How to code qualitative data using Braun & Clarke’s Reflexive Thematic Analysis (RTA)

If you’re using Braun and Clarke’s reflexive thematic analysis, coding is often the stage where things start to feel overwhelming.

Questions start piling up:

What exactly counts as a code?

How detailed should my coding be?

Am I coding too much… or not enough?

How do I know if I’m doing it “right”?

If you’ve ever looked at your transcripts and thought “I have absolutely no idea what I’m doing”, you are not alone.

Coding is one of the stages that most qualitative PhD researchers struggle with.

The good news is that coding in reflexive thematic analysis (RTA) doesn’t require perfection. It’s an exploratory and interpretive process.

In this blogpost, we’ll walk through:

  • what coding is in thematic analysis

  • how to code qualitative data step-by-step

  • examples of coding in reflexive thematic analysis

  • common mistakes to avoid

If you want a full overview of Braun and Clarke’s approach, you might also find my structured framework helpful - Braun & Clarke Reflexive Thematic Analysis Guide.

What is coding in thematic analysis?

In Braun and Clarke’s reflexive thematic analysis, coding is the process of identifying meaningful features in your qualitative data.

You label segments of data with codes that capture something interesting, relevant, or conceptually important.

Think of coding like placing tags or labels on parts of your data.

Each tag marks something that might matter for answering your research question.

For example, imagine a participant says:

“I felt ignored during meetings.”

Possible codes might include:

  • exclusion

  • feeling overlooked

  • lack of communication

The code captures one aspect of meaning in the quote.

It’s not the full interpretation yet. It’s simply identifying something that may later contribute to a theme.

Coding in reflexive thematic analysis is interpretive

One important thing to understand about reflexive thematic analysis is that coding is not mechanical.

You are not simply categorising words. You are interpreting meaning.

Different researchers might code the same quote differently, depending on their research question, theoretical perspective, and analytic focus.

For example:

Quote:

“The training sessions were confusing and I didn’t know who to ask for help.”

Possible codes:

  • lack of clarity

  • organisational support issues

  • confusion about procedures

  • unclear training processes

All of these could be valid.

Coding in qualitative research is not about finding the single correct answer. It’s about developing interpretations that help you understand the phenomenon you’re studying.

Step-by-step: How to code qualitative data

In Braun and Clarke’s framework, coding usually happens during Phase 2 of thematic analysis.

Here is a simplified version of the process.

Step 1: Familiarise yourself with the data

Before coding, you need to become deeply familiar with your dataset.

This usually involves:

  • reading transcripts several times

  • noting early observations

  • identifying interesting patterns

Coding works best when you already have a strong sense of what your data is about.

Step 2: Identify meaningful segments of data

Next, start identifying parts of the data that feel relevant to your research question.

These might be:

  • sentences

  • phrases

  • paragraphs

  • short extracts

You are looking for segments that express something meaningful about the experience, process, or phenomenon you are studying.

Step 3: Assign a code

Once you identify a meaningful segment, attach a label that captures its meaning.

Example:

Participant quote:

“I really appreciated how my manager checked in with me regularly.”

Possible codes:

  • feeling supported

  • regular managerial contact

  • workplace support

  • feeling valued

Each code highlights a slightly different interpretation.

That’s completely normal in reflexive thematic analysis.

Step 4: Continue coding across the dataset

Work through your data systematically.

You may generate dozens or even hundreds of codes depending on your dataset size.

Don’t worry about perfection at this stage.

The goal is to capture interesting patterns, not to create the final structure.

Coding evolves during analysis

One of the biggest misconceptions about coding is that your initial codes need to be perfect.

They don’t. Coding evolves as your understanding deepens.

For example:

Original quote:

“The training sessions were confusing and I didn’t know who to ask for help.”

Initial codes:

  • confusion

  • lack of guidance

  • lack of support

Later in the analysis you might refine these.

Perhaps:

  • confusion

  • lack of organisational clarity

Or you might split codes into:

  • lack of technical support

  • lack of emotional support

This kind of revision is a normal part of reflexive thematic analysis.

Common coding mistakes in thematic analysis

Overcoding

You don’t need to code every single line.

Some data simply won’t be relevant to your research question.

Focus on meaningful segments, not every word.

Using vague codes

Avoid codes like:

  • “miscellaneous”

  • “other”

  • “general comment”

Even if your code feels messy or imperfect, give it a specific descriptive label.

You can refine it later.

Confusing codes with themes

This is one of the most common mistakes.

Codes and themes are not the same thing.

Codes are small units of meaning.

Themes are broader patterns that connect multiple codes together.

Think of it like this:

Codes = puzzle pieces
Themes = the picture created when pieces connect

Coding for hours without breaks

Coding is cognitively demanding work.

Many qualitative researchers experience coding fatigue.

Take regular breaks.

Some of the biggest insights in qualitative analysis often happen away from the screen.

Want step-by-step support with Braun & Clarke’s Reflexive Thematic Analysis?

If you’re using Braun and Clarke’s reflexive thematic analysis in your qualitative research, coding is only one part of the process.

Many PhD researchers find it challenging to connect all the stages together - from familiarisation, to coding, to theme development, and finally writing up the analysis clearly.

That’s exactly why I created my Braun & Clarke Reflexive Thematic Analysis Guide.

It’s a practical, step-by-step guide designed specifically for qualitative PhD researchers. Inside, you’ll find structured guidance and worksheets that help you:

  • move from raw qualitative data to meaningful codes

  • develop strong, coherent themes

  • understand what reflexive thematic analysis actually requires

  • avoid common mistakes in qualitative analysis

  • confidently explain your analytic process in your thesis

Instead of second-guessing every stage of the analysis, you’ll have a clear roadmap to follow.

You can explore my Braun & Clarke Reflexive Thematic Analysis Guide here.

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If you’re navigating qualitative research and want practical guidance on, thematic analysis, thematic literature reviews, research paradigms, and qualitative PhD writing, you might also like to join my email community. You can sign up here - Join the Degree Doctor email community.

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