- With the growing popularity of mobile commerce (m-commerce), it becomes vital for both researchers and practitioners to understand m-commerce usage behavior. In this study, we investigate browsing behavior patterns based on the analysis of clickstream data that is recorded in server-side log files. We compare consumers' browsing behavior in the m-commerce channel against the traditional ecommerce channel. For the comparison, we offer an integrative web usage mining approach, combining visualization graphs, association rules and classification models to analyze the Web server log files of a large Internet retailer in Israel, who introduced m-commerce to its existing e-commerce offerings. The analysis is expected to reveal typical m-commerce and e-commerce browsing behavior, in terms of session timing and intensity of use and in terms of session navigation patterns. The obtained results will contribute to the emerging research area of m-commerce and can be also used to guide future development of mobile websites and increase their effectiveness. Our preliminary findings are promising. They reveal that browsing behaviors in m-commerce and e-commerce are different.