This paper is an example of data mining in action. The database we are mining contains 1085 profiles of individuals who have downloaded the statistical software XploRe. Each profile contains the responses to an online questionnaire comprised of questions about such things as an individuals' computing preferences (operating system, favourite statistics software) or professional affiliation. After formatting and cleaning the raw data using MS Excel, we use IBM's Intelligent Miner to perform a cluster analysis of the download profiles. We try to identify a small number of types of users by employing a clustering algorithm based on the New Condorcet Criterion, which is particularly well-suited for our all-categorical data. We identify three clusters in the mining run: Academia, Unix/Linux users and Researchers. The three variabels that are most important in identifying the clusters are an individual's kind of work, the way he or she got to know XploRe and the operating system of his or her computer.