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Linguistic corpus analysis is often an overlooked research method in writing center studies. This methodology has the potential to reveal countless patterns in datasets, but frequently lacks important details. Pairing corpus analysis with inductive coding—a qualitative approach—provides a comprehensive view of both overarching themes and specific information. This paper utilized this mixed-methods approach to explore the types of feedback that writing consultants provide to students during sessions at Iowa State University’s writing center. Session notes, written by a consultant during a writing session, contain an abundance of information surrounding the inner workings of writing centers, but few studies have recognized them as viable data sources. For the quantitative analysis, this study utilized AntConc to derive frequencies of commonly occurring words and n-grams in session notes. The qualitative analysis consisted of a process of inductively coding the data to identify commonly occurring themes and define them based on their linguistic realizations. By creating an initial coding guide, completing several rounds of session note annotations, and adjusting the guide as needed, inductive coding provided a level of context and detail that was instrumental in understanding the characteristics of writing center session notes.