Airline Customer Satisfaction Analysis Using Machine Leaning Methods

Abstract

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.

Keywords

• Customer satisfaction
• Airline industries
• Deep learning techniques
• Data analysis

Makine Öğrenme Yöntemleri Kullanarak Havayolu Müşteri Memnuniyeti Analizi

Abstract

Havayolu endüstrisi, küresel taşımacılığın önemli bir aktörü olarak, müşteri memnuniyetini sağlamak ve sürdürmek açısından büyük öneme sahip olan son derece rekabetçi bir pazarda faaliyet göstermektedir. Bu çalışma, dünyanın önde gelen havayolu şirketlerinden biri olan Türk Hava Yolları'na odaklanarak, sosyal medyada paylaşılan müşteri geri bildirimlerini analiz ederek rakiplerine kıyasla müşteri memnuniyetini değerlendirmeyi amaçlamaktadır. Çalışmanın temel amacı, hizmet odaklı havayolu endüstrisinde müşteri memnuniyetini önemli ölçüde etkileyen temel faktörleri belirlemek ve iyileştirme stratejileri önermektir. Müşteri verilerini ve sosyal medya üzerindeki geri bildirimleri analiz etmek için bazı yaygın makine öğrenmesi yöntemleri kullanılmıştır. Bulgular, uçak içi eğlence sisteminin bu havayolu için müşteri memnuniyetini etkileyen kritik bir faktör olduğunu ortaya koymaktadır. Özellikle, uçak içi eğlence sistemine yüksek puan veren müşterilerin genellikle 35-55 yaş aralığında olduğu, business class tercih ettikleri ve havayoluna sadakat gösterdikleri tespit edilmiştir. Bu doğrultuda, 35-55 yaş aralığında bulunan ve business class’ı tercih eden sadık müşterilerin genel olarak havayolu hizmetlerinden yüksek memnuniyet duyduğu sonucuna varılabilir. Bu analiz, uçak içi eğlence sisteminin önemini vurgulamanın yanı sıra, memnun müşterilerin demografik özellikleri ve tercihlerine dair önemli iç görüler sunmaktadır. Elde edilen bulgular doğrultusunda, Türk Hava Yolları, özellikle 35-55 yaş grubundaki ve business class’ı tercih eden sadık müşterilerine yönelik hizmetlerini stratejik olarak özelleştirebilir. Bu da belirlenen müşteri segmentine uygun hedeflenmiş iyileştirmeler ve girişimlerin yolunu açarak, havayolu endüstrisinin rekabetçi ortamında kalıcı müşteri memnuniyetinin sağlanmasına katkıda bulunacaktır.

Keywords

• Müşteri memnuniyeti
• Havayolu endüstrileri
• Derin öğrenme teknikleri
• Veri analizi

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