The Sort and Sift, Think and Shift qualitative data analysis approach is an iterative process where analysts dive into data to understand its content, dimensions, and properties, and then step back to assess what they have learned and to determine next steps. Researchers move from establishing an understanding of what is in the data (“Diving In”) to exploring their relationship to the data (“Stepping Back”). This process of “Diving In” and “Stepping Back” is repeated throughout analysis. To conclude, researchers arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge. To illustrate core tenets of Sort and Sift, Think and Shift, we analyzed three focus group transcripts from a study of postnatal care referral behavior by traditional birth attendants in Nigeria; these transcripts came from Syracuse University’s Qualitative Data Repository and were unfamiliar to the analytic team prior to this exercise. We focused on letting the data be our guide into not only the explicit purpose of the interviews, but also into the unexpected discoveries that arise when inquiring about people’s lived experiences. Situating our efforts within an Initial Learning Period, each member of the team closely read each transcript, and then identified powerful quotations that made us pause and take note. We documented what we learned from each transcript in an episode profile which contained diagrams and memos. Episode profiles were shared and discussed across the team to identify key points of interest, such as the role of faith in women’s decision-making processes related to their pregnancy and delivery preferences, and concepts of who bears what knowledge about reproductive health. Our engagement in this analytic exercise demonstrates the applicability of qualitative inquiry and Sort and Sift as flexible approaches for applied research.