# How to analyse focus group data — from transcribing sessions to coding group dynamics, comparing across groups, and writing up. Includes a worked example.

Focus group analysis is the process of working through recorded group discussion data to identify themes, areas of agreement and disagreement, and findings that reflect how a group collectively makes sense of a topic. The core steps are: transcribe the recordings with speaker attribution, read for overall impression, code both the content and the group dynamics, compare findings across multiple groups, and write up with explicit attention to how the group interaction shaped what was said. The key difference from [individual interview analysis](https://skimle.com/interview-transcript-analysis) is that the unit of analysis is the group, not the individual — which means the social and conversational dynamics are data, not background noise.

This guide covers the full process, including a worked example, common mistakes, and how AI tools can assist with the content analysis while you focus on the interpretive work that requires human judgement.

# Why focus group analysis is different

The method shapes the data. Focus groups produce material that one-to-one interviews do not, and analysing it as if it were a set of individual interviews produces weaker findings.

The distinctive features of focus group data are:

**Collective meaning-making**: participants build on each other's contributions, correct each other's framing, introduce ideas others take up and extend. The analysis needs to capture these dynamics, not just the individual utterances.

**Social influence**: what participants say in a group is shaped by who else is in the room. Positions are moderated by social pressure, norms of the group, and the presence of authority figures. This is partly why focus groups are limited for sensitive topics — but when the phenomenon you are studying is itself social, it is analytically valuable.

**Consensus and dissent**: groups often produce a surface-level consensus that can be misleading. One or two vocal participants can make a majority view out of what is actually a minority position. Equally, dissenting voices are sometimes suppressed and may only emerge in how participants qualify their agreement. Both are worth tracking.

**Turn-taking and sequence**: who said what in response to whom matters. A comment made after a strong intervention from a dominant participant means something different from the same words said spontaneously at the start of the discussion.

For a deeper treatment of the unique challenges of focus group transcripts, see [how to analyse focus group transcripts](https://skimle.com/how-to-analyse-focus-group-transcripts). This guide focuses on the broader analysis process, from setup to write-up.

Read the full guide here: [https://skimle.com/blog/focus-group-analysis](https://skimle.com/blog/focus-group-analysis)

Signal & Noise: Focus group analysis: a complete guide