Forecasting Airline Ticket Sales Conversion Rate

Our system provides comprehensive historical data regarding the display of flight offers, encompassing various parameters such as time, departure and arrival airports, number of stops, layover time, ticket class, number of passengers, and more. This data, combined with information on ticket purchases, serves as the foundation for building accurate machine learning models to predict the conversion rate of airline ticket sales.

General task: Developing a predictive system that identifies queries with the highest conversion rate. Additionally, the forecast system can be employed to identify queries that are unlikely to result in a purchase, thereby optimizing revenue by minimizing non-converting impressions.

Forecasting Air Ticket Price Fluctuations

Building upon the sales conversion forecasting system, we address the optimization problem of determining the optimal mark-up for air ticket prices, focusing on the concept of dynamic pricing.

General task: Establishing a system for predicting price margins on air tickets, with the aim of maximizing sales conversion and profitability.