Customer Classification-Based Pre-sale Multi-value-chain Collaborative Mechanism Verification

Abstract

During the automobile pre-sale service, understanding customer preferences and segmenting customer purchasing power can provide a foundation for automobile dealers’ vehicle allocation strategy to manufacturers. It can improve the service ability of dealers and increase marketing revenue. This paper comes up with a verification method based on customer segmentation for multi-value-chain collaborative mechanism. First, we studied the process and inner accounting mechanism of the automobile marketing value chain and production value chain. We can explore the value-added of customer segmentation in each value chain and examine the extent to which customer segmentation results affect the value-added. Then, we construct a colored Petri net model for the value chain of each accounting unit. The sales service is mapped to transition. The sales resource management department is mapped to the place. The sales resource is mapped to the Token in the place. And we simulate the value-added process of the automobile marketing value chain and production value chain. Finally, we offer differentiated sales service processes for different categories of customers based on customer segmentation and design a multi-value-chain collaborative mechanism. On the CPN Tools simulation platform, we simulate the value-added quantitative effects in multi-value-chain collaborative state. We verified the correctness of the collaborative mechanism. In the simulation experiment, we monitored the number of automobile sales, the number of backlogs. The simulation result shows that the multi-value-chain collaborative mechanism based on customer segmentation designed in this paper can effectively increase the number of automobile sales by dealers and manufacturers. It provides a quantifiable basis for the optimization solutions of multi-value-chain.