sajjad shokohyar; ali rezaeian; amir boroufar
Volume 20, Issue 4 , January 2017, , Pages 65-94
Abstract
Interaction of companies with customers in the form of customer relationship management has changed significantly. Identifying characteristics of different customers and allocating resources to them according to their value to the firm has become one of the main concerns in customer relationship management. ...
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Interaction of companies with customers in the form of customer relationship management has changed significantly. Identifying characteristics of different customers and allocating resources to them according to their value to the firm has become one of the main concerns in customer relationship management. The purpose of this paper is to provide an appropriate model for customer segmentation based on some of the most important financial and demographics characteristics influencing factors of customer lifetime value (CLV). The process proposed in this study was performed in Saman insurance company. After determining RFM model indices, which include date, frequency and monetary of purchase, AHP method used for weighting them among 180000 customers. The optimal number of clusters based on the silhouette and impact of RFM indicators was done by using Two-step algorithm and then customers classified through K-Means clustering algorithm. Results provided a platform to analyze the characteristics of customers in three main sections. Also, by prioritizing clusters based on the RFM indices, valuable customers were identified. Finally, some suggestions were presented to the company to improve its customer relationship management system.
Adel Azar; Seyed Hamid Khodadad Hosseini; Mohammad Safari Kahreh
Volume 18, Issue 4 , January 2015, , Pages 87-110
Abstract
The more a marketing paradigm evolves, the more long-term relationship with customers gains its importance. Nowadays, most of corporations and firms in the world, including manufacturers and servicers, increasingly gain their incomes and profits through constructing and maintaining long-term relationships ...
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The more a marketing paradigm evolves, the more long-term relationship with customers gains its importance. Nowadays, most of corporations and firms in the world, including manufacturers and servicers, increasingly gain their incomes and profits through constructing and maintaining long-term relationships with the customers. The move towards a customer-centered approach to marketing, coupled with the increasingavailability of customer transaction data, has led to an interest in understanding and estimatingcustomer lifetime value (CLV). Furthermore, as marketing endeavors to be more accountable, the need of tools and models for measuring and evaluating efforts and investments that accomplish in marketing extent, is felt. The purpose of this research is CLV analysis for customer segmentation and profitability management. This dissertation we proposes a model for CLV measurement in banking industry. Our case study is one of the branches of Iranian Melli Bank. For this purpose, we selected savings (loan) accounts for 4 years, (from 2005 to 2008), in order to run our model. The study sample included 10,000 customers picked up among the accounts. After calculating the CLV of customers, we segmented the customers based on the calculated CLV. For customer segmentation, we used Clustering technique. This conceptual model is a new approach in customer segmentation context. More Customer Profitability Management based on segmented customer sections will be explained. Based on the models explained in this dissertation programs and methods will be proposed for each of introduced segments.
