Travel companies were the original data-driven marketers. By combining customer and transaction data they changed the targeting, timing, and distributing of the travel product and its promotional fares. These techniques, now called revenue management, and the loyalty programs that followed shortly thereafter, resulted in huge value for both travel companies and their customers. They instantly changed competitive landscapes as they provided huge economic (low fare, free seats and upgrades!) and emotional (thrill of expanded vacation travel options!) value to customers.
The fact is that while airlines and other players in the travel industry have demonstrated the value of understanding their customers by analyzing data to better serve them and improve business operations, the proliferation of new data sources requires a renewed focus for these firms to stay competitive. This article explains important techniques the industry has used to develop data-driven relationships with customers that deliver value. It also discusses ways to improve in the future because there are many challenges facing this competitive industry. The airlines and other large travel firms cited here are customers of my company.
First, the historic strengths of the industry start with revenue management and customer service.
Revenue management is used by travel companies to ensure customers benefit from the lowest possible prices and every inventory item (seat, car, hotel room) is optimally priced. The top U.S. airlines perform sophisticated analytics after receiving the daily advanced bookings data for flights, integrating historical booking trends and price data along with details about consumer preferences from individual customer bookings in near-real time. Airlines also evaluate continuing changes in supply and demand, from seasonal, competitive and capacity trends, and use price promotions to respond to market trends. Price promotions will always have a place in the travel business. With advanced analytics, some companies offer tactical, under-the-radar price promotions to make sure that any space available for sale is offered to customers that have a high propensity of taking the offers, without necessarily tipping off competitors on what they’re doing. Over time, as more behavioral data becomes available, airlines will create more personalized price offers and offer a wider range of prices to stimulate demand on the one hand and at the same time ensure seats are always available to last minute travelers.
Customer convenience and on-time flights. Over the decades, as competition in the airline industry intensified and flights filled up, airlines and other travel companies have focused on service issues with data-driven approaches. Siegel & Gale, in their 2013 Brand Simplicity Survey identify the top four issues that passengers find most challenging — and advanced airlines use data to tackle these:
1. Customers want to know they have the lowest prices. Travelocity has met this head-on with data, by monitoring daily changes in prices and sending customers a low-fare alert when prices fall below a certain threshold.
2. Travel plans made in advance often require changes and that can create anxiety for a customer. One airline noted for its customer friendly approach, captures data to make sure its customers can get their refund quickly when required.
3. Getting through security. Lufthansa realizes that while it cannot control lengthy security lines, it can control its own front counter. By using real-time data from multiple sources including its reservations and check-in systems it can predict the number of check-ins and luggage are due at its counters and when. The airline then ensures that the counter has enough staff so that customers do not get delayed before they get to security.
4. Addressing missed connections and anticipating problems. One major airline discovered that in spite of numerous real-time flight support systems, the impact on the customer, in terms of missed connections, was not visible without employees piecing together data from multiple systems. The company needed to develop a single definition of missed connections to create a trustworthy metric, and to measure subsequent improvement. And by making data available to employees, they raised the visibility of the problem and created the means for employees to solve the problem before it could happen.
Turbulence Ahead: A Storm of New Data Demands New Approaches
It’s clear that more data-driven changes are on the way. Travel companies are seeing a storm of new data sources – text data from flyer blogs, social media, Web clickstream data from new digital channels, geolocation and other mobile data and soon, a flurry of sensor data from RFID bag tags to those on airplane parts. With such volumes and types of new data, conventional techniques will no longer work; new approaches are required.
One technique growing in favor is called “discovery analytics.” For some time it has been a best practice for advanced companies to use sandboxes within their data warehouses, to rapidly explore new data for potential hot areas of benefits, as a means to prioritizing the integration of new data into the data warehouse. Shawn Clark, former director of security at Continental and then United Airlines and now head of an analytics consulting firm, has noted that security and IT functions can collaborate in a discovery process; in one case, he said, an airline “discovered” more than $250 million of fraud by proactively exploring every new data source as soon as it emerged. “The innovative power is not in development of new [fraud] profiles,” Clark says. “It lies in discovery of new clusters of fraud and bad business we haven’t thought of yet—identified during discovery and analysis. With each new data source and analytics deployment, our quiver of fraud and bad business profiles continues to grow.”
In today’s world, the new data sources encompass so much variety that new tools and architecture are needed to go beyond sandboxes. The benefits of discovery are likely to progress across the organization, from improved customer experience to higher aircraft reliability, including:
Customer experience and loyalty. Travel companies are fiercely competitive and price is critically important, but data from Hertz suggests that only 30 percent of customers may be driven by price alone; the remainders are looking for both price AND value — and willingly pay extra for selected services; about half of travel companies’ revenue is driven by loyalty programs. Leveraging information available on these customers is crucial. Travel service companies – from airlines to hotels to rental cars – have millions of interactions per month with customers after they purchase the service and before they travel. Each of these interactions can be turned into a service improvement and revenue opportunity. Companies like United Airlines are making substantial investments in value-added services such as various baggage services (for example, BagsVIP, delivered to your destination) or FareLock (to hold a fare for 3 to 7 days) that individually may have low uptake rates, but collectively have significant value to the customer and profitability for the airline. Predictive analytics is the key to selling such services. Even better is to decide what offer will be most relevant to the customer in real time, just when the customer engages with the travel company – an application of in-bound marketing. Recently, Hertz has implemented a range of services aimed at improving the customer experience, including its “carfirmation” service that sends email messages to customers about which car they should pick up.
Reliability and safety. Today’s newest jetliners have thousands of sensors that track metrics every minute of every flight. The risk of not having real time fleet mechanical health is readily evident: unexpected service requirements cause delays, congestion, cancellations and complex customer re-accommodation scenarios – made even more complicated by today’s high percent of seats filled. While most airlines currently perform monthly reliability trend monitoring of the most mission critical parts, today’s discovery analytics capabilities make it possible to monitor every replaceable part, every day, for adverse reliability trends. The impact is reduced spare parts needs, more flexibility in scheduling aircraft for repair and earlier capture of new problem trends and in the worst cases avoidance of a national story filled with months of poor publicity and notoriety.
The travel business has long been data-driven. While the seat, room and car are largely unchanged, the relative information generated on each asset has greatly expanded. Whereas 30 years ago, broad categorization of customers into business versus leisure fares was satisfactory, and more recently segmentation of customers into tiers of loyalty membership and status was satisfactory, the steady stream of new data sources is driving the industry towards a different relationship with customers. Personalized conversations with customers who are increasingly in control are reshaping the new marketing environment. Whereas in the past, actionable insights targeted aggregate data, now actionable insights have to be found and executed at the level of the individual customer. It’s a cumulatively dramatic effect, and one that places a premium on discovery analytics and new kinds of data-driven approaches.
Tim Simmons, vice president of Teradata industry marketing for retail, hospitality, travel and transportation, works with retailers in business intelligence, CRM and merchandise systems. He has spent his career in retail and CPG and has a particular focus on cross channel and touch point customer analytics as well as customer-centric merchandising solutions. Prior to joining Teradata, he held national account and brand positions at Gillette. He graduated from the Cox School of Business at Southern Methodist University with an Executive MBA in International Business.