Predicting firms' performances in customer complaint management using machine learning techniques
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing Ag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
With the globalization and more intense increasing competition, customer relationship management (CRM) is an important issue in today's business. In this manner, managing customer complaints which is a critical part of CRM presents firms with an is an opportunity to make long-lasting and profitable relationships with customers. In this context, the aim of this paper is to predict firms' performances in online customer complaint management using machine learning algorithms. This study utilizes data obtained from Turkey's largest and well-known third-party online complaint platform and employs three popular machine learning classifiers including decision tree (DT), random forests (RF) and support vector machines (SVM). The results show that the RF algorithm performed better in firms' performance prediction compared to other ML algorithms.
Açıklama
4th International Conference on Intelligent and Fuzzy Systems (INFUS) -- JUL 19-21, 2022 -- Bornova, TURKEY
Anahtar Kelimeler
Data mining, Machine learning, Business intelligence, CRM analytics, Data-driven CRM, Data Mining Techniques, Hybrid Approach, Industry, Churn
