Consensus as a tool supporting customer behaviour prediction in Social CRM systems

• Autorzy: Czyszczoń A. , Zgrzywa A.
• Języki publikacji: EN

Abstrakty

EN

Social Customer Relationship Management systems represent a new area in the field of CRM which together with rapid development of Social Networks and Social Media has acquired strategic importance for many companies. As a response to ongoing challenges related to growing customer expectations, in this paper we present intelligent tools for customer behaviour prediction in Social CRM systems. The use of the consensus approach is aimed at resolving contradictory forecasts of customer behaviour provided by different agents working as independent Artificial Neural Networks systems. The goal of the presented tool is to improve prediction functionality of customer behaviour.

Słowa kluczowe

EN

CRM; Social CRM; consensus method; customer behaviour; behaviour prediction

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2012
• Tom: Vol. 13 (4)
• Strony: 133--146
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Czyszczoń A.

• Wrocław University of Technology, Faculty of Computer Science and Management, Wrocław, Poland

autor

Zgrzywa A.

• Wrocław University of Technology, Faculty of Computer Science and Management, Wrocław, Poland

Bibliografia

• [1] Czyszczon A., Zgrzywa A.: Zastosowanie sztucznych sieci neuronowych do przewidywania zachowania klientów w systemie CRM, pp. 61–72. Wydawnictwo WTN, xviii edition, 2011.
• [2] Greenberg P.: CRM at the Speed of Light: Social CRM Strategies, Tools, and Techniques for Engaging Your Customers, 4th ed. McGraw-Hill, 2010.
• [3] Grzanka I.: Kapitał społeczny w relacjach z klientami. CeDeWu, 2009.
• [4] Gartner Inc..: Gartner press release. http://www.gartner.com/it/section.jsp, February 2012.
• [5] Nguyen N. T.: Consensus system for solving conflicts in distributed systems. Information Sciences, 147(14):91 – 122, 2002.
• [6] Nguyen N. T.: Advanced Methods for Inconsistent Knowledge Management (Advanced Information and Knowledge Processing). Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2008.
• [7] Urban W., Siemieniako D.: Lojalnosc klientów. Modele, motywacja i pomiar. Wydawnictwo Naukowe PWN, Warszawa, 2008.