Popular rail ticket booking app Trainline is starting to leverage its new cloud infrastructure and huge historic data set to deliver customers more personalised offers, including a new predictive pricing tool.
Since being acquired in January 2015 by private equity firm KKR, Trainline has been busy shifting to the cloud and building out its engineering and data science teams, to offer the kind of personalised shopping experience consumers expect in the age of Amazon and Expedia.
Speaking to Computerworld UK from their newly refurbished office in Holborn, London, Trainline's CTO Mark Holt explained how the company has finally admitted to being an ecommerce company, embracing the cloud and a DevOps culture to deliver regular changes to its user experience.
Armed with 15 years of search history and price data, the data scientists and data engineers at Trainline have been busy coming up with these smart features for its core consumer app.
"We have a massive amount of stuff in our labs, particularly around data innovation to create more customised, personalised experiences," Holt said. "We have both data scientists and data engineers that work in collaboration to make data available and then turn it into data product. So it is all very well coming up with an algorithm, but making it robust and reliable is a big part of that."
The aim of these projects is to increase a "mixture of conversion and attention", according to Holt, as the Trainline app acts as a popular information resource for hundreds of thousands of commuters every day, as well as a booking platform.
For example, a predictive pricing tool is due to be rolled out to UK app users this month. The tool allows travellers to look into the future and see when advance ticket prices are set to increase over time. This makes it easier to compare ticket prices across a range of dates, like Skyscanner or Expedia does with flights.
Jon Moore, chief product officer at Trainline said as part of the official press release: "Our data scientists have used historical pricing trends from billions of customer journey searches to predict when the price of an advance ticket will expire. We now share this information in our app to allow our customers to get the best price possible for their journey.
"We're introducing more advanced machine learning every day so naturally our predictions will get increasingly accurate. Our mission is to make train travel as simple as possible and price prediction is the first in a long line of predictive features we have planned to help customers save time and money."
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