Churn Prediction Analysis And Practical Research Of E-Commerce Platform

Compared with traditional offline shopping in the past,e-commerce is not limited by time and place,and its convenient advantages attract more and more people.However,in today's market environment where e-commerce platforms are flourishing,the competition among them is becoming increasingly fierce.E-commerce logistics has gradually become the only bottleneck in the development of e-commerce platforms,and logistics service quality,such as logistics distribution,has gradually become the most dissatisfied place for customers.For e-commerce platform customers,their behavior is more unstable and the loss rate is higher,and the stability of customers is directly related to the sales volume forecast of e-commerce,thus affecting the allocation of storage and the optimization of transportation,etc.,a series of problems related to logistics and enterprise cost.However,the logistics service quality of e-commerce platform itself is very likely to be a factor that cannot be ignored to cause customer loss.Therefore,it is an urgent problem for e-commerce platforms to explore the causes of customer loss,analyze the factors affecting customer loss and put forward countermeasures.It is also a measure to promote the development of modern logistics and improve the quality of logistics service.This paper first discusses the characteristics,market size and development prospects of e-commerce platform customers in China,and analyzes the factors that may affect the loss of e-commerce platform customers.Then it discusses how to use big data to build the early warning model and finds out the efficient and accurate algorithm.Then,based on the data of the maternal and infant business department under the big data platform of a well-known domestic e-commerce H company,using data mining technology and machine learning methods,such as random forest and xgboost algorithm,etc.According to the RFM model,the characteristic engineering of factors affecting customer churn is established,and the early warning model is further trained according to the previously established characteristic dimensions.Finally,based on the training model,the main reasons affecting customer behavior are obtained,and the factors that do not exist are found,and retention measures are proposed accordingly.The results show that the model has a high accuracy,and the main factors affecting customer loss of e-commerce platform in the maternal and infant market,such as customer loyalty,baby'age,customer satisfaction with logistics,are obtained from the model.Based on this,some constructive suggestions are put forward to help e-commerce enterprises develop personalized marketing measures for customer retention.The study of this paper is of great significance and reference value for e-commerce platforms to timely discover high-risk customer loss,further reflect on the shortcomings of the platform,and timely take measures to repair them,so as to improve corporate profits and expand their e-commerce market share.