Supervised Machine Learning: Building Classification Models to Predict Airline Passenger Satisfaction
For businesses in different fields, customer satisfaction is one of the most important measurements to determine whether a product or a service meets customer expectations. Higher customer satisfaction leads to higher purchase intentions and custimer loyalty, which can be a strong indicator of business growth and revenue. If a customer is satisfied, they are more likely to come back for the product/service again and recommend it to other people. Considering the fact that acquiring a new customer can be 4 to 10 times more expensive than keeping an existing one (Kingwill, 2015), it is extremely important for businesses to find ways to increase customer satisfaction.
The above concept applies to airlines as well, and it explains the purpose of this project: help airlines understand what factors influence customer satisfaction and find ways to imporve passenger experience. The analysis result will help airlines to allocate their resources more effectively and maximize profitability.