Today, people are increasingly connected and extensively interact with each other using technology-enabled media. Hence, customers are more frequently exposed to social influence of other customers when making purchase decisions. However, established approaches for customer valuation most widely neglect network effects based on social influence leading to a misallocation of resources. Therefore...

Customer lifetime value (LTV) estimation involves two parts: the “survival” probabilities and profit margins. This article describes the estimation of those probabilities using discrete-time logistic hazard models and that of profit margins is based on linear regression. In the scenario when outliers are present among margins, we suggest applying robust regression with PROC ROBUSTREG.

T measurement of customer lifetime value is important because it is used as a metric in evaluating decisions in the context of customer relationship management. For a firm, it is important to form some expectations as to the lifetime value of each customer at the time a customer starts doing business with the firm, and at each purchase by the customer. In this paper, we use a hierarchical Bayes...

The present study attempts to establish a new framework to speculate customer lifetime value by a stochastic approach. In this research the customer lifetime value is considered as combination of customer’s present and future value. At first step of our desired model, it is essential to define customer groups based on their behavior similarities, and in second step a mechanism to count current ...

Acquiring and retaining the most profitable customers is a big concern of a telecommunication operator to perform more targeted marketing therefore business demand and competition between mobile operators is becoming more based on life cycle of customers in the network. In order to improve customer satisfaction and fulfill requirements, several data mining technologies can be used. Many researc...

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...

<span lang="EN-US">We proposed an approach of retailer segmentation using a hybrid swarm intelligence algorithm and recency frequency monetary (RFM)-location model to develop tailored marketing strategy for pharmacy industry distribution company. We used sales data plug it into MATLAB implement ant clustering K-means, then the results were analyzed RFM-location calculate each clusters’ cu...

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...