What does churn prediction aim to identify?

Churn prediction primarily focuses on identifying customers who are likely to stop using a product or service. This predictive analysis uses various data points and behavioral patterns to assess which customers might be at risk of leaving. By understanding the factors that contribute to churn, businesses can implement strategies to retain these customers, such as targeted marketing campaigns, personalized communication, or improvements in customer service.

On the other hand, new customer acquisition rates involve strategies to bring in new clients rather than focusing on existing ones. Identifying customers who will remain loyal indefinitely does not align with the practical aspects of churn prediction, as no model can guarantee customer loyalty without ongoing engagement and satisfaction. Finally, trends in market predictions focus more on broader industry changes and consumer behaviors rather than the specific behavior of individual customers regarding their likelihood to stop using a service. Thus, the primary aim of churn prediction centers on understanding the risk of customer attrition.