Dynamic Airline Discounts using an Evolutionary Subgroup Discovery Methodology

Historically, airlines around the globe have used static pricing structures, which are constrained to discrete price points and there is limited segmentation between their guests. Because of these limitations and constraints, the necessity of novel methods to calculate the willingness to pay and identify potential guests whose propensity to book a flight will increase if they receive a discount in order to improve their sales is huge. This paper proposes a novel methodology to identify interesting subgroups whose chance to book a flight increases if they receive an offer discount. This proposal includes a grammatically evolutionary feature selection algorithm to extract the best subgroups by analyzing the booking behaviour of historical passengers. A real case scenario was considered in the experimental analysis using private data from a commercial airline.