> For the complete documentation index, see [llms.txt](https://ailyze.gitbook.io/ailyze-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ailyze.gitbook.io/ailyze-docs/methods-and-best-practices/qualitative-research-best-practices.md).

# Qualitative Research Best Practices

This page shows you how to use Evidano so your qualitative findings hold up to scrutiny. AI speeds up qualitative analysis, but it doesn't replace your judgment — these practices keep your work rigorous.

### 1. Prepare clean inputs

* Keep **one interview or group per file**, with **speaker labels** intact.
* Fix transcription errors first — garbage in, garbage out. Use the transcript editor.
* Give Evidano context: add your interview guide or framework in the optional **Instructions** section so [themes](/ailyze-docs/reference/glossary.md#theme) line up with your study.

### 2. Treat AI themes as a first draft

* Generate themes with AI, then *curate* them: rename, merge, split, and define each [code](/ailyze-docs/reference/glossary.md#sub-theme) in the codebook editor.
* Add a description to every code so labeling stays consistent and auditable.
* Don't accept the [codebook](/ailyze-docs/reference/glossary.md#codebook) just because it looks plausible — check it against your data.

### 3. Stay close to the data

* Read the [quotes](/ailyze-docs/reference/glossary.md#quote), not just the counts. A high [frequency](/ailyze-docs/reference/glossary.md#frequency) with weak quotes is a weak theme.
* Use the [co-occurrence network](/ailyze-docs/reference/glossary.md#co-occurrence-network) and [hierarchy graph](/ailyze-docs/reference/glossary.md#hierarchy-graph) to see relationships, not just how often something comes up.

### 4. Look for disconfirming evidence

Confirmation bias is the enemy. Use the [chat](/ailyze-docs/analyze-data/chat-with-your-data.md) to ask questions like *"What evidence contradicts theme X?"* and *"Which participants don't fit this pattern?"* Then report the nuance.

### 5. Check reliability

* Run **"Calculate AI Accuracy"** *(Pro)* to gauge how consistently the codebook was applied.
* Open the **"AI Labels as Checklist (with code justifications)"** tab to see *why* the AI assigned each code.
* For high-stakes work, have a second researcher review a sample.

### 6. Be transparent about method

* If you publish, name your [methodology](/ailyze-docs/reference/glossary.md#methodology) and describe how you used AI (it suggested themes; you curated them), your codebook, and your validation steps.
* Keep your codebook and exports as an audit trail. Reuse it across waves with **"Use Previous"** for consistency.

### 7. Handle quotes and people ethically

* Verify every quote against the source before you publish it.
* Anonymize: turn on personal-information (PII) redaction on transcripts, and be careful with the **Respondent Name/ID** field.
* Get consent for recording and analysis, and mind GDPR (the EU data-privacy law) and IRB (ethics-review board) requirements.

### 8. Mind sample size when comparing

Small [segments](/ailyze-docs/reference/glossary.md#segment) make for noisy comparisons. Don't over-interpret a difference in a group of five. See [Compare groups](/ailyze-docs/analyze-data/compare-groups-segments.md).

### A credibility checklist

* [ ] Inputs cleaned and given context
* [ ] Codebook curated, defined, and saved
* [ ] Quotes read and verified
* [ ] Disconfirming evidence sought
* [ ] Reliability checked
* [ ] Method and AI use documented
* [ ] Consent and anonymization handled

## Next steps

* [Build a codebook](/ailyze-docs/analyze-data/build-a-codebook.md)
* [Discover themes and patterns](/ailyze-docs/analyze-data/discover-themes-and-patterns.md)
* [Reporting findings](/ailyze-docs/methods-and-best-practices/reporting-findings.md)
* [Analysis issues](/ailyze-docs/troubleshooting/analysis-issues.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://ailyze.gitbook.io/ailyze-docs/methods-and-best-practices/qualitative-research-best-practices.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.