Diagnostic analytics, Investigate the churn rate by building a model using available customer data and identifying signs of dissatisfaction., Descriptive analytics, Calculate churn rates and compare them in different quarters. Identify high-value customers based on recent purchase data., Prescriptive analytics, Streamline the implementation of strategies to reduce the churn rate, such as ranking customers based on churn propensity and customer value, in order to target high-value, high-risk customers for additional attention., Predictive analytics, Use a model to predict the likelihood of churn for each customer.

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