Business Technology

Wednesday 15 August 2018

How big data and AI are driving the travel industry down the right track

Stock image PA
Stock image PA
Louise Kelly

Louise Kelly

Disruptive technologies such as IoT, AI, robotics and blockchain are all hitting their critical inflection point at the same time, forcing industries to re-write their own value chains.

Digital transformation for the travel industry, specifically, has faced resistance, but is on the cusp of an entire revolution that will touch on every phase of the customer experience.

For digital rail platform Trainline, they've become market leaders in collating and creating a vast data pool from which they are using to create customer-facing innovations to make the travel experience smarter and as seamless as possible.

"Our main focus is to drive value from the data that our users give us either on the app or on the websites," Fergus Weldon, Head of Data Science at Trainline told Independent.ie.

Fergus Weldon
Fergus Weldon

"From a customer perspective they need to research the trains that they are going to get on and to do that they need to search online. So every time somebody searches on our platform, we can see all the journeys that you searched for and the information that you got back.

"You see that for every user, which is about 6-7 million searches a day, tens of billions a year, and that provides a large foundation for a lot of the recommendation work that we do and a lot of the price prediction."

First created in 1997, Trainline now boasts around 600 employees across its main offices which are based in London, Paris and Edinburgh.

The digital transformation and service expansion was really apparent from the late 2000s and has been ongoing for the last decade.

From Ticket Alert, allowing notifications of advance (and cheaper) tickets for specific trips, and Best Fare Finder in 2008, the company then launched a basic app in 2009 which allowed for ticket purchasing the following year. 

More recently, an AI-based tool BusyBot was introduced so that data submitted by the app users can be used to predict where there will be free seats in train carriages.

"We asked customers if their train was delayed or on time, if they got a seat or not, where they were based on the train. So then we could build this feature where customers are best informed where they might be able to get on; what part of the platform to stand at, what carriage might have free space," said Fergus.

"It's all about educating the customer, through the use of their own data, and providing a better end-to-end service experience."

Price is obviously a huge pain point for travellers and Fergus said that their Price Prediction tool can "stop people paying more for the tickets that they could have bought previously". 

Trainline's strapline states that 'buying in advance could save you up to 43pc' but this latest data-led offering could shave off more.

"Prices rise quite steeply, especially as you get close to the day that you're due to travel. But, from a consumer perspective, they don't really understand that. In a large part, we're trying to educate people that they should be buying their ticket earlier," he said.

"Travelling by rain is more economical better for the environment. We want to be able to build the features to encourage that and facilitate a better service for customers end-to-end."

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