Abstract
In this paper, we describe the research and development of a fuzzy expert system methodology for categorising customer and customer service advisor (CSA) within customer contact centre (CCC) environment. On the basis of data collected through case studies carried out within customer contact centre, two step clustering analysis within SPSS was used to derive the categories for customers and advisors based on demographic, experience, business value and behavioural attributes. The fuzzy expert system assigns a new customer or advisor to the pre-defined categories and provides the corresponding membership values given into the system using fuzzy logic. The author has explained the steps which were followed for the development of the fuzzy expert system. A prototype system has been designed and developed to identify the type of customer and CSA based on the demographic, experience and behavioural attributes. Experimental results are provided and the methodology is validated within the case study approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bushey, R.; Mauney, J. M. and Deelman, T. (1999). The development of behaviour-based user models for a computer system. 7th International Conference on User Modeling (UM99). 20th–24th June 1999. Banff Centre, Banff. Canada. Pp 109–18
Chiu, C (2002). A case based customer classification approach for direct marketing. Expert Systems with Applications. Vol 22 (2002). Pp 163–168. Elsevier Science
Dolen, W; Ruyter, K and Lemmink, J. (2004). An empirical assessment of the influence of customer emotions and contact employee performance on encounter and relationship satisfaction. Journal of Business Research. Vol. 57. Pp 437–444.
Goff, B. G; Boles, J. S; Bellenger, D. N and Stojack, C. (1997). The influence of salesperson selling behaviours on customer satisfaction with products. Journal of Retailing. Vol 32. No 2. pp 171–183.
Harline, M. D and Ferrell, O. C (1996). The management of customer contact service employees: an empirical investigation. Journal of Marketing. Vol 60 (1996). Pp 52–70.
Heckman, R and Guskey, A (1998). Sources of customer satisfaction and dissatisfaction with information technology help desks. Journal of Market Focused Management. Vol 3. pp 59–89.
Hu, T. and Sheu, J. (2003). A fuzzy based customer classification method for demand responsive logistical distribution operations. Fuzzy Sets and Systems. Vol 139. No.2 October 2003. PP 431–450
Johann, B; Knut, W. and Melanie, V. (2001). SPSS Two Step Cluster — A first evaluation. http://www.statisticalinnovations.comlproducts/twostep.pdf
Martinez, F.E; Magoulas G.D.; Chen S., and Macredie R. (2004). Recent soft computing approaches to user modeling in Adaptive Hypermedia. Proceedings of 3rd Int. Conference Adaptive Hypermedia-AH 2004, Eindhoven, The Netherlands, Aug. 2004, Lecture Notes in Computer Science, vol. 3137, Springer, 104–113.
Mathworks Fuzzy Logic Toolbox. Model based design software. Available at: http://www.mathworks.comlproducts/fuzzylogic/ (accessed on: 15/01/05)
Ngai, E.W.T and Wat, F.K.T (2003). Design and development of a fuzzy expert system for hotel selection. International Journal of Management Science. Vol 31. PP 275–86.
Song, H. S; Kim, J. K. and Kim, S. H. (2001). Mining the change of customer behaviour in an Internet shopping mall. Expert Systems and Applications. Vol 21. pp 157–168. Elsevier Science Ltd.
SPSS Inc (2005). Statistics & Data Mining Software: SPSS.
Swinyard, W. R (2003). The effects of salesperson mood, shopper behaviour and store type on customer service. Journal of Retailing and Consumer Services. Vol 10 (2003). Pp 323–333. Elsevier Science Ltd.
Zadeh, L. (1996). The role of soft computing and fuzzy logic in conception, design and deployment of intelligent systems. Proceedings International Workshop on Soft Computing in Industry, Muroran, Japan, April 1996, pp 136–137.
Zeelenberg, M. and Pieters, R. (2004). Beyond valence in customer dissatisfaction: A review and new findings on behavioural responses to regret and disappointment in failed services. Journal of Business Research. Vol 57 (2004). Pp 445–455. Elsevier Science Ltd.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shah, S., Roy, R., Tiwari, A. (2006). Development of Fuzzy Expert System for Customer and Service Advisor Categorisation within Contact Centre Environment. In: Tiwari, A., Roy, R., Knowles, J., Avineri, E., Dahal, K. (eds) Applications of Soft Computing. Advances in Intelligent and Soft Computing, vol 36. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36266-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-36266-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29123-7
Online ISBN: 978-3-540-36266-1
eBook Packages: EngineeringEngineering (R0)