Data Science - Helping consumers to save money and travel for less

Wednesday, September 27, 2017

Data Science - Helping consumers to save money and travel for less

Have you ever purchased a train or plane ticket online? If so, you will know how hundreds of different website display different prices. Also, you will be aware that prices fluctuate, generally increasing the later they are booked. So when is the best time to book? Can Big Data give us the answers?

Obviously, train operators and airlines do not want to inform people of when their prices are set to increase. They predict when demand will be high and inflate prices accordingly - the higher the predicted demand, the higher the price. If they were to release insights into their price change schedule, it would alter consumer behavior. People will rush to buy tickets before inevitable price increases and in turn save money.


Helping you to save money
Figure 1: Helping you to save money






 
An independent train ticket seller, The Trainline, believes it has solved the pricing mystery through the power of Big Data. As a massive corporation operating primarily in the United Kingdom, they have access to billions of past data points relating to train ticket prices and demand fluctuations. Now they are in a position where they can accurately predict when prices are due to increase. On their mobile app, there is a feature known as the "Price Prediction Tool" and it will show a user when a journey is likely to sell out and how the price will change depending on the booking date. They also claim that the system will become increasingly accurate as time passes and their data bank grows (however, they believe the current system will still save users on average 6% on the price of advanced tickets). It will learn from all future searches, benefitting consumers in the long run. In addition to aiding users to save money, The Trainline has also manipulated its data to make journeys more comfortable for their clients. They are doing this by suggesting areas of the train which are likely to have empty seats based on previous data information.

This is an incredible example of how Big Data has been used to help consumers, but is there any more potential to explore in this industry? In theory, any large comparison site has the power to manipulate its data for the benefit of its consumers.

Helping you to save on your next holiday
Figure 2: Helping you to save on your next holiday










  
Let´s take the example of Skyscanner, a site which provides comparisons on plane ticket prices. The aim of Skyscanner is to display the lowest possible price to consumers and the inclusion of Big Data analysis will surely aid this. Skyscanner has already conducted some basic research into its potential. A tool on their website informs users of the best time to book but it is extremely limited; with only 10 departure airport locations (all situated in the UK) and only 19 destination airports (presumably the most popular destinations with the largest amount of data). This tool certainly has space for innovation and development. Firstly, as more data is collected, they could display information for more routes. In addition, it is currently separate from the flight search tool; a coming together of these two would result in a more informative consumer experience.

It is clear to see that the world of Big Data is growing and here at LUCA we will always strive to be at the forefront of innovation. It is only a matter of time before more companies unlock their true potential with Big Data. Businesses will take advantage of the information to maximize their revenues but as discussed, consumers will benefit from the increased ease of operation. Big Data is the future of business.

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