Search results for "click-stream analysis"
showing 2 items of 2 documents
Using association rules to assess purchase probability in online stores
2016
The paper addresses the problem of e-customer behavior characterization based on Web server log data. We describe user sessions with the number of session features and aim to identify the features indicating a high probability of making a purchase for two customer groups: traditional customers and innovative customers. We discuss our approach aimed at assessing a purchase probability in a user session depending on categories of viewed products and session features. We apply association rule mining to real online bookstore data. The results show differences in factors indicating a high purchase probability in session for both customer types. The discovered association rules allow us to formu…
Characterizing Web sessions of e-customers interested in traditional and innovative products
2016
Web traffic characterization and modelling is currently a hot research issue. Low-level analysis of HTTP traffic on the server allows one to build adequate traffic models to be used in server benchmarking. High-level analysis of Web user behavior allows one to optimize website structure and develop personalized service strategies. In this paper, analysis of customer sessions in an online store is performed using Web server log data. The goal is to explore possible differences between sessions of customers viewing and purchasing innovative products, and customers only interested in traditional products.