B2B Payments

Machine Learning Plays Mediator Between Corporates And Their Travelers

As business travel plays catchup to the consumer travel space and the technology deployed to improve the traveler experience, companies now enjoy a market saturated with choices for travel booking, expense management and traveler management.

Ongoing global economic improvement, coupled with stable and improving airfares, means companies are spending big on travel. Businesses spent $1.26 trillion on travel in 2016 alone, according to Global Business Travel Association (GBTA) figures released earlier this year.

As that spend value increases, Advito, a corporate travel advisory firm, predicts a pretty steady year for corporate travel in 2018. But what isn’t steady, says Bob Brindley, vice president and principal of Advito, is the pace of technological change impacting the sector.

In its 2018 Industry Forecast report, released earlier this month, Advito pointed to machine learning and artificial intelligence (AI) as a particularly disruptive tool that is helping corporates meet traveler demands while saving money.

“Early attention has focused on the use of machine learning to enhance and analyze data about traveler behavior,” Advito said in its report, pointing to chatbots as a particularly popular focus. “The real opportunity for the travel industry may lie in something less visible and potentially more impactful. Machine learning can be applied to spot entirely new opportunities to make savings and take some of the stress out of travel.”

One of the clearest ways this trend has presented itself is via mobile applications, Brindley recently told PYMNTS.

“Based on past behavior, the apps are adjusting responses and searches they come back with,” he explained. “Machine learning algorithms are built in to fine-tune customized displays and cut through the complexity of looking at different travel options.”

It’s a mirror image of what’s going on in consumer travel, too.

“Travelers are using these services in their leisure travel, and they expect the same kind of service and level of customization in the corporate space as well,” the executive noted, adding that both current and emerging corporate travel service providers are now hustling to integrate machine learning capabilities for a better customer experience.

But all of this technology presents an even greater opportunity in the corporate space. While business travelers demand convenience, corporates themselves demand affordable travel and efficient expense management — and those two demands don’t always work together. Machine learning, Brindley explained, could help companies achieve both.

“There is an increased amount of available data on the market today that can be applied to analytics to identify new opportunities,” he said. Brindley pointed to forecasting technologies that use machine learning to be able to predict pricing models and fluctuations of corporate travel, which could help companies ensure employees secure the travel vendors they want while also obtaining a better price for the corporation.

Using machine learning in behavioral economies could also help the corporation gain better insight into business travel behavior, spend patterns and beyond, another initiative in the broader effort to ensure traveler satisfaction while maintaining compliance and saving the company money.

“There is this conflicting dichotomy between corporate objectives and corporate traveler objectives,” said Brindley. “Corporates have duty of care requirements. They’re trying to fulfill travel requirements at the lowest reasonable cost. The traveler is looking at convenience instead of pure cost. It’s not that one is right and one is wrong, but they are two distinctly different objectives.”

Historically, companies have hoped to address this issue by implementing rigid corporate travel policies that strictly outline how corporate travelers can plan and pay for their trips. But Brindley noted that the pace of change in corporate travel, like quickly fluctuating air fares, make these rigid policies no longer effective and, in some cases, unable to meet the objectives of either side.

As machine learning and AI become ubiquitous technologies among corporate travel service providers, the corporate clients of these solutions may be wise to take note and implement some of the benefits of the technologies into their own operations to save money.

“Machine learning really helps facilitate that process by providing more options to the traveler and helping them sort through all of those options,” explained Brindley, “as well as building in analytics to turn static travel policies into dynamic policies and building an incentive component that works for both the company and the traveler.”

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