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This research question focuses on understanding the drivers of customer churn (i.e., when customers stop using a service) in the telecommunications sector. By analyzing customer behavior, usage patterns, and service data, data scientists can identify factors that most significantly influence churn. The use of machine learning models, such as logistic regression, decision trees, or random forests, can be employed to predict churn rates based on historical data, enabling companies to take preventive measures to retain customers.

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