Yet, there is now growing concern over just how such dynamics are engineered based on the data that is collected, analysed and utilised. To be sure, much of that data may well have been collected legitimately in the process of the exchange of goods, or in the name of potentially improved services. For instance, an internet retailer stores addresses and credit card details to simplify the checkout process. Or, the government tracks commuter and traffic patterns in order to improve a city’s infrastructure.
SINGAPORE (Apr 15): A year and a half ago, Tony Fernandes, CEO of the wildly successful low-cost carrier AirAsia, talked about data as “the new oil”, and revealed plans to use data and machine learning to customise the pricing of air tickets and ancillary services to individuals. “We begin to know what your tolerance level is for a certain ticket to a certain destination,” Fernandes said. Effectively, AirAsia would be able to monetise the information it has gathered from its half a billion customers. “We will charge you differently for baggage,” Fernandes adds.
You may or may not have noticed the difference in your holiday planning, but it would stand to reason that airline tickets and related services, as price-competitive products based on demand and supply, are suited to such “dynamic” pricing.
