Understanding users’ behavior with software operation data mining

•We inspect different types of knowledge about software users’ usage behavior.•We select state-of-the-art data mining techniques to analyze software usage.•We create a method for mining usage knowledge from software operation data.•We instantiate the method in a prototype developed in R.•We evaluate the Usage Mining Method and the prototype by means of a case study.

Software usage concerns knowledge about how end-users use the software in the field, and how the software itself responds to their actions. In this paper, we present the Usage Mining Method to guide the analysis of data collected during software operation, in order to extract knowledge about how a software product is used by the end-users. Our method suggests three analysis tasks which employ data mining techniques for extracting usage knowledge from software operation data: users profiling, clickstream analysis and classification analysis. The Usage Mining Method was evaluated through a prototype that was executed in the case of Exact Online, the main online financial management application in the Netherlands. The evaluation confirmed the supportive role of the Usage Mining Method in software product management and development processes, as well as the applicability of the suggested data mining algorithms to carry out the usage analysis tasks.