Thematic analysis is the most widely used method for analysing qualitative data such as interviews, focus groups and open survey answers. NVivo makes the process faster and easier to document, but the software does not analyse your data for you. This guide combines the six phases of thematic analysis from Braun and Clarke with the practical steps in NVivo.
Before you start
- Transcribe your interviews consistently and remove identifying details to protect participants.
- Decide whether your analysis will be inductive (themes built from the data) or deductive (codes guided by a theory or framework), or a mix of both.
- Keep your research question visible. Every theme should help answer it.
Phase 1: Familiarise yourself with the data
Read every transcript at least once before coding anything. Note first impressions, surprising comments and recurring ideas.
In NVivo: create a new project and import your transcripts under Data > Files. Use Memos to record your early thoughts, and link each memo to the relevant file. Memos become valuable evidence of reflexivity when you write your methodology.
Phase 2: Generate initial codes
A code is a short label for a meaningful segment of data, such as “fear of isolation” or “flexibility as reward”. Work through each transcript systematically and code everything relevant to your question. A passage can have more than one code.
In NVivo: select text and drag it onto an existing code, or right-click and choose Code Selection to create a new one. Turn on coding stripes to see which codes you have applied to each passage. Expect dozens of codes at this stage; that is normal.
Phase 3: Generate initial themes
A theme captures a broader pattern of shared meaning across the dataset. Look at your codes and group the ones that tell part of the same story. For example, “fear of isolation”, “missing informal chat” and “harder to ask for help” might form an initial theme called “Losing the social fabric of work”.
In NVivo: create a parent code for each candidate theme and drag related codes underneath it to build a hierarchy. The Hierarchy Chart and Mind Map tools help you see the structure visually.
Phase 4: Review themes
Check each theme on two levels. First, do the coded extracts within it fit together? Second, does the theme reflect the dataset as a whole? Some themes will merge, some will split and some will be discarded.
In NVivo: open each parent code and read all of its references in one place. A Matrix Coding Query is useful for comparing themes across participant groups, for example managers versus employees, once you have set up case classifications with attributes such as role or gender.
Phase 5: Define and name themes
Write a short definition of each theme: what it is about, what it is not about and how it relates to your research question and to the other themes. Choose names that are concise and informative. “Losing the social fabric of work” tells the reader more than “Social issues”.
In NVivo: add each definition to the code’s Description field so your definitions and data stay together.
Phase 6: Write the report
Your findings chapter should present each theme as an argument, supported by vivid, well-chosen quotations. A good pattern for each theme is:
- State what the theme is and why it matters.
- Explain how it showed up across participants.
- Support it with two or three short quotations, attributed with pseudonyms or codes such as P4.
- Interpret what it means in relation to your research question and the literature.
Include a table or thematic map summarising your themes and sub-themes. NVivo can export code books and charts to support this.
Reflexive thematic analysis
Braun and Clarke now describe their approach as reflexive thematic analysis. They emphasise that themes are actively developed by the researcher, not passively “discovered” in the data. In practice, this means you should:
- Acknowledge your own position and how it may shape your interpretation.
- Avoid claiming that themes simply “emerged”.
- Not rely on inter-rater reliability scores, which fit coding reliability approaches rather than reflexive analysis.
Citing their more recent work (Braun and Clarke, 2019; 2021) alongside the original 2006 paper shows examiners you understand the method’s current form.
Common mistakes
- Presenting interview questions as themes
- Themes that are just topic summaries with no central idea
- Too many themes for the length of the thesis; three to six is typical
- Long quotations with little interpretation
- No explanation of how codes became themes in the methodology chapter
Need help coding your interviews or turning codes into convincing themes? Our qualitative analysis specialists work with NVivo and QDA Miner Lite and can guide you through each phase.