travel

We’re Still Traveling Like It’s 1996

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Editor’s note: John Balen has been involved in the venture capital and technology industries for more than 25 years. At Canaan he focuses on the digital media, enterprise and fintech sectors, and has led investments in Cardlytics, Stayful, SwitchflySilverRail TechnologiesUrbanSitter, Blurb, SOASTA and others.

Travel still provides some of the highest human anxieties of anything we do on a routine basis. There are countless variables when it comes to travel: weather, mechanical issues, overbooked flights, traffic, human delays and so much more. But if we could combine all of our intelligent data in a way that it works together, travel disruptions could be corrected automatically and efficiently.

Think about Google’s self-driving car and all of the random occurrences and variables it encounters on the road — and its ability to react and correct based on real-time information. Smart travel should not be so different.

Big Data Is in the Dark

This is the overarching problem with travel today: booking travel efficiently — and getting a good deal on it — is still very labor-based and lacking in transparency. Ultimately, there are hundreds (or thousands?) of customer-service agents on the other side of Expedia’s or Orbitz’s online booking portals, and if just one aspect of travel plans falls out of place, customers are forced to wait on hold to speak to a live person.

Not even the very first step of travel planning — the initial booking — is automated. And even still, it’s based on laborious manual research as we scour the Internet and review numerous different options for flights, hotels, rental cars, etc. Can we really trust booking services that tell us we’re getting the lowest possible price?

The discovery that Orbitz shows more expensive hotels to Mac users than to those browsing on PCs has only led to more time spent on trying to find the best deal and manually cross-referencing multiple sites. Thanks to economies of scale, big agencies can buy up better rates on hotel rooms, but as average consumers, you and I don’t have access to such deals — or to information about what the best prices really are.

The booking process hasn’t evolved nearly enough since the likes of Priceline and Travelocity came about in the mid-1990s, bringing the first revolution of online travel booking. We’ve grown light years in terms of gathering valuable data, but for most of us regular consumers, that useful big data is still in the dark.

It doesn’t have to be this way. Personal data and preferences exist in multiple scattered databases – what hotels I’ve stayed at, airlines I’ve flown, cities I’ve visited, the kinds of activities I like to do, where I like to eat, and even tasks that I need to complete before I travel (board the pets, have someone pick up mail, etc.)

Of course there is all that social data, too. Integrating my social graph into travel planning would allow me to see recommendations based on where friends or colleagues like to go. But these pieces of data haven’t been brought together in a single comprehensive system that actually knows my preferences, and knows how much I’m willing to pay for them.

In other words, various pieces of big data are still too compartmentalized. Right now, I have to rebuild my ideal travel experience, when really it should be pre-built for me based on my past patterns. I get recommendations the travel sites assume I want, rather than what it knows I want.

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Where Is the Amazon for Travel?

Everything you buy creates a signal. Amazon has used that data to tailor suggested products for each individual. But the travel industry as a whole has struggled to break out of its own silo and adopt a similar approach in order to better suit personal preferences. We have more data available to us than ever before, but so far nobody has managed to link it.

Sites like Kayak at least do some of the online legwork for us by showing multiple sites at once to compare prices. But no service goes far enough beyond price comparisons into knowing our full travel histories and being able to make recommendations based on past bookings and preferences.

To streamline the travel process — and overall industry — we need the travel supply chain to have a radical transformation, primarily around transparency and how big data is ultimately applied, in order to deliver targeted, personalized results for consumers. Like an Amazon, travel needs a booking service that tailors results based on previous preferences.

Early last year, British Airways made moves in the direction of personalized travel by announcing its “Know Me” program, designed to use Google images and social networks (or as many customers saw it, “stalk you on the Internet”) in order to bring customers better service once they arrive at the gate. While British Airways was clearly thinking about ways to use data to make travel more pleasant, this may not be the most useful application of data to travel. It’s more like a step up from the traditional loyalty programs rather than a solution to the problems of travel booking.

Time for Smart Travel To Take Off

Most of the pieces are ready to fall into place for big data-based travel to become a reality: a proliferation of smartphones — 1.4 billion by the end of the year — that can pull data from across services, apps and social networks; and the availability of real-time information on changing travel itineraries and pricing.

A few companies are already in a strong position to win the travel innovation game. Clearly Google is a force when it comes to data, and we should especially keep an eye on Google Now, one of the most interesting consumer-facing experiences of big data in action — and one that’s built for agile mobile experiences.

Google Now is starting to read your data across Gmail, Calendar and Maps (and maybe Waze soon?), to provide valuable information on where you need to be and what information may be relevant to you at the right time. Microsoft’s recently announced Cortana expands on Siri’s capabilities by trying to anticipate what mobile users want before they ask for it. While it is likely to struggle (much like Siri) in certain situations, it’s a step in the right direction and shows how big companies are starting to think.

One new startup that may be worth watching is Vamo, started by ex-Facebook engineer Art Steinberg. The service hasn’t launched yet, but it claims to solve the headaches of travel booking with a streamlined process built on big data. There are also a few companies tackling the issue of transparency in the hotel-booking space that are exploring the usefulness of big data in making reservations.

A new study by Amadeus IT Group, “At the Big Data Crossroads: turning towards a smarter travel experience,” is another encouraging sign that innovation is on the way, noting several case studies of hotels and travel services that are stepping up their analytics game. I look forward to the day when I can book a week-long trip to Paris through a travel bot that automatically gives me a window seat, books my hotel and makes a dinner reservation at my favorite restaurant in Montmartre. Big data can get us there.

Images by Flickr user Martin Burns under a CC BY 2.0 license and Flickr user Cameron Russell under a CC BY 2.0 license