British Airways is one of the world's most renowned airlines. They provide quality service and flights to their passengers. One of the things that make British Airways stand out is their great customer service. They have provided customers with excellent service for more than a century. In fact, they have been voted the 'Best Airline in the World' by Skytrax for the past eleven years in a row! With their excellent customer service, luxurious seats, delicious food, and great destinations, it is no wonder that so many people fly with British Airways each year. Today, we are going to review the BA airline to help you decide whether to fly with them or not. We'll look at their service, flights, destinations, lounge and more!
This project is a part of the Data Science virtual internship program offered by Forage with British Airways.
The virtual Internship is divided into two main tasks: Web scraping to gain company insights and Predicting customer buying behaviour
Task 1 - Web scraping to gain company insights Customers who book a flight with BA will experience many interaction points with the BA brand. Understanding a customer's feelings, needs, and feedback is crucial for any business, including BA.
This first task is focused on scraping and collecting customer feedback and reviewing data from a third-party source and analysing this data to present any insights you may uncover.
Customer review data for British Airways was collected from Syntrax.
Task 2 - Predicting customer buying behaviour Customers are more empowered than ever because they have access to a wealth of information at their fingertips. This is one of the reasons the buying cycle is very different to what it used to be. Today, if you’re hoping that a customer purchases your flights or holidays as they come into the airport, you’ve already lost! Being reactive in this situation is not ideal; airlines must be proactive in order to acquire customers before they embark on their holiday.
This task involves building a high quality predictive to predict the successful bookings using customer bookings data.
