Perspectives of Innovations, Economics and Business

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Volume 7
Issue 1
Online publication date 2011-01-16
Title Utilization of intelligent methods and techniques for customer knowledge management
Author Trninic Jelica, Grljevic Olivera, Ana Maria Serdar
Abstract In order to achieve better market position, companies need to develop customer-centric strategy and properly manage customer data at their disposal in order to obtain useful knowledge. However, conversion of customer data into customer knowledge is very challenging. Data mining methods and techniques search for hidden relationships and patterns in corporate databases, and herein lies their advantage in the process of generating the knowledge. The paper illustrates application of data mining techniques for improvement of marketing activities.
Citation
References
Berry, M., Linoff, G., 2004. Data mining techniques for marketing, sales, and customer relationship management, Wiley Publishing

Bošnjak, Z., 2006. Inteligentni sistemi i poslovna primena, Subotica: Ekonomski fakultet

Buttle, F., 2009. Customer relationship management: Concepts and technologies, Elsevier

Dous, M., Kolbe, L., Salomann, H., Brenner, W., 2005. “Knowledge management capabilities in CRM: Making knowledge for, from and about customers work,” Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA, pp.167-78

Frank, A., Asuncion, A., 2010. UCI machine learning repository, Irvine, CA: University of California, School of Information and Computer Science (http://archive.ics.uci.edu/ml)

Grljević, O., Zita, B., 2008. Primena CRISP-DM Metodologije u Analizi Podataka o Malim i Srednjim Preduzećima. SYM-OP-IS, Septembar, Soko Banja, Serbia. pp.275-79

Lei, Y., Tang, B., 2005. “Study on knowledge management based CRM system,” Proceedings, The Sixth Wuhan International Conference on E-Business, pp.2505-510

Sison, R., 2006. Knowledge management: Concepts, techniques and cases, knowledge management, Philippines, Manila: De La Salle University
 
Keywords Knowledge management, customer relationship management, data mining.
DOI http://dx.doi.org/10.15208/pieb.2011.11
Pages 48-50
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