Analyzing online consumer behavior in mobile and PC devices: A novel web usage mining approach Academic Article uri icon

abstract

  • We compare online browsing behavior across mobile and PC platforms.A novel web usage mining approach is proposed to identify sequences of navigation patterns in clickstream data.The approach combines footstep graph visualization with sequential rule mining.Mobile sessions are more task-oriented, whereas PC sessions are more exploratory.Sequence rules are valuable in predicting a purchase for both mobile and PC devices. We investigate and compare online consumer behavior on an e-retailer website in mobile versus PC devices, through the application of a web usage mining approach on clickstream data recorded in server-side log files. Online consumer behavior is characterized through both engagement measures and the discovery of common sequences of navigation patterns, using an innovative approach that combines footstep graph visualization with sequential association rule mining. We find that sessions conducted through mobile devices are more likely to consist of task-oriented behavior whereas sessions conducted through PC devices are characterized by a more exploration-oriented browsing behavior. Moreover, we find that certain sequence rules are associated with an increased likelihood of purchase in both mobile and PC sessions. The results demonstrate the value of our approach in analyzing online browsing behavior, across platforms, in the context of electronic retailing.

publication date

  • January 1, 2017