Case Study


Unlocking the Secrets of Domestic Flight Pricing: An Analysis of Historical Prices and Future Trends

Domestic air travel is a crucial part of modern transportation infrastructure, but fluctuations in flight prices can significantly impact both consumer behavior and industry profitability. Therefore, our client wanted to understand the factors that influence flight prices and forecasting future pricing trends which has become an important area of research.

Resources Assigned
Project Type

Consulting Firm



Project Completion

The Problem

This project aims to analyze historical domestic flight prices to identify patterns and trends, and develop a predictive model for forecasting future prices. The goal was to provide insights into the drivers of domestic flight pricing and inform decisions for airlines, travelers, and policymakers.

The Solution

To achieve the project’s goal of analyzing historical domestic flight prices and developing a predictive model for future prices, we used statistical analysis techniques to identify patterns and trends in the data. We also used machine learning algorithms to develop a predictive model that can accurately forecast future prices based on historical data and other relevant factors. The model was tested and refined using cross-validation techniques to ensure accuracy and reliability. Finally, we presented our findings in a clear and concise manner, along with recommendations for airlines, travelers on how to use this information to make more informed decisions.

The Impact we created

An analysis of historical domestic flight prices and a predictive model for future prices could improve pricing strategies for current and upcoming airlines, hence helping travelers save money on airfare, and inform policymakers in supporting the growth of the domestic airline industry.