Learning management systems (LMS) allow for a variety of ways in which online multiple-choice assessments ("tests") can be configured, including the ability to allow for multiple attempts and options for which of and how the attempts will count. These options are usually chosen according to the instinct of the instructor; however, LMS also provide an opportunity to make data-informed decisions based on data captured by the LMS itself. This article describes an experience with extracting and analyzing LMS data for determining online test option settings that encourage behaviors that promote learning (or discourage behaviors that do not). The data extraction and cleaning process was relatively straightforward, but not without some challenges, and required beyond-novice spreadsheet skills. It seems to have been worth the effort, though, as the insights gained led directly to a change in online test administration, and current option settings seem more appropriate and are supported by data.