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The Churn Rate is the most relevant metric for analyzing customer retention and predicting customer churn. It measures the percentage of customers who leave your service during a given period. By analyzing churn rate patterns, you can identify the factors contributing to customer attrition and develop strategies to mitigate this loss. For predicting churn, focusing on customers who are likely to leave based on historical data and behavior is essential, making churn rate the most direct measure of customer retention. Why Other Options Are Wrong : A) Incorrect : Customer Lifetime Value (CLV) is important for understanding the long-term value of customers but does not directly measure churn or predict which customers will leave. C) Incorrect : The Net Promoter Score (NPS) measures customer satisfaction and loyalty but does not directly indicate which customers are likely to churn in the near future. D) Incorrect : Customer Acquisition Cost (CAC) tracks how much it costs to acquire a new customer, not the rate at which existing customers leave the service. E) Incorrect : Average Revenue Per User (ARPU) is useful for revenue analysis but does not provide direct insights into customer churn behavior.
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