With its early use of online booking, the travel industry stands as one of the first successful adopters of digital marketing. But as tech’s effect on consumer behavior continues to evolve, so must the playbook by which companies operate. For travel companies, that means meeting customers’ rising expectations for assistance at every point of the purchase journey.
Today’s travelers are increasingly impulsive and want information quickly. A recent study that we conducted with Phocuswright suggests that more than 60% of U.S. travelers would consider an impulse trip based on a good hotel or flight deal.1 We see this trend reflected in our search data too. In the U.S., we’ve seen that travel-related searches for “today” and “tonight” on mobile have increased by 150% over the past two years.
“People don’t just want faster access to information—they want better, more personalized experiences,” said Oliver Heckmann, Google’s VP of engineering for travel and shopping. “If I were to pull out my phone and search for a nearby hotel or restaurant, I’d expect the information I find to be tailored to me based on my location, time of day, and maybe even past interests," he said.
The numbers show Heckmann is right: 57% of U.S. travelers feel that brands should tailor their information based on personal preferences or past behaviors. Furthermore, if a travel brand tailored its information and overall trip experience based on personal preferences or past behavior, 36% (over 1 in 3) would be likely to pay more for their services.2 He added: “Not only is there a strong appetite for more customized, meaningful experiences, but there’s a business case for travel companies to do more here.”
And here’s where machine learning and artificial intelligence (AI) factor into the picture. As we transition to a new era of computing with machine intelligence—equally significant to last decade’s move from desktops to mobile devices—machine learning unlocks new insights and opportunities for travel companies to deliver better, more useful experiences for users than ever before.
Automating marketing campaigns with consumer-intent signals such as purchase history and contextual relevance, coupled with customizing those experiences on the fly, is just one example of how companies will be able to use machine learning in more impactful ways moving forward.
“Travel and hospitality have always been about assisting and anticipating needs, and we’re barely scratching the surface in terms of how this technology can be used to simplify and streamline the entire consumer journey,” Heckmann said. “As an industry, we’re getting to a place where we can help travelers get whatever information they need about a new destination, flight, hotel or activity as quickly and easily as possible, with smarter recommendations that learn and evolve over time.”
Heckmann also pointed to the use of machine learning to make existing applications even better, like with Google Translate. “When we converted most of the Translate traffic to an AI-based system, we saw overnight gains in quality roughly equal to what the previous system had accrued in its entire lifetime. We still have a long way to go, but the friction in travel experiences makes it ripe for innovation and AI,” he said.
Voice and digital assistants will increase in importance
Other big topics in travel are voice and digital assistants, with our data informing that people are using their voice to find and discover information. In fact, almost 70% of requests that we see to the Google Assistant are expressed in natural language, meaning that people are getting more comfortable having conversations with computers. More specifically for travel, Heckmann noted that over 1 in 3 travelers across countries are interested in using digital assistants to research or book travel,3 and they’re already searching for everything from hotels to flights, and things to do in-destination.
“There is a tremendous opportunity for all of us to simplify and streamline the traveler journey with new technology. There’s a tendency for companies to chase (and build for) the next big thing, but I’d argue that these shifts emphasize how important it is to stay focused on the person behind the search, not the individual devices that they’re using,” Heckmann said. “Optimizing for the traveler will be even more important as people start to use more digital assistants across surfaces and speak in natural language.”
To keep up with the change, Heckmann said travel companies can get ahead by thinking user-first, embracing automated marketing opportunities, and experimenting with new platforms. Machine learning is already helping companies unlock new insights, better predict customer needs, and deliver more relevant experiences at scale.
“Our goal is to make sure that travelers have a great user experience when they come to Google for answers, and I see our role in the travel ecosystem as one that helps connect users to partners. Where we can help is in providing data and insights around traveler intent, identity, and context,” he said. “At the end of the day, it’s all about making people’s lives easier, and machine learning accelerates all of these opportunities to engage travelers at the right time and place.”
