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How Data Can Overcome Commoditisation in Travel.
October 31, 2016 News big data Qlik Travel


Travel has become a commodity in many markets, making price the only differentiator but big data can help to differentiate offers and in many cases travel has become a commodity like sugar, oil or steel, where the product is mostly indistinguishable from competitors’ products and the primary way to differentiate offers is in the price.

Indeed, it is fair to say that today there is little difference between one low-cost flight and another, or between one mid-priced business hotel and another.

The pricing dilemma was a central theme at EyeforTravel’s recent flagship show in the US where there was a clear recognition that this approach is never going to be enough, and the only way to stand out is through digital and data innovation.

Clearly there is a challenge for travel vendors who rely on differentiating their product to maintain competitivity. So the big question is, how can suppliers create meaningful differentiation in their products to build customer loyalty while at the same time remain competitive on price? The answer to this challenge lies in the effective use of big data analysis.

“The only way to overcome commoditisation in the travel market is through personalisation and smarter use of big data,” says Carlos Sánchez, Senior Manager for Big Data Analytics and Product Innovation at the business travel agency Carlson Wagonlit Travel. “Suppliers need to understand who their customers are, where they are travelling, when and why. With this data they can work out what they need to do to make themselves stand apart from the competition.”

One way to make a standardised product look different is to wrap around it an experience so that it can be distinguished. While every ticket is essentially the same if you are looking at just the basic flying part, airlines are beginning to understand that they can improve the end-to-end experience by adding ancillary services. These services can include better functionality of mobile apps, offering simpler booking, quick check in and easy access to additional services like travel to the airport and related deals.

In the same way, even commodity-like hotels can enhance their experience with extra benefits like seamless check-in, app-based room keys, digital concierge services or a well-marketed bed. Premier Inn’s consistent approach and a ‘guarantee of a good night’s sleep’ on a mattress that you can even buy on the Premier Inn site is a good example.

So while the basic product is undifferentiated the customer perceives the overall experience as being a positively memorable. “Everything is geared to turning the trip into the best experience it can be, an experience that sticks in your mind so that you ask for the same supplier next time you travel,” says Sánchez.

What makes this much easier today is the increasing use of mobile devices by travellers, the availability of huge amounts of data from the customer base and accurate artificial intelligence algorithms that help identify ways to make business travel easier and more memorable.

How does this work in practice? CWT advises that travellers fill out their personal information so that the booking process can be automated as much as possible. Then using the CWT to Go app the company uses mobile app analytics from Mixpanel combined with the analysis and visualisation from Tableau Software.
Whatever the tools chosen, Sánchez recommends that business intelligence platforms for mobile should be based on four essential characteristics:

  • User-centric, event-based data model
  • Cross platform – covering native app, the mobile site and website
  • Real-time data collection, manipulation and raw data export at any scale
  • Data accessible through simple, easy-to-use tools that enable people to get answers to questions.

Sánchez argues that the combination of Mixpanel and Tableau is very effective but there are also other interesting solutions like Qlik, which creates ‘visualisations’ and ‘dashboards’ to help teams find the answers to data-driven questions.

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