Is price a significant predictor of the churn behavior during the global pandemic? A predictive modeling on the telecom industry

The recent pandemic has affected the world in many aspects including, communication. Telecom and internet-based communication have witnessed a drastic upsurge due to lockdown and consequent work-from-home situation, being termed as the new normal. Due to the low switching costs and stiff competition, telecom service providers are struggling hard to attract new customers and prevent the existing ones from switching to rival telecom service providers. Hence this study is undertaken with an aim to discover the key factors in the order of their relative worth that could be focused upon by the telecom companies to prevent their customers from churning. For the study, linear discriminant analysis was applied on the collected dataset to predict the customers’ churn behavior. It was found that tariff rates for domestic calls and the number of calls made to the customer service were the significant predictors of the customer churn behavior.