Modeling Organizational Customer Lifetime Value Under B2B Situation

Customer relationship management (CRM) theory caters to the change and development of global economic marketing environment so much that it has drew more and more attention of enterprises, it also becomes one of the most effective ways for company to stand out from the crowd, so most companies has take the theory into consideration when making marketing strategies.Organizational customer is an important part of all the customers, the premise of organizational customer’s marketing management is the recognition of high value organizational customers, only by doing this can limited resources not wasted. In this paper, during the modeling of organizational customer lifetime value, the following aspects of work was made:First, through the literature study, a generalization of concept related to customer lifetime value was made. Trading scene was classified into three kinds, including compact trading scene, half-compact trading scene and non-compact trading scene, classifying the customer behavior (including purchasing behavior and churning behavior) into discrete and continuous, and explained the reason of using probability model rather than the regression model to modeling organizational customer lifetime value.Second, through literature study about modeling individual customer lifetime value, generalized the commonly used probability distribution to describe customer’s purchasing behavior, churning behavior and heterogeneity between customers, and analyzed the reason of using the distribution.Finally, by comparing the difference of organizational customer and individual customer, this paper selected the SBG model as the foundation to model organizational customer lifetime, according to the changing amplitude of trading volume, organizational customers can be classified into high fluctuate risk customers and low fluctuate rick customers, for customers with low fluctuate risk, SBG model can do the work, for customers with high fluctuate risk, this paper introduced the concept of recession risk, in,For volatility risk higher customer, introducing the concept of recession risk, In this paper, we assume that the probability of a customer to extend the contract is closely related to the trend of his trading volume, this paper has quantized the trend, and using the quantized value to make the model with it. In the model application part, this paper used one of the three Beijing telecom operator’s revenue data from November 2010 to November 2011, the result turned out convictive...