The airline industry has become increasingly competitive over the last decades. Airlines strive to keep their cost structure as low as possible, while looking for new ways to increase their revenues. Achieving these goals requires getting the best possible understanding of passenger behaviour: collecting and analysing data about their customers is a critical factor for airlines to optimise their route network and develop new routes, differentiate their product, fine-tune ticket prices and maximise ancillary revenues.
Turning big data into actionable insights on airline passenger behaviour
In the past, the study of how passengers think, feel, and use products and services related to air travel was based on a limited number of data inputs, such as aggregated origin-destination flows, statistics on market demographics, passenger surveys, information on the prices paid for a given flight ticket, and data collected through customer loyalty programs. This situation is now changing: new digital technologies allow the collection of huge quantities of large-scale, fine-grained data along the various components of the passenger journey, enabling a much deeper understanding of passengers’ tastes and behaviour. Through the combination of travel journey analysis and predictive modelling, Nommon helps airlines make sense of these new data sources to predict market demand, optimise their network, analyse competition and complementarity with other transport modes, and maximise their revenue through more personalised offers.