Using big data to boost travel efficiency

Marta Desviat

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It’s hard to determinate the enormous potential of big data for the travel industry as a whole. In 2013 it became the buzz word and we identified how it was about to transform rail travel, in our report ''At the Big Data Crossroads''.

The report findings: a smarter travel experience

Using Big Data to boost travel efficiency. Our 2013 report, ''At the Big Data Crossroads'', revealed that rail travel was set to become safer, more efficient and tailored to passenger preferences, thanks to the big data revolution, identifying three major areas impacted:

  • Safety: making train maintenance more timely and detecting problems before disruption thanks to onboard sensors and predictive analytics.
  • Customer service: aggregating customer data, the analytical insights lead to better marketing and customer service.
  • Data management: reducing cost, as the technology associated to manage big data is free or low-cost. 

The main challenge identified was for rail companies to develop an effective strategy, unlocking the potential of big data to enhance products and services and the end-to-end customer experience. Let's see how far the rail industry has gone with the use of big data. 

Big data today: train delays, something from the past

The major advancement we have identified is the railways' use of big data to avoid delays, forecast disruption and act before it happens. By adding sensors to the trains, it relays data back to the engineers about the condition of the locomotive’s parts and rail tracks.

  • The Swedish train operator Stockholmståg is an example of using a big data prediction model, which provides a view of the entire commuter train system two hours into the future.
  • Renfe, the Spanish rail network, is also a good example. Due to the high competition with air on the route connecting Madrid and Barcelona, they have partnered with Siemensto improve punctuality. Renfe guarantees train passengers a complete refund if the train is delayed by 15 minutes or more. The result? Only one of 2,300 journeys has been noticeably delayed in 2016. 

By combining big data and predictive maintenance, railways can find out what needs to be repaired before disruption happens, keeping travellers happy. 

Big data helping revenue collection

Additionally, big data is going one step further helping metropolitan transport systems: Los Angeles Metropolitan Transportation Authority announced last year a new analytics software, surveillance cameras and mobile phone validators as part of its fare enforcement strategy. The analytics software monitors activity at stations, highlighting behaviour that is out of the norm and alerts security personnel if a rider attempts to avoid paying a fare.

Big data, also for online travel agencies

Travel sellers can now benefit from big data, in particular online travel agencies. Knowing in advance what the customer wants, is now a reality. Combining big data with machine learning disciplines can predict booking trends, learning from the user data stored, and how this affects the booking process and time.

The data generated through smart devices represent for travel sellers an opportunity to improve customer service by better-knowing their preferences. 

Big data analytics, a pending matter

The travel industry generates a tremendous amount of data. Railways and travel sellers are in various stages of determining how to harness all that information to improve overall operations and customer satisfaction. Even though we have identified some advancements in the use of all this data, an analysis strategy still needs to be put in place.

Big Data analytics, for instance, will offer unprecedented insight into travellers’ behaviour, allowing rail companies to deliver a more intuitive customer experience. From offering ancillary services to providing recommendations about additional destinations to visit, there will be plenty of opportunities to improve the customer experience. As a result, the rail travel experience will become more personalised. 

How can big data transform rail travel? Find out more in our white paper

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