Research On The Calculation Model Of Customer Lifetime Value

Information technology progress and the rapid development of Internet makes us into the information age. With the arrival of the era of enterprise business environment, earth-shaking changes happened. Customer relationship management (CRM) has become the focus of continuous and academic problems. CRM is the whole life cycle of customer, customer lifetime value of management CLV (CRM) is the focus on customer lifetime value, the evaluation and quantization is the whole life cycle of enterprise management decision is an important basis for from customers, through the calculation of the value of life, can guide enterprises segment, and on the basis of the marketing strategy formulation.Aiming at the importance of customer lifetime value in research and existing problems, this article mainly aims at e-commerce business customers to download the characteristics are studied, and use the concept of customer lifetime value, established considering many factors of Pareto/NBD probability model, mainly from the model and parameter, and management from four aspects of Suggestions were studied.Ⅰ. Model research. This can be used to identify customer characteristics of market segmentation and customer lifetime value customer value, especially the related problems are reviewed in this paper. On the basis of summarizing the customer lifetime value, the calculation model and parameter of seven ranks, found some problems in them. On the basis of introducing the multiple problems, influence factors, namely, dynamic and static double key variables in the previous research, on the basis of the Angle from multiple variables and establish a new Pareto/NBD probability model.Ⅱ. Parameters. In Pareto/NBD probability model is introduced, the static and dynamic two key elements. In consideration of static element was introduced in value of assets and sustain assets, and consider the attenuation and utility "problems" compounding, For dynamic index, in previous studies, and on the basis of introducing the brand effect as the key elements of the original index, only consider public effects and customer satisfaction, the modeling and its elements of brand and the relationship between customer satisfaction, and brand effect and linear relationship between public effects. Above the work in the existing literature haven’t appearedⅢ. Empirical research. Using a well-known B2C e-commerce sites to download the business and consumption data model in future, empirical studies on prediction of customer transactions, the model is proved for B2C e-commerce suitability of consumption, download the business through this model and the simple model of public effects considering a comparative study was performed to validate the model is more comprehensive advantages.Ⅳ. Management strategy. Based on the empirical analysis results of Pareto/NBD probability model in the B2C e-commerce sites download business application, and presents the corresponding marketing management advice.In previous job, customer lifetime value mixed forecasting model, and gives the specific customer lifetime value customer lifetime value mixed forecasting model method, and an empirical study of current customer lifetime, is worth and customer behavior prediction research contents of the rich.