5 years ago

What every marketer needs to know about Big Data in the travel industry

NB: This is a guest article by Jim Sterne, founder of the eMetrics Summit, president of the Digital Analytics Association and author of the book Social Media Metrics.

Big Data. There’s no escaping it. It’s catchy. It’s generic enough that everybody is using it for everything. It’s a one-size-fits-all phrase. Right?

It’s so all-encompassing that the best definition I’ve seen recently is from Stephane Hamel, director of strategic services at Cardinal Path, who put it this way:

“The simplest definition of big data is it doesn’t fit in Excel.”

So with Big Data on everybody’s lips, here’s all you (the marketing executive) need to know to keep up your end of the conversation.

1. Disk drives got cheaper so we can store more data

The ways and means of collecting all sorts of data have proliferated faster than Twitter traffic or security lines at the airport. We have more of data, more types of data, and it’s coming at us faster (real time) than ever dreamed possible.

That’s what makes up “volume, variety, velocity.”

So, the ability to replace big disk drives with many smaller, cheaper drives that we can wire together is the first, significant technical advance.

2. We can split up the processing

The second advance is the ability to augment the great big processors with many smaller, cheaper servers. We have distributed the processing to the data instead of waiting for the data to rocket back and forth from disk farm to processor.

So what?

So, there are three things to keep in mind when your marketing budget is being allocated to what seems like pure IT projects:

  • The more data you throw into the pot, the more likely you are of finding some sort of relationship (correlation) to act on.
  • This practice of splitting up the data, solving smaller problems, and bringing it back together is very useful for some specific types of processing. Getting thisunder your belt gives you voting rights when discussing options.
  • Big analytics processors are very good at finding hidden pieces in a hurry. (Show me all the customers who have bought in the past three months after clicking on these special offers and abandoning their shopping carts.)

But those types of questions are known unknowns. You know the things you’re going to ask and the entire database is set up that way.

You know you’ll want to see things by date, by region, by product line, etc.

That is what gives these enterprise data warehouses their power: they are designed in advance to answer the questions you know you might ask, and they can answer them very quickly so you can refine your questions – as long as you have deep knowledge about what data you have and how it is structured in the database.

But the other data – the messy data – is chock-full of unknown unknowns. We know the information might be valuable, but we don’t know what to ask.

Help on the way

MapReduce is a low-cost storage medium for unstructured data and for refining that data into a more structured form for heavy analysis.

Social media data, call center transcripts, clickstream data, website content, and sensor data all start out unstructured.

MapReduce is ideal for pre-processing text, turning all those tweets into numerical models of opinion (sentiment analysis), which can then be fed to the big analytics machines for correlation discovery and problem solving.

It’s great for asking slower questions of larger amounts of data. It’s great for finding a representative sample of data so the big processors don’t have to juggle all of the bits at once.

NB: This is a guest article by Jim Sterne, founder of the eMetrics Summit, president of the Digital Analytics Association and author of the book Social Media Metrics.

NB2: Global data image via Shutterstock.

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  1. Jim Sterne

    Well, you’re ALL right.

    You can’t make a splendid gourmet meal for 100 until you’ve learned to peel a potato and boil an egg. Companies who haven’t gotten their minds around little data have no business worrying themselves about Big Data. But they should know what it is, and that’s the intent of the article.

    Privacy is another matter altogether and one that I believe can only be done properly with incremental opt-in.- something I wrote about here: http://www.clickz.com/clickz/column/2173262/incremental-opt-privacy

    Both of these issues are part of the conversation we have at the eMetrics Summit http://www.eMetrics.org – and there’s another one coming up in London on 27 & 28 November.

    Hope to see some of you there.

  2. Steve

    Interesting comments!

    Almost every travel company I’ve worked for or with has had data coming out of its ears and has also been pretty damn good at processing it and using it for insight into customer trends, booking patterns, preferences and for informing their own contracting and purchasing strategy.

    Who are these travel companies who don’t understand the value of the masses of data their reservation systems, analytics tools, CRM tools, contracting databases etc collect?

    I work with companies in the finance world a lot as well, and in my experience travel co’s are much, much better at utilising their data in an insightful way.

    Notice I didn’t say big? That’s because data has always been big and travel co’s have always had some of the biggest…

    • jonathan meiri

      @Steve from a consumer point of view, you’d expect all that data to result in a more personal experience. If you take a common use case, say flight search, the standard experience goes as follows.

      (1) a user goes to Kayak to search for a flight
      (2) Books the flight on an OTA
      (3) Possibly sticks around and books a hotel
      (4) Finally receives a confirmation booking from the airline with ticket info

      Throughout that process virtually non of it is personalized. Yes all the players can tell you their exact page views, uniques, conversion numbers, revenue etc…but virtually nothing about a particular user going through the funnel.

      The user may enter their FF number and then the airline might know something about their previous travels with that airline, but that is about it. 95% of searches, on the meta search level are anonymous.

      Sure there is a ton of data buried in many of the travel co’s systems yet by and large the most users are left with a commoditized experience.

      • Stephen Thair (@TheOpsMgr)

        @jonathan – the problem is that “personalisation” depends on context – knowing who the user is by some form of authentication or tracking.

        And whilst people like Janrain (http://janrain.com/solutions/) are trying to solve that user context with social login conversely we have Do-Not-Track and other privacy initiatives trying to stop the very mechanisms that make personalisation possible (particularly if you want a cross-website aka “federated” user experience).

        That said, the increasing number of travel-related API’s (as seen in the Tnooz hack events) makes some of this more of a reality, assuming that you have that “who am I and what do I like” user context.

        • jonathan meiri

          @steve I agree context and user profile are key. The privacy issues are legitimate, but the issue is really about trust. Users have been shown to share some information if (and only if) they feel it will provide real value and not be shared carelessly.

          I personally am not a big fan of federated experience, especially on mobile.

          I wasn’t planning to mention Superfly.com, my company but we do in fact have both user profile (who am I) and user intent (what I want to do).

          It’s a long road but I think we agree that data will be key 🙂

  3. Jonathan Meiri

    @ Jim what the on line travel industry needs is not big data, but rather little data, or maybe any data. Consumers are underserved because the airlines and other travel providers have no idea what they are worth.

    Data can be used to understand where I’ve been, what my preferences are what I’m worth. Then tailor offers that are best suited for me. You don’t need much more than what the average agent already knows about me – my travel profile and preferences to start with.

    Before going gangbuster on collecting and parallel processing terabytes of data, how about start with helping me book my favorite hotel in NY. Makes sense?

    • Daniele Beccari


      you’re right on the spot, and I have a specific example.
      I booked a one-day trip to Dublin some time ago.
      The airline kindly sent me all kind of offers for hotels.

      And no it’s not Ryanair.

  4. Kevin Trill

    interesting article, anyone interested in this have a look at http://www.boxever.com/, new company dealing with Airline Big Data. By the way I don’t work for the company!

  5. Rosie

    This is interesting. We found in our research in the travel space that a lot of travel businesses are intrigued by big data but few have truly actioned it. A lot of others found the term quite a “hype” word, and were more interested in getting to the depths of company wide data and analytics strategies for NOW. Ie, day to day business tips to actually action better predictions, forecasting and planning, also things like social media ROI.


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