Customer Value Analysis Method Based on Automotive Multi-value-Chain Collaboration

From the view point of the automotive multi-value-chain in collaborative businesses, different customers will produce unequal values in the future services. To strive for the continuous contribution of high-value customers, and optimize the collaborative business efficiency in parts supplier value chain and service multi-value-chain, in this paper, we will mention a customer analysis method for service multi-value-chain in automotive industry. Firstly, according to the related data in our automotive service collaborative business platform, we selected some evaluation indicators to describe the customer’s current value and potential value. Then, a customer value analysis model was offered based on a multi-classification SVM, which would give a classification recommendation according to the potential value of customs. Finally, we randomly selected 40 customers’ 36 months related information from our platform, to verify our method by some experiments. The experimental result shows that the customer classification was close to the actual situation. Among the 40 testing samples, the accuracy rate of customer value classification reaches to 87.5%. The results of customer value forecasts can be used to guide parts supplier and service providers to make a more effective policy, such as giving specific offers for outstanding customers. It will expand the synergy of multi-value-chain outside the Three-guarantee period of serving period of automobile service, and realize the strategic management of service life cycle centered on customer value.