The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis

Yıl 2022, Cilt: 26 Sayı: 3, 530 - 544, 30.06.2022

Handan Donat , Saliha Karadayı Usta

https://doi.org/10.16984/saufenbilder.1077229

Cited By: 1

Öz

Today's rising cutting-edge technology requirements and competitive environment in telecommunication industry has gained a remarkable importance due to the COVID-19 pandemics in terms of high need of information sharing and remote communication necessity. Telecommunication companies conduct significant analyses by highlighting that the customer data is the most valuable information. Besides, they obtain results emphasizing that acquiring new customers is costlier than retaining the existing ones. Therefore, the companies are willing to determine the important customer features in order to understand why they shift to the other telecommunication service providers. Hence, this study aims to conduct a churn analysis by feature selection approach with large volumes of telecommunication customer data in order to present what kind of customer behaviors and qualifications exist. Since there is a huge amount of data in this field, data mining is a vital requirement. The performance outputs were observed, and the features carrying these outputs to the highest value were identified. The data collection and analysis were carried out in mid-2019, and the same data collection and analysis were carried out again at the beginning of 2021, and these before and after results were compared. In addition, a comparison was made with the results obtained by the other churn analysis studies. This paper contributes to the practitioners by presenting the most important customer features in telecom customer churn, and a new approach in performance evaluation have been proposed specific to the telecommunication market with the industry experts’ guidance as a theoretical contribution.

Anahtar Kelimeler

telecommunication, customer churn, churn analysis, data mining, machine learning

Kaynakça

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