Research On Customer Churn Prediction Of Airline A

In recent years,the rapid development of high-speed railway and the large number of airlines,the aviation industry is facing the great competitive pressure from internal and external,so the churn of customers has become a major problem.Customers are the most important resource for an airline,but the volume of customers is finite.Therefore,the competition between airlines mainly show as contending for customer resources and customer value.This paper takes Airlines A as object,and researches the problem of customer churn.Through the value analysis and churn prediction of the customer,the paper finds out the churned customers in Airlines A and identifies the value of each customer,so as to help the company to find out the most worthy of retention customers.Firstly,the customer value analysis model was established based on LRFMC.K-means clustering was used to divide customers into three categories,and then the value of each customer group is compared to identify the highest value of each customer group.Finally,based on the results of customer churn prediction and value analysis,we find out the high-value but churned customers of Airlines A,which is the most worthwhile customers.Secondly,the paper uses the C5.0 algorithm to build a customer churn prediction model for Airlines A.The results show that the accuracy and predictability of the model are very good,which can better identify the customer churn status and find out the characteristics of churned customer.The results of this research will help Airlines A optimize its resource allocation.It guides Airlines A to use the finite resources on most valuable customers and improve the churn problem by implementing suitable measures.