Research And Application Of C Company’s Customer Segmentation Model Under The Optimal Allocation Of Supply Chain Resources

At present,the process of economic integration is accelerating,market competition is gradually increasing,and the imbalance between supply and demand of resources in supply chain enterprises has become increasingly prominent.For sustainable and stable development,how to grasp customer information and realize customer segmentation in the case of limited resources,so as to make the allocation of enterprise resources reasonable,has become the focus of current supply chain management.However,most of the existing supply chain resource matching model research starts from the perspective of resource demand,and pays less attention to the resource provider.Therefore,this paper studies the resource allocation of supply chain enterprises in combination with the characteristics of actual supply chain enterprises and the shortcomings of previous research.This paper takes C company as the research object,from the perspective of resource optimization allocation with the participation of supply chain resource providers and demanders,and uses the improved K-Means clustering to solve the problems of mismatch between supply and demand of supply chain resources and low customer satisfaction.Algorithms subdivide different customer groups,build a customer segmentation model for the purpose of optimizing the allocation of supply chain resources and improving customer satisfaction,and form a better matching plan for product resources and service resources,so as to optimize company C’s supply of goods and customer services,and realize resources Accurate matching from resource providers to demanders to solve product and service problems that reduce customer satisfaction.First of all,from the perspective of commercial enterprises,build a customer segmentation model under the supply of goods for the overall retail customers of C company.The "0-proportion" iterative allocation algorithm is proposed to improve the supply strategy based on customer grading,simulate the supply based on the real data of the C company’s system,and then verify the practical application value of the model through empirical research.Evaluating the effect of the supply of goods is reflected by the order fulfillment rate indicator that can reflect the tension between supply and demand.Then from the perspective of industrial enterprises,taking Zhenlong(Lingyun)as an example,a customer segmentation model under customer service is built for Zhenlong(Lingyun)retail customers.The customer value index is introduced to subdivide customers,and the Pareto rule is used to carry out the secondary subdivision of customer value,which is convenient to provide differentiated services to customers of different value categories,solve problems such as single service form,and optimize the allocation of service resources.Finally,through the empirical research of C company,the customer satisfaction before and after the improvement is compared,and the feasibility of the program is demonstrated.The research results show that the improved clustering algorithm has better performance;The supply of goods based on the customer segmentation model has an overall increase of 11.80%compared with manual delivery;the customer service based on the customer segmentation model improves the overall satisfaction of C company’s retail Customers.With a score of 1.19 points,the allocation of product resources and service resources in Company C’s supply chain has been optimized.To sum up,the research in this paper can provide a reference for the empirical research on the optimal allocation of resources in supply chain enterprises.