This article explores the use of the AutoScholar Advisor System (Auto-Ad) to provide useful learning support analytics for self-mediated student academic support. The study is part of a pilot project for enhancing student success in a four-year undergraduate degree (BEd) programme. Adopting students' self-authorship as an organising framework and using the Auto-Ad implemented on the learning management platform, the study involved 200 high-performing undergraduate students (cum laude or summa cum laude trajectory) in a School of Education at one university. A mixed-methods approach was used to collect and analyse the data. Quantitative data were analysed based on the students' interaction with the Auto-Ad as academic learning support tool to enhance their performance through automated advising. Qualitative open-ended comments allowing in-depth insight into the students' perceptions of their performance were also analysed. The students considered knowledge, self, and relationship to be important for achieving high performance and success. The strongest correlated factors were choice of degree, motivation, study habits, family, and relationships. Implications of these findings within the current student support systems at South African universities are discussed.