DocumentCode :
2499744
Title :
Improving customer satisfaction by the expert system using artificial neural networks
Author :
Qian, Feng ; Xu, Linwen
Author_Institution :
Inst. of Manage. Sci. & Inf. Eng., Hangzhou Dianzi Univ., Hangzhou
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
8303
Lastpage :
8306
Abstract :
CRM, which aims to enhance the effectiveness and performance of the businesses by improving the customer satisfaction and loyalty, has now become a leading business strategy in highly competitive business environment. The objective of this research is to improve customer satisfaction on productpsilas colors with the aid of the expert system developed by the authors by using artificial neural networks. The expert systempsilas role is to capture the knowledge of the experts and the data from the customer requirements, and then, process the collected data and form the appropriate rules for choosing productpsilas colors. In order to identify the hidden pattern of the customerpsilas needs, the artificial neural networks technique has been applied to classify the colors based upon a list of selected information. Moreover, the expert system has the capability to make decisions in ranking the scores of the colors presented in the selection. In addition, the expert system has been validated with a variety of customer types.
Keywords :
customer satisfaction; expert systems; neural nets; CRM; artificial neural networks; business strategy; customer requirements; customer satisfaction; expert system; Artificial neural networks; Automation; Color; Customer satisfaction; Engineering management; Expert systems; Information management; Intelligent control; Neurons; Pattern recognition; Artificial neural networks; Customer relationship management; Expert system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594228
Filename :
4594228
Link To Document :
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