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Qualitative analysis and coding

Code open-ended responses with AI assistance, build theme hierarchies, and measure intercoder reliability.

QuestionPunk includes a built-in workspace for coding open-ended and AI interview responses. Run AI-assisted coding sessions, organize codes into theme hierarchies, measure intercoder reliability, and export coded data.

analysisqualitativecodingreport15-30 minutesIntermediate to AdvancedResearchersAcademicsAnalysts

Steps

  1. Open qualitative analysis
    Click Qualitative under Analysis in the sidebar to open a gallery of every study you have coded or imported, or, in a survey's Results > Analysis sub-tab, pick Qualitative coding from the switcher to open the same workspace scoped to that survey. You can also import open-ended data from outside QuestionPunk: upload a CSV, or connect a Qualtrics survey directly and pull in its text-entry questions.
  2. Set up a research framework
    In the Codebook tab, create an initial codebook. You can start with a blank codebook or let AI suggest codes based on your data.
  3. Run an AI coding session
    In the AI coding tab, start a coding session to have AI apply codes to your open-ended responses. The AI reads each response and assigns relevant codes from your codebook, suggesting new codes when it encounters themes not yet captured.
  4. Review and refine codes
    In the Read & code tab, review AI-assigned codes, accept or reject suggestions, and organize codes into theme hierarchies in the Codebook. Merge similar codes and split overly broad ones.
  5. Explore themes
    Use the Explore tab to look at how codes and themes are distributed across your responses and compare them between groups.
  6. Measure intercoder reliability
    In the Check coding tab, run intercoder reliability analysis to measure agreement between coders using Cohen's Kappa and Krippendorff's Alpha. Academic reviewers often ask for these figures.
  7. Export coded data
    Use the Export & audit tab to download a respondent-by-code matrix (CSV), the codebook (CSV), a REFI-QDA .qdpx project for NVivo, ATLAS.ti, or MAXQDA, a methods statement, or the full JSON research record.

Qualitative analysis in QuestionPunk bridges the gap between raw open-ended responses and structured research findings. AI-assisted coding accelerates the process while maintaining researcher control.

The workspace has eight tabs: Overview, Data sources, AI coding, Read & code, Codebook, Check coding, Explore, and Export & audit. It works both as a standalone, cross-survey workspace reached from the sidebar's Analysis section, and embedded in a native survey's Results tab alongside the Analysis sub-tab and Quantitative analysis.

The Data sources tab is not limited to native QuestionPunk surveys: import a CSV of open-ended responses, or connect directly to a Qualtrics survey and select which text-entry questions to bring in for coding.

Theme hierarchies let you organize codes into parent-child relationships, making it easy to analyze data at different levels of abstraction.

The methods statement in Export & audit records how coding was done. It does not claim theoretical saturation; that judgment stays with you.

Intercoder reliability metrics (Cohen's Kappa and Krippendorff's Alpha) provide quantitative measures of coding consistency, which is a requirement for publishable qualitative research.

Add analytic memos to document your analytical decisions and keep a record of your coding process.