How data analytics enhances the experience of air travel

Company providing in-flight entertainment technology uses AI and machine learning to help airlines improve services.

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Anyone who's ever traveled on an airplane knows that some experiences have been more pleasant than others. One of the facets of air travel designed to enhance passenger experience is in-flight entertainment and internet access, and a company that provides these systems, Gogo Air, is relying on data analytics and machine learning to make ongoing improvements in the service.

Gogo Air is using a suite of Adobe Analytics tools including Virtual Analyst, a machine learning data analysis tool, to glean insights into customer experience for a number of its major airlines customers.

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The company is a partner of more than 17 of the world's largest airlines, delivering insights that help the airlines enhance passenger experience and better understand travelers' in-flight needs. Through its work with Adobe Analytics, Gogo Air has been able to provide new context and information on user behavior, sparking two major airlines to redesign the strategy of their in-flight entertainment systems.

"Ultimately, we were driven to [advanced analytics] to better serve our partners, many of which were strong advocates of delivering a superior customer experience," said Jeremy Linhardt, Gogo Air's ecommerce and Web analytics manager.

The airlines are hungry for insights into how their customers are enjoying -- or not enjoying -- their experience, Linhardt said. "Our ability to glean those insights through the use of such a sophisticated analytics tool was one of the core drivers of our decision to work with Adobe," he said.

Gogo provides in-flight entertainment and Wi-Fi service to passengers, and by doing so, gathers information about passengers using the services. It applies analytics to the data, taking complex and massive data sets of passenger interactions to churn out insights that help airlines improve experiences and in some cases even offer more targeted products to passengers.

"We're able to answer many of the key questions airlines have about their passengers," Linhardt said. "What products are they interested in inflight? What devices do they use while traveling? How long do they like to surf [the Web] or be entertained during the flight? What entertainment options are they looking for -- seatbacks, personal devices, movies, TV shows, music, ebooks?"

The analytics platform allows Gogo to build custom projects and share dashboards throughout the company. "This makes everyone in our organization data-driven and keeps everyone focused on the passenger experience," Linhardt said.

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Gogo's airline customers have leveraged the technology to test a number of tactics. These include building awareness by increasing the merchandising and advertising of entertainment products on popular, non-entertainment specific pages such as the inflight gateway's home page; and increasing title merchandising effectiveness through title placement, content curating, and interfaces that make it easier for passengers to find titles.

They're also looking into personalization based on situational context, for example, by customizing inflight gateways based on the length of the flight, the device the passenger uses, the availability of seatback devices on the aircraft, and the flight's destination city.

Machine learning and AI have advanced the analytics process and simplified it to the point where it's more easily accessible and user friendly, Linhardt says.

"Advancements in sharing and visualization have also brought insights to non-technical employees," Linhardt said. "Before, so much of this work had to be accomplished with data scientists and database administrators, reports were complex and still required further explanation. Now, companies like ours benefit from templates, drag and drop visualizations, innovations in mobility, and more. It's frictionless and allows us to be data-driven in every decision."

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