Many institutions struggle to develop a meaningful way to assess the effectiveness of drop-in tutorial services provided to students. This article discusses the development of a data collection system based on a visitor sign-in system that proved to be an efficient method of gathering assessment data, including frequency of visits, end-of-course grades, and demographic information on student visitors. The data were used to analyze the impact of tutorial services on student grade rates, with special attention given to the effects of service on populations underrepresented (females and Blacks) in science, technology, engineering, and mathematics (STEM) fields. The results showed a significant difference in grade distributions among Black males and provided evidence to support the existence of self-selection biases in the use of tutorial services. The biases may include self-selected use of tutorial services by at-risk students, who are more likely to need support, and by self-motivated students, who are more likely to utilize all available resources to succeed.