Measuring Customers Satisfaction of E-Commerce Sites Using Clustering Techniques: Case Study of Nyazco Website

Document Type: Case Study


1 Department of Information Technology Management, Management and Accounting Faculty of Shahid Beheshti University, Tehran, Iran

2 Faculty Member of Information Technology Management Group, Shahid Beheshti University, Tehran, Iran


Today the use of modern technologies in the daily life for satisfying the needs is unavoidable. Follow the news and searching through the internet has affected organizations to provide platform on the Internet for availability of information for the customers. With the development of e-commerce, online shopping plays an increasingly important role in people’s life. With the use of data mining technique prospect, managers of this site can analyze preferences and purchasing patterns of online customers in order to custom product recommendations. Data mining helps to provide services in accordance with customers’ requirements. The aim of this research is to identify the customers’ requirements in online shopping and cluster these customers based on independent attributes such as gender, product classification, recency, frequency and monetary. For this purpose, the data related to Nyazco website that is an e-commerce website with a variety of products, were examined as a case study in the period of 7 months. The authors of this paper will define four clusters by using k-means algorithm and RFM model by IBM SPSS Modeler 14.2 software. Customers in the third cluster and fourth cluster will be identified as the most important customers. Therefore, providing the demands of these customers should be prioritized.


Al-Mudimigh, A. S., Saleem, F., Ullah, Z., & Al-Aboud, F. N. (2009, August), “Implementation of Data Mining Engine on CRM-improve customer satisfaction,” In Information and Communication Technologies, 2009. ICICT'09. International Conference on (pp. 193-197). IEEE.
Aresti, A., Markellou, P., Mousourouli, I., Sirmakessis, S., & Tsakalidis, A. (2008), “A movie e-shop recommendation model based on web usage and ontological data,” Journal of electronic commerce in organizations (JECO), 5(3), 2008, pp 51-69.
Brun, M., Sima, C., Hua, J., Lowey, J., Carroll, B., Suh, E., & Dougherty, E. R. (2007), “Model-based evaluation of clustering validation measures,” Pattern Recognition, 40(3), 807-824.
Chen, H., & Li, Y. (2007), “An Empirical Research of Factors Influencing the Decision-Making of Chinese Online Shoppers,” In Integration and Innovation Orient to E-Society Volume 1 (pp. 202-210). Springer US.
Chen, L. F., & Tsai, C. T. (2016), “Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain,” Tourism Management, 53, 197-206.
Cheng, C.H. and Chen, Y.S. (2009), “Classifying the segmentation of customer value via RFM model and RS theory,” Expert Systems with Applications, Vol. 36, No. 3, pp.4176–4184.
Cho, Y. S., Moon, S. C., Noh, S. C., & Ryu, K. H. (2012, June), “Implementation of Personalized recommendation System using k-means Clustering of Item Category based on RFM,” In Management of Innovation and Technology (ICMIT), 2012 IEEE International Conference on (pp. 378-383). IEEE.
Cho, Y. S., Moon, S. C., Noh, S. C., & Ryu, K. H. (2012, June), “Implementation of Personalized recommendation System using k-means Clustering of Item Category based on RFM,” In Management of Innovation and Technology (ICMIT), 2012 IEEE International Conference on (pp. 378-383). IEEE.
Deng, X. (2013), “An Efficient Hybrid Artificial Bee Colony Algorithm for Customer Segmentation in Mobile E-commerce,” Journal of Electronic Commerce in Organizations (JECO), 11(2), 53-63.
Deng, Z., Lu, Y., Wei, K.K. and Zhang, J. (2010), “Understanding customer satisfaction and loyalty: an empirical study of mobile instant messages in China,” International Journal of Information Management, Vol. 30 No. 4, pp. 298-300.
Evanschitzky, H., Iyer, G. R., Hesse, J., & Ahlert, D. (2004), “E-satisfaction: a re-examination,” Journal of retailing, 80(3), 239-247.
Hamel, G., Sampler, J. (1998), “E-corporation; more than just Web-based, it’s building a new industry order”, pp. 52–63.
Ho, C. F., & Wu, W. H. (1999, January), “Antecedents of customer satisfaction on the Internet: an empirical study of online shopping,” In Systems Sciences, 1999. HICSS-32. Proceedings of the 32nd Annual Hawaii International Conference on (pp. 9-pp). IEEE
Hongli, G., & Juntao, L. (2011, October), “The application of mining association rules in online shopping,” In 2011 Fourth International Symposium on Computational Intelligence and Design (pp. 208-210). IEEE.
Hosseini, S. M. S., Maleki, A., & Gholamian, M. R. (2010), “Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty,” Expert Systems with Applications, 37, 5259–5264.
Kalakota, R. and A. B. Whinston, (1996), “Frontiers of Electronic Commerce.” Addison-Wesley Publishing, MA.
Keim, D. A., Pansea, C., Sipsa, M., & Northb, S. C. (2004), “Pixel based visual data mining of geo-spatial data,” Computers and Graphics, 28, 327–344.
Lee, Y., & Kim, J. (2002), “From Design Features to Financial Performance: A Comprehensive Model of Design Principles for Online Stock Trading Sites,” J. Electron. Commerce Res., 3(3), 128-143.
Liao, S. H., & Chen, Y. J. (2004), “Mining customer knowledge for electronic catalog marketing,” Expert Systems with Applications, 27, 521–532.
Liao, S. H., Chen, Y. J., & Lin, Y. T. (2011), “Mining customer knowledge to implement online shopping and home delivery for hypermarkets,” Expert Systems with Applications, 38(4), 3982-3991.
Liao, S. H., Chu, P. H., & Hsiao, P. Y. (2012), “Data mining techniques and applications–A decade review from 2000 to 2011,” Expert Systems with Applications, 39(12), 11303-11311.
Liao, S. H., Hsieh, C. L., & Huang, S. P. (2008), “Mining product maps for new product development,” Expert Systems with Applications, 34(1), 50–62.
Lun, O. K., & Yazdanifard, R. (2015), “How Could Xiaomi Success in Online Phone Purchase Persuasion Influence other Phone Manufacturer?”, International Journal of Management, Accounting and Economic, Vol. 2, No. 5, pp. 481-488.
Nadali, A., Kakhky, E. N., & Nosratabadi, H. E. (2011, April), “Evaluating the success level of data mining projects based on CRISP-DM methodology by a Fuzzy expert system,” In Electronics Computer Technology (ICECT), 2011 3rd International Conference on (Vol. 6, pp. 161-165). IEEE.
Samizadeh, R., Koosha, H., Zangeneh, S. N., & Vatankhah, S. (2015), “A New Model for the Calculation of Customer Life-time Value in Iranian Telecommunication Companies,” International Journal of Management, Accounting and Economic, Vol. 2, No. 5, pp.394- 403.
Santouridis, I., & Trivellas, P. (2009, December), “Investigating the mediation effect of satisfaction on the service quality and customer loyalty link: empirical evidence from Greek customers of internet shops,” In Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on (pp. 2227-2231). IEEE.
Shim, B., Choi, K., Suh, Y. “CRM strategies for a small-sized online shopping mall based on association rules and sequential patterns,” expert system with applications, 39, 2012, pp. 7736-7742.
Ting, C. W., Chen, M. S., & Lee, C. L. (2013), “E-satisfaction and post-purchase behaviour of online travel product shopping,” Journal of Statistics and Management Systems, 16(2-3), 223-240.
Ture, M., Kurt, I., Turhan, K. A., & Ozdamar, K. (2005), “Comparing classification techniques for predicting essential hypertension,” Expert Systems with Applications, 16(4), 379–384.
Vrahatis, M. N., Boutsinas, B., Alevizos, P., & Pavlides, G. (2002), “The new k-windows algorithm for improving the k-means clustering algorithm,” Journal of Complexity, 18(1), 375–391.
Zamzuri, N. H. A., Mohamed, N., & Hussein, R. (2008, August), “Antecedents of customer satisfaction in repurchase intention in the electronic commerce environment,” In Information Technology, 2008. ITSim 2008. International Symposium on (Vol. 3, pp. 1-5). IEEE.
Zboja, J. J., & Voorhees, C. M. (2006), “The impact of brand trust and satisfaction on retailer repurchase intentions,” Journal of Services Marketing, 20(6), 381-390.
Zhang, L., & Wang, Y. (2014, May), “Research and Realization of Online-Shopping Customer Segmentation Based on RFM Model,” In Applied Mechanics and Materials (Vol. 513, pp. 1361-1364).
Zhang, Y., Fang, Y., Wei, K. K., Ramsey, E., McCole, P., & Chen, H. (2011), “Repurchase intention in B2C e-commerce—A relationship quality perspective,” Information & Management, 48(6), 192-200.