Airline Customer Satisfaction Analysis Using Machine Leaning Methods

The airline industry, a major player in global transportation, operates in a fiercely competitive market where ensuring and maintaining customer satisfaction are of essential importance. This study focuses on Turkish Airlines, one of the leading airline companies in the world, aiming to assess its customer satisfaction relative to competitors by analyzing customer feedback on social media. The primary objective is to identify the key factors significantly impacting customer satisfaction in the service-oriented airline industry and propose strategies for improvement. Some well-known machine learning methods are employed to analyze customer data and feedback on social medias. The findings highlight that in-flight entertainment is a crucial factor influencing customer satisfaction for this airline. Notably, customers who highly rate in-flight entertainment tend to be in the 35-55 age range, prefer business class, and demonstrate loyalty. Consequently, it can be inferred that loyal customers within the 35-55 age range, opting for business class, generally express high satisfaction with airline services. This analysis not only underscores the importance of in-flight entertainment but also provides insights into the demographic characteristics and preferences of satisfied customers. Based on these findings, Turkish Airlines can strategically customize its services to better cater to the specific needs of its loyal clientele within the 35-55 age group, particularly those who prefer business class. This paves the way for targeted enhancements and initiatives that align with the identified customer segment, fostering enduring satisfaction in the competitive landscape of the airline industry.