The authors evaluate the usefulness of customer lifetime value (CLV) as a metric for customer selection and marketing resource allocation by developing a dynamic framework that enables managers to maintain or improve customer relationships proactively through marketing contacts across various channels and to maximize CLV simultaneously. The authors show that marketing contacts across various ch...

data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. one of the useful applications of data mining is segmentation. segmentation is an effective tool for managers to make right marketing strategies for right customer segments. in this study we have segmented retailers of a hygienic manufacture. nowadays all manufactures do understand that for sta...

The purpose of this study is to test s structural equation model which aims to explore the extent to which customer lifetime value (CLV) is impacted by customer perceptions of value, satisfaction, and loyalty. A series of examinations revealed that (1) customer value (CV) impacts customer satisfaction and loyalty directly and positively; (2) customer satisfaction is directly and positively rela...

Nowadays companies increasingly derive revenue from the creation and sustenance of long-term relationships with their customers. In such an environment, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the lifetime values of the company’s customers. A frequently-encountered difficulty for companies wishing to measure customer prof...

Valuing customers is a central issue for any commercial activity. The customer lifetime value (CLV) is the discounted value of the future profits that this customer yields to the company. In order to compute the CLV, one needs to predict the future number of transactions a customer will make and the profit of these transactions. With the Pareto/NBD model, the future number of transactions of a ...

This paper is about how to use data from a random sample of customer relationships to calculate an appropriate average Customer Lifetime Value (CLV). When the sample contains only completed relationships, the simple unweighted average is appropriate. When the sample contains a mix of active and completed relationships, the lifetimes of the active relationships are said to be right censored beca...

The more competition among industry participants severe, the more companies try to retain their customers and acquire new customers from their competitors. To gain competitive advantage, many companies are adopting and deploying more refined and sophisticated Customer Relationship Management systems. In the marketing area, a personalized marketing paradigm has already been infiltrated into our ...

Being able to measure customer value is a prerequisite for effective customer relationship management and data-driven marketing strategy, as it allows to maximize return on marketing investment, particularly when resources are limited. While past profitability is certainly a useful metric, it is insufficient when trying to predict which customers are going to be most valuable in the future so a...

The concept of customer lifetime value (CLV) is widely used by marketing practitioners and academics in making decisions about customer acquisition and retention spending. The traditional view of CLV, however, assumes that the firm has the unlimited capacity to serve all its acquired and retained customers. In this paper we consider a firm with limited capacity and determine the role that CLV p...

Pervasive application of data mining technology is very important in analytical CRM software development when the distributed data warehouse is constructed. We propose a multi-factor customer classification evaluation model CLV/CL/CC which comprehensively considers customer lifetime value, customer loyalty and customer credit. It classifies clients with synthetic data mining algorithms. In this...