No one has the ability to capture and analyze data from the future — however, there is a way to predict the future using data from the past. It’s called predictive analytics and more and more businesses are doing it every day.
In fact, you are probably doing it too – in one form or another. Ever made a forecast of next quarter’s revenue based on historical booking data? Used marketing reports to determine which tactics drive the most profitable sales? Increased or decreased inventory based on seasonal trends? All of these are forms of predictive analytics as they use past data to predict future results. Over here in the travel industry we use predictive analytics a LOT — and here’s why…
To Prepare for the Future, Observe the Present and Analyze the Past
Remember People Express? If you’re under 40, chances are you may not. People Express was one of the first low cost airlines and it launched – in 1981 – with a unique pricing model: All of its tickets were sold at one low price. Unfortunately for People Express, they were competing with the likes of American Airlines who – with the support of sophisticated computing technology and years of prior booking data – set prices dynamically in an effort to extract the maximum yield for every seat they sold. This was one of the earliest instances of a large travel brand employing sophisticated predictive analytics and it gave American a significant leg up on its competitors for years to come … and left People Express to be quietly absorbed by Continental in 1987.
What American learned early on was that to make predictions about what customers will do in the future, you need to have relevant data on their past behavior and the tools with which to curate and activate it. Fast forward 30 years and today’s American – armed with recent advances in big data computing – can crunch reams of data (demographic, geographic, search, purchase and loyalty, to name a few) to derive the perfect product (vacation destination, hotel recommendation, or simply optimal flight routes) for each one of its millions of customers within milliseconds.
From a traveler’s point of view, here’s how that might look: Say you’re traveling to Dubai for a three-day conference and you’ve decided to stay the weekend for some sightseeing. You start by searching for flights into Dubai on Wednesday and out early Monday via your favorite OTA (Online Travel Agency).
Well, thanks to the magic of predictive analytics, you might receive an exclusive offer from your favorite airline (the one you fly most often) for the ideal route (you tend to fly late morning and like non-stops) along with an option to include a hotel (where you have a loyalty account) and a convertible at a significant discount (from a brand you’re not familiar with but desperately wants you to be). Oh, and perhaps a few thoughts on the best restaurants in Dubai for someone traveling on an expense account … or a free pass to shred the only indoor ski mountain in the world … or a twilight offer to play Arabian Ranches Golf Course.
How is this possible? Because travel companies – and the big data specialists who help them – are getting better and better at divining the needs of their customers based on prior booking patterns. In the not too distant future this might look like a scene out of StarTrek: “Computer, book flights, accommodations and entertainment for me during the Big Travel Show in Dubai.” Welcome to warp drive!
Keep an Eye on Travel Trends – Old and New
Until that day, we’ll have to continue parsing data in less automated ways. Trends reports like this one – based on hundreds of millions of travel data points – can help by confirming intuitive patterns and identifying emerging ones. For example, comparing the top travel destinations from last summer to the trending ones for this summer illustrates that most of the same destinations find their way to the top of the list.
But they can also highlight unexpected blips, like the fact that Iceland has crept onto the list of most popular European summer hot spots. Or that geo-political events (like Western sanctions and falling oil prices which tanked the ruble) can significantly impact outbound (where are the Russians?) and inbound (here come the Chinese!) travel patterns around the world.
Discoveries like these have important implications for travel companies as they inform marketing strategies to align products, pricing and promotion with anticipated customer demand in an effort to maximize profitability.
First Party Data + Third Party Data = Magic
Good thing for the travel industry it has never been one to lack data – in fact, quite the opposite. Airlines, hotels, car rental and cruise companies have all been generating data sets too large for conventional applications for decades. The difference now is that storage capacity, data mining and analytics tools are far more powerful and increasingly affordable. Add to that specialized data companies that have emerged to help brands make sense of their own data – and cross-reference it against other (third-party) data sets – and you have a truly powerful recipe for predictive analytics.
Let’s say you are a small, independent hotel that considers someone who stays with you three times a year a “loyal” customer. But what if that customer actually travels to your city 10 times a year and stays with a competitor the other seven times? Still loyal? By combining your data (e.g. CRM records) with other relevant data sets (e.g. airline booking activity to your city) you can draw a more complete picture of your customer which in turn enables you to customize sales and marketing activity to gain greater market share of that customer.
Predicting the Unpredictable
Even if you’re already doing all of this, don’t rest on your laurels. Predictive analytics is an evolving science, constantly morphing with better tools and advanced technology so you’ll need to stay on top of the latest advancements to maintain your competitive advantage. And don’t forget there’s always room for good old common sense. At the moment it’s pretty tough to explain an Icelandic volcano to a predictive model…or a coup in Egypt…or an Ebola scare in Africa.
In travel, predictive analytics brings the dual promise of greater yield for suppliers (air, car, cruise, hotel companies) and at the same time a greater travel experiences for their customers.
Beam me up, Scotty!
Mark Rabe is CEO of Sojern.