Research on Optimization strategy of Customer Experience Management based on K-Means clustering algorithm
In recent years,the Chinese market has entered the era of stock game,and the demo-graphic dividend has turned into the popular dividend.The urgency of jointly promoting the it-erative upgrading of industries has become increasingly prominent,and the requirement for the service of thousands of people has become increasingly high.In order to solve this problem,a combination of K-Means clustering algorithm is proposed to achieve customer clustering to opti-mize customer experience management.Among them,k-Means clustering method can find out K clusters of different groups,and take the mean value contained in this group as the core of each group,also known as the K-Mean value.The clustering results can provide important basis for providing refined services and optimizing customer experience management for various types of customers in the future.Experiments have shown that customer clustering using K-Means clus-tering has higher accuracy and shorter time consumption than using other clustering algorithms
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