Enhancing Customer Relationship Management by Integrating Customer and Product Values based on Clustering and Indexing Techniques
نویسندگان
چکیده
Customer relationship management is not only pure business, but also indicates strong personal bonding within people. Development of this type of bonding drives the business to new levels of success. Once this personal and emotional linkage is built, it is very easy for any organization to identify the actual needs of the customer and to help and serve them in a better way. It is a belief that if more sophisticated strategies are involved in implementing the customer relationship management, the business becomes stronger and fruitful. The main objective of this paper is to provide an optimal solution which optimizes the process of Customer Relationship Management. The process is primarily executed by means of the Clustering technique . When a new customer arrives, that customer is classified into any one of the existing Clusters which automatically provides us the properties of the customer. This paper
منابع مشابه
New Approach for Customer Clustering by Integrating the LRFM Model and Fuzzy Inference System
This study aimed at providing a systematic method to analyze the characteristics of customers’ purchasing behavior in order to improve the performance of customer relationship management system. For this purpose, the improved model of LRFM (including Length, Recency, Frequency, and Monetary indices) was utilized which is now a more common model than the basic RFM model apt for analyzing the cus...
متن کاملCustomer behavior mining based on RFM model to improve the customer relationship management
Companies’ managers are very enthusiastic to extract the hidden and valuable knowledge from their organization data. Data mining is a new and well-known technique, which can be implemented on customers data and discover the hidden knowledge and information from customers' behaviors. Organizations use data mining to improve their customer relationship management processes. In this paper R, F, an...
متن کاملIntegrating AHP and data mining for effective retailer segmentation based on retailer lifetime value
Data mining techniques have been used widely in the area of customer relationship management (CRM). In this study, we have applied data mining techniques to address a problem in business-to-business (B2B) setting. In a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. Segmentation is a useful tool for identifying groups...
متن کاملCustomer Behavior Mining Framework (CBMF) using clustering and classification techniques
The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features using k</em...
متن کاملGeneric Model for Customer Relationship Management Based on Back Propagation Algorithm
Data mining is most widely used in all fields because of its purposeful usage in the field where it is applied to. The techniques such as Clustering, Association rules and Classification take very important role in management. It is described that how these techniques are used to improve the customer relationship with the company which leads to a considerable profit. This paper deals with provi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015