What Is Memo Writing?
Memo writing is the practice of recording analytic thoughts, questions, comparisons, and emerging ideas throughout the qualitative research process. Memos aren't field notes (which describe what happened) or code definitions (which define labels). They're the researcher's running commentary on the analysis itself, why a code was created, how two categories might connect, what a surprising data segment means, or why a participant's account contradicts the emerging pattern. In grounded theory, memo writing is considered as essential as coding itself. Glaser called it "the core stage in the process of generating theory." In practice, memos are where the real analytic thinking happens, not in the codebook, not in the final report, but in the messy, iterative process of writing your way toward understanding.
Why Memo Writing Matters
Coding without memo writing is filing, not analyzing. You can label every segment of your data and still not understand what it means. Memos force you to think on paper, to articulate why a code matters, how it connects to other codes, and what you're starting to see across the dataset. They also create an audit trail that makes your analytic process transparent to others (and to your future self). When you sit down to write findings and wonder "why did I create this category?", the memo answers that question.
How Memo Writing Works
Types of Memos
Code memos document individual codes: their definition, the reasoning behind them, examples, and how they've evolved. When you split a code into two subcodes or merge two codes that overlap, the code memo explains why.
Theoretical memos explore emerging ideas: how categories might relate, what processes the data suggests, what theoretical framework might account for the patterns you're seeing. These are the memos that eventually become the backbone of your findings.
Methodological memos record decisions about the research process: why you changed your interview guide after the fifth interview, why you added a new participant segment, why you decided to use focused coding instead of axial coding.
Personal reflection memos capture your reactions, assumptions, and biases. They overlap with reflexivity practices, documenting how your own perspective might be shaping your analysis.
When to Write Memos
During coding. When a code surprises you, confuses you, or excites you, write a memo. When you notice a pattern across participants, write a memo. When a participant contradicts what everyone else said, write a memo. The trigger is any moment of analytic energy, whether positive or negative.
Between coding sessions. Some of your best analytic ideas will come when you step away from the data. Keep a way to capture them, a notebook, a voice memo, a notes app.
During second-cycle coding. As you move from open coding to focused coding or pattern coding, memos help you document why you selected certain codes, how you defined categories, and what relationships you're proposing.
When you're stuck. If your analysis stalls, write a memo about why it's stalled. Often, the act of articulating the problem reveals the solution.
Memo Writing Practices
Start messy. Memos aren't polished prose. They're thinking tools. Write in fragments, questions, contradictions. A memo that says "I keep seeing X but I don't know what it means, maybe it's related to Y?" is a productive memo.
Date every memo. Your thinking will evolve. Dating memos lets you track how your analysis developed over time.
Sort memos periodically. As memos accumulate, organize them by code, category, or theme. This sorting process often reveals connections you hadn't noticed.
Use memos in your write-up. The theoretical memos you've been writing throughout the project become first drafts of your findings sections. Some researchers find that their best analytic writing appears in memos rather than in formal reports.
Memo Writing and AI-Assisted Analysis
When using AI-powered qualitative analysis tools, memo writing becomes even more important. AI can generate codes, but it can't generate the analytic reasoning behind them. Your memos document why you accepted, rejected, or modified AI-generated codes, maintaining the human interpretation that gives qualitative research its depth.
When to Use Memo Writing
- Every qualitative study. Memo writing isn't optional methodology, it's a core practice that strengthens any qualitative analysis regardless of method or tradition.
- Grounded theory: memo writing is mandatory in all versions of grounded theory (Glaser, Strauss and Corbin, Charmaz).
- Long-duration studies: in longitudinal or multi-phase research, memos preserve analytic continuity across months or years.
- Team-based analysis: shared memos help team members understand each other's coding decisions and build shared interpretive frameworks.
Common Mistakes
- Not writing memos at all. The most common mistake. Researchers skip memos because they feel like extra work, then struggle to move from codes to findings because they haven't developed their thinking along the way.
- Writing memos that are too short or too descriptive. "This code is about pricing" isn't a memo, it's a code definition. A memo should explore: Why does pricing come up so often? What's different about how different participants talk about it? What does pricing connect to in the broader analysis?
- Waiting until analysis is "done" to write memos. Memos written after the fact are rationalizations, not analytic tools. The value of memo writing comes from doing it during analysis, when your thinking is active and evolving.
Quali-Fi Support
Quali-Fi's qualitative analysis platform includes annotation and memo tools alongside its AI-powered thematic coding, so researchers can document their analytic reasoning directly alongside focus group transcripts, discussion board data, and coded survey responses. Every AI-generated code can be annotated with researcher memos that explain the human interpretation behind the analysis.
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FAQs
How long should a memo be?
As long as it needs to be, from a single paragraph to several pages. Theoretical memos exploring complex category relationships might run long. Code memos might be a paragraph. The goal is to capture your analytic thinking, not to hit a word count.
How many memos should I write?
Glaser suggested writing memos freely and frequently. For a typical 20-interview study, 50-100+ memos across the project is reasonable. If you've written fewer than 20, you're probably not memoing enough. Quality matters more than quantity, but quantity is usually a sign of active analytic engagement.
Can memos be shared with stakeholders?
Selected memos, especially theoretical memos that explain how findings connect, can be valuable for stakeholders who want to understand not just what you found but how you got there. They demonstrate analytic rigor and make the reasoning behind recommendations transparent.