This exploratory study aimed to investigate the characteristics of students who opted in to use Boost, an automated student-support mobile app, and compare them to characteristics of Boost nonusers. Boost integrates with a learning management system (Canvas) and provides support services aimed at improving student behavior and success. At the start of the spring 2019 semester at Indiana University, instructors were invited to opt in for Boost to be available to their classes. Instructors who did so invited their students to use Boost. Our multivariate analysis of variance compared those who opted in for automated support with those who did not (n = 158 courses). Findings reveal that opt-ins were further along in their studies and slightly lower performing than their peers who did not opt in. A profile of Boost users will help university administration, student support services, and instructors make data-informed decisions on the optimal use of Boost.