How data helped me conquer the Leadville Trail 100 MTB

…and how it can help airlines become advanced retailers

The tipping point

I’ve worked in the travel industry for more than 15 years, witnessing first-hand many ups and downs and supporting customers through critical technology projects. The turbulence of the COVID pandemic forced airlines to rethink how they run their business, but a silver lining is that they’ve been driven to innovate and reconsider how they balance risk and opportunity.

There’s a growing disconnect between what travelers want and what airlines are able to deliver in terms of the end-to-end travel experience – from shopping, booking and payment through to servicing. Airlines’ margins are being squeezed and consumers are increasingly underwhelmed with their travel industry experiences. 

A few years ago, the technology wasn’t yet available to deliver a solution that meant the juice (quantifiable benefits for both airlines and travelers) was worth the squeeze (largescale transformation). But the business case for a technology-led industry transformation that delivers a more traveler-friendly experience and makes commercial sense for airlines is now clear. We’ve arrived at the tipping point. For me, the keys to unlocking the travel experiences that today’s consumers demand are data and experimentation. They are the enablers for airlines to transform and become truly customer-centric.

Data

“Data by itself is useless. Data is only useful if you apply it.”

Todd Park, former Chief Technology Officer for the United States of America

Why do I use this example? Because airlines likely collect more data than any other supplier in the travel ecosystem. Capturing data in a timely fashion and storing it in a way that makes it useful is critical. But the real challenge for airlines is in analyzing that data, interpreting it and applying it in a meaningful way to anticipate the needs of customers and drive competitive advantage. This is where the latest advances in data capture, storage, analysis and application can really help – and are central to the offer and order solutions that my team is building at Sabre. As a business, we’ve already made big strides in this arena with our Beyond NDC and Retail Intelligence product suites, and there’s plenty more coming down the pipe.

Whenever I think about how data can support sustainable revenue-generating opportunities for airlines, I think in terms of maximizing conversion.

The latest technology we’re building – powered by Google Cloud’s BigQuery – enables customers to ingest, store, analyze and visualize vast quantities of data from a wide range of sources with ease. It then uses features like machine learning and business intelligence to algorithmically refine it down to create highly personalized and contextualized offers that maximize conversion. We’re using science to answer the question ‘what does this customer really want?’ – something that’s very difficult or impossible for airlines to do today.

For me, one of the most powerful ways to spotlight the potential that data holds to maximize conversion in an offer- and order-enabled retailing future is to use the simple analogy of a grocery store.

Today, using existing systems and processes governed by the PSS, airlines can make limited inferences about customers based on data held in the Passenger Name Record (PNR). I liken it to being able to see what’s in a customer’s grocery bags as they leave the store. You can learn about their preferences, perhaps check their receipt to see how they paid for their purchases and draw some conclusions based on that limited insight.

In the future, using Google Cloud’s BigQuery will be like following customers around the grocery store as they shop and connecting all aspects of their shopping behavior together. You’ll be able to understand why they’re going to the store in the first place, see where they go in the store, what they look at and in what order, what products they put in their shopping cart, what products they pick up and look at but put back on the shelf, what was on the shelves around the products they put in their cart that they decided not to buy, and so on.

In short, you can make a wider range of more accurate inferences based on these additional insights. And these data points gets captured as part of a continuous feedback loop and are used to ensure ‘offers’ become increasingly intelligent over time – optimizing conversion, maximizing margin and improving customer retention.

But this is only one part of the power that Google Cloud holds. In my next blog, I’ll switch focus and look at experimentation. For me, experimentation sits at the intersection of science and technology and it’s where things start to get really exciting. I’ll share my thoughts on the vital role it can play for airlines in becoming more customer-centric and meeting the needs of travelers in a modern retailing world.

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