Customer Relationship Management Systems: The Application of Fuzzy ART Neural Network

2002 ◽  
pp. 78-100 ◽  
Author(s):  
Sungjune Park ◽  
Nallan C. Suresh
Keyword(s):  
Neural Network ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Management Systems ◽  
Fuzzy Art

scholarly journals Prediction of customer behaviour through datamining assets

2009 ◽  
Vol 57 (3) ◽  
pp. 43-54
Author(s):  
Naděžda Chalupová
Keyword(s):  
Neural Network ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Marketing Strategies ◽  
Customer Relationship ◽  
Business Managers ◽  
Correct Decision ◽  
Commercial Success ◽  
Customer Behaviour ◽  
Managerial Decisions

Business managers accounting for commercial success or non-success of the organization have to gain knowledge needful for correct decision acceptance. These knowledge represent sophisticated information hidden in enterprise data. One possibility, how to extract mentioned knowledge from data, is to use so-called datamining assets.The paper deals with an application of chosen basic methods of knowledge discovering in da­ta­ba­ses for area of customer-provider relation and it presents, how to avail acquired knowledge as basis of managerial decisions leading to improving of customer relationship management. It solves prediction, whose aim is, on the basis of some attributes of exploring objects, to predict future be­ha­viour of objects with these attributes. This way acquired knowledge, as the output of prediction, then can markedly help competent enterprise manager with planning of marketing strategies, for example so-called cross-selling and up-selling. The contribution describes a whole operation of available data processing: from its purifying, over its preparation for mining task, to self processing by the help of SAS Enterprise Miner tool. Regression analysis, neural network and decision tree, whose principles are briefly explained in this paper too, were used for knowledge mining. The estimation of customer behaviour was tested by two mining task varying in attribute using and in categories number of one of predicive attributes. The results of these two tasks are confronted by the help of prediction fruitfulness charts.

Suitability of Customer Relationship Management Systems for the Management of Study Participants in Biomedical Research

2013 ◽  
Vol 52 (04) ◽  
pp. 340-350 ◽  
Author(s):  
O. Rienhoff ◽  
T. G. Schulze ◽  
S. Y. Nussbeck ◽  
J. Schwanke
Keyword(s):  
Customer Relationship Management ◽  
Biomedical Research ◽  
Relationship Management ◽  
Study Participant ◽  
Requirements Analysis ◽  
Customer Relationship ◽  
Management Systems ◽  
Quality Of Data ◽  
Suitability Evaluation ◽  
Study Participants

SummaryBackground: Longitudinal biomedical research projects study patients or participants over a course of time. No IT solution is known that can manage study participants, enhance quality of data, support re-contacting of participants, plan study visits, and keep track of informed consent procedures and recruitments that may be subject to change over time.. In business settings management of personal is one of the major aspects of customer relationship management systems (CRMS).Objectives: To evaluate whether CRMS are suitable IT solutions for study participant management in biomedical research.Methods: Three boards of experts in the field of biomedical research were consulted to get an insight into recent IT developments regarding study participant management systems (SPMS). Subsequently, a requirements analysis was performed with stake-holders of a major biomedical research project. The successive suitability evaluation was based on the comparison of the identified requirements with the features of six CRMS.Results: Independently of each other, the interviewed expert boards confirmed that there is no generic IT solution for the management of participants. Sixty-four requirements were identified and prioritized in a requirements analysis. The best CRMS was able to fulfill forty-two of these requirements. The non-fulfilled requirements demand an adaption of the CRMS, consuming time and resources, reducing the update compatibility, the system’s suitability, and the security of the CRMS.Conclusions: A specific solution for the SPMS is favored instead of a generic and commercially-oriented CRMS. Therefore, the development of a small and specific SPMS solution was commenced and is currently on the way to completion.

scholarly journals Development of Customer Relationship Management System in E-Commerce Based on BP Neural Network

2012 ◽  
Vol 6-7 ◽  
pp. 995-999
Author(s):  
Mei Ling Zhou ◽  
Jing Jing Hao
Keyword(s):  
Neural Network ◽  
Customer Relationship Management ◽  
Bp Neural Network ◽  
Management System ◽  
Customer Value ◽  
Relationship Management ◽  
Customer Relationship ◽  
Feed Forward Network ◽  
Neural Network Algorithm ◽  
Hidden Layer

BP neural network can learn and store a lot of input - output mode mapping, without prior reveal the mathematical equations describe the mapping. The model based on BP neural network algorithm is constituted by an input layer, output layer and one hidden layer, three-layer feed forward network. CRM is to acquire, maintain and increase the methods and processes of profitable customers. The core of CRM is the customer value management, customer value; it is divided into the de facto value, potential value and model value. The paper presents development of customer relationship management system in e-commerce based on BP neural network. The experiment shows BP is superior to RFCA in CRM.

Sign in / Sign up

Export Citation Format

Share Document