The following is the actual lost customers category email list of this sample analysis data. What is the essence of lost user operations? Analyze how to build a user loss early warning system from three aspects The model case processing summary shows that 506 cases are censored. This figure represents the number of customers who have not yet lost, accounting for 72.3%. (1) Which dimensions will affect the loss of users What is the essence of lost user operations? Analyze category email list how to build a user loss early warning system from three aspects.
The final model calculates several impact indicators with strong category email list correlation, including address, occupation, calling card service, wireless network service, wired network service, telephone time, etc. The Exp(B) value for an address means that for customers residing at the same address, the annual churn risk is reduced by 100%−(100%×0.972)=2.8%. Customers who have lived category email list at the same address for two years have a 100% lower churn risk − (100% × 0.9722) = 5.5%. The Exp(B) value of the calling card.
Indicates that the risk ratio of churn for customers who do category email list not subscribe to the calling card service is 2.024 times that for customers who subscribe to the service. The Exp(B) value for the web service indicates that customers who do not subscribe to the web service have a churn risk ratio of 0.577 times that of customers who subscribe to the service. (2) Survival curve of the average customer Customer Survival Curve is a visualization of the model's category email list predicted churn time for the.