Churn Analysis for an Iranian Mobile Operator Customers; Using Data Mining
Abstract
To avoid customer churn it is important for organizations to analyze their customers' behaviors and needs. In this paper attitudes leading to customer churn in a mobile operator are investigated. Logistic Regression Analysis is applied to analyze profile data of 3150 registered users of a mobile operator in Iran. Results show that customer complaint number, the extent of service use, and demographic characteristics of users are the most important factors affecting customer churn. Moreover, results of hierarchical regression analysis show that customer status (active or inactive) plays a mediating role between customer churn and customer profile.
عباس کرامتی
سید محسن سیدین اردبیلی
بابک سهرابی (1388). تحلیل رویگردانی مشتریان، بررسی وضعیت یکی از اپراتورهای تلفن همراه ایران با کمک روشهای دادهکاوی. سال 4 (شماره 14), 63-92 Abbas Keramati
S. Mohsen Seyedian Ardabili
Babak Sohrabi (2009). Churn Analysis for an Iranian Mobile Operator Customers; Using Data Mining. Volume 4 (Number 14), 63-92
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