mattersight has been working with hotels, airlines, cruise lines and travel booking services to do just that. For instance, our speech analytics system helped Hilton Hotels and Resorts ensure that their contact center representatives are coached to help customers in the right way.

Traveling is a highly emotional experience. Our platform focuses on quantifying the emotion and personality that comes across during phone interactions and using that data to predict outcomes, ensuring for a brand like Hilton that their customers are happier by the time they hang up. These kind of predictive analytics in the contact center have also driven a 6 percent increase in bookings for a major airline, as well as a 10 percent increase in bookings for a cruise line travel service.

This is just one example of how AI and machine learning is improving the booking process and elevating customer service for travelers. Another interesting area is chatbots, which have become an increasingly popular way for travel and hospitality companies to quickly respond to basic customer questions. Booking.com, for instance, launched a chatbot to connect hotels and travelers ahead of last summer’s travel season.

Icelandair took things a step further in launching its own Facebook chatbot with the ability to promote free stopovers in Iceland to warm leads. If you use the chatbot to plan your trip from U.S. destinations to Europe it acts as your travel agent for planning the trip through Icelandair, while ensuring dates are available for a free stopover in Iceland.

Kayak’s original co-founder, Paul English, is also taking the chatbot approach to booking and travel customer service with his newest startup, Lola. Lola’s approach is somewhat similar to the Mattersight approach in the contact center — creating better agents for business travelers with a successful combination of human handling and AI.

In the future, machine learning may even be able to predict the travel mode desired by potential travelers before they even begin to book their next trip.

Dynamic Pricing and Better On-Site Experience

Last, but certainly not least, AI and machine learning can drastically improve the on-site experience for travelers, ensuring that their stay is enjoyable and worth every penny.

One early use on this side of the equation is evident in dynamic pricing. Machine learning can be used to analyze the demand for flights and hotels in real time. This allows hotels and airlines to avoid downtimes with low bookings and capitalize on busy times. Customers, on the other hand, can avoid paying the going market rate for a less than average experience, while discovering deals that provide real value along the way.

Future on-site usage in the travel industry could automate sentiment analysis of guest reviews to suggest improvements that can be made to improve the overall guest experience.

Creating a positive customer experience is the foundation of every successful travel company. The AI and machine learning evolution of the travel industry is improving experiences and travelers will just start to reap the benefits of more enjoyable vacations guided by technology this summer. Furthermore, hotels, airlines, and other travel focused businesses that smartly harness data to create better connections with travelers will position themselves for market leadership — creating happy travelers and loyal, lifelong customers along the way.

Republished with author's permission from original post.

Marcel Korst
Marcel Korst is VP of Product Marketing & CX Strategy at Mattersight where he leads product evangelization, analyst relations, competitive positioning and customer marketing. Prior to Mattersight, Korst spent 13 years at Microsoft, most recently as Director of Marketing & PR for Worldwide Customer Service & Support, where he led brand, product marketing, demand generation, marketing automation, PR and analyst relations.

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