Discovering Patterns of Users' Behaviour in an E-shop - Comparison of Consumer Buying Behaviours in Poland and Other European Countries

• Authors: Mariusz Łapczyński , Sylwester Białowąs
• Languages of publication: EN

Abstracts

EN

The goal of this article is to analyze behaviour patterns of customers to an e-shop offering clothing for women. The authors discovered the sequences of selected products from the store (web clickstream analysis) and conducted market basket analysis by using popular association rules. IP addresses of visitors that were obtained from web logs enabled identification of the user's country of residence. Geolocation was the basis of comparison of consumer buying behaviours in Poland and other European countries.

Keywords

EN

Customer behaviour; E-commerce

PL

Handel elektroniczny; Zachowania klientów

• Publisher: Uniwersytet Ekonomiczny w Katowicach
• Journal: Studia Ekonomiczne
• Year: 2013
• Volume: 151
• Pages: 144-153

Contributors

author

Mariusz Łapczyński

author

Sylwester Białowąs

References

• Agrawal R., Imielinski T., Swami A.: Mining Association Rules Between Sets of Items in Large Databases. In: Proceedings of the ACM SIGMOD Conference on Management of Data. Washington D.C., May 1993.
• Brijs T. et al.: Using Association Rules for Product Assortment Decisions: A Case Study. In: Proceedings KDD-99, San Diego, California 1999.
• Carmona C.J., Ramirez-Gallego S., Torres F., Bernal E., del Jesus M.J., Garcia S.: Web Usage Mining to Improve the Design of an e-commerce Website: OrOliveSur. com. "Expert Systems with Applications" 2012, No. 39.
• Chen M.-C., Lin C.-P.: A Data Mining Approach to Product Assortment and Shelf Space Allocation. "Expert Systems With Applications" 2007, No. 32(4).
• Cooley R., Mobasher B., Srivastava J.: Web Mining: Information and Pattern Discovery on the World Wide Web. Proceedings of the 9th International Conference on Tools with Artificial Intelligence. IEEE Computer Society, 1997.
• Linoff G.S., Berry M.J.A.: Mining the Web. Transforming Customer Data into Customer Value. John Wiley & Sons, New York 2001.
• Liu B.: Web Data Mining. Exploring Hyperlinks, Contents, and Usage Data. Springer, Heidelberg 2007.
• Munk M., Drlik M.: Impact of Different Pre-Processing Tasks on Effective Identification of Users' Behavioral Patterns in Web-based Educational System. "Procedia Computer Science" 2011, No. 4.
• Russell G.J., Petersen A.: Analysis of Cross Category Dependence in Market Basket Selection. "Journal of Retailing" 2000, No. 76.
• Sohn S., Kim Y.: Searching Customer Patterns of Mobile Service Using Clustering and Quantitative Association Rule. "Expert Systems With Applications" 2008, No. 34(2).
• Van den Poel D., Schamphelaere J.D., Wets G.: Direct and Indirect Effects of Retail Promotions on Sales and Profits in the Do-it-yourself Market. "Expert Systems With Applications" 2004, No. 27(1).
• Zhang X., Edwards J., Harding J.: Personalised Online Sales Using Web Usage Data Mining. "Computers in Industry" 2007, No. 58.

Identifiers

ISSN

2083-8611