You’ve just spent weeks gathering rich customer feedback—interview transcripts, survey responses, support tickets. Now you’re staring at a mountain of text, wondering, “Where do I even begin?”
This is a common challenge for customer experience professionals. You’ve done the hard work of listening to your customers, but now you need to turn that raw data into a clear, compelling story that drives action. Without a systematic approach, it’s easy to get lost in the details, focus only on the most memorable (but not necessarily most important) quotes, or miss the deeper patterns that reveal what your customers truly need.
This is where thematic analysis comes in. It’s a straightforward, flexible method for cutting through the noise and finding the meaningful themes in your qualitative data. And the best part? Anyone can learn to do it.
Thematic analysis is a systematic process of organizing and interpreting qualitative data to identify and understand recurring patterns or ideas. In their influential 2006 paper, psychologists Virginia Braun and Victoria Clarke define it as a method for “identifying, analysing and reporting patterns (themes) within data”(1).
In simple terms, you’re looking for the big ideas that come up again and again in your customer feedback. A theme isn’t just a topic; it’s a specific, recurring concept that captures something important about your customers’ experiences, beliefs, or needs.
Thematic analysis revolves around two key concepts: codes and themes.
- A code is a short label you assign to a piece of data—a sentence, a phrase, or a paragraph. It’s like a hashtag that summarizes what that piece of data is about.
- A theme is a broader pattern of meaning that you identify by grouping related codes together.
Codes are the individual bricks, and themes are the walls you build with them. You start by labeling the individual pieces, and then you step back to see the larger structure that emerges.
Thematic analysis revolves around two key concepts: codes and themes.
- A code is a short label you assign to a piece of data—a sentence, a phrase, or a paragraph. It’s like a hashtag that summarizes what that piece of data is about.
- A theme is a broader pattern of meaning that you identify by grouping related codes together.
Codes are the individual bricks, and themes are the walls you build with them. You start by labeling the individual pieces, and then you step back to see the larger structure that emerges.
Let’s look at an example from a customer interview about a new banking app:
“I was so frustrated. I tried to transfer money to my son for his rent, and I kept getting this cryptic error message. I had to call customer support, and it took me 20 minutes just to get through to someone. By the time I was done, I was ready to switch banks.” Here’s how you might code this passage:
- Descriptive codes: “error message,” “long wait time,” “frustration”
- Interpretive code: “channel escalation due to failed self-service”
The descriptive codes capture the facts of the story. The interpretive code connects those facts to a broader CX concept, providing a more analytical lens.
While there are many ways to approach thematic analysis, the six-phase process developed by Braun and Clarke is a great starting point (1). You can do this process using specialized software (like Dovetail or NVivo), or with simple tools like spreadsheets, digital whiteboards, or even just sticky notes and a wall.
Step 1: Get to Know Your Data
Before you start analyzing, you need to immerse yourself in the data. Read through all your transcripts, notes, and other documents from beginning to end. Get a feel for the content and start jotting down initial ideas. This is a great activity to do with your team to build shared empathy and understanding of the customer.
Step 2: Generate Initial Codes
Now, go through your data systematically and assign codes to segments of text. Don’t worry about getting it perfect at this stage; just try to capture the essence of what’s being said. This is often called “open coding”(2). As you go, keep a running list of your codes and their definitions to ensure consistency.
Step 3: Search for Themes
Once you have a list of codes, start looking for patterns. Which codes seem to go together? Are there any overarching ideas that connect multiple codes? Start grouping your codes into potential themes. A great way to do this is with affinity diagramming, where you write your codes on sticky notes and physically move them around on a wall or digital whiteboard to create clusters(3).
Step 4: Review Your Themes
Now it’s time to refine your potential themes. Look at the codes within each theme. Do they form a coherent pattern? Then, look at the themes in relation to your entire dataset. Are they a good representation of the data? You may need to split, combine, or discard themes at this stage. This is a critical step for ensuring the quality and validity of your analysis.
Step 5: Define and Name Your Themes
Once you have a final set of themes, you need to clearly define what each one means. Write a detailed description of each theme, explaining the story it tells and how it relates to your research questions. Give each theme a short, memorable name that will be easy for your stakeholders to understand.
Step 6: Write Your Report
Finally, it’s time to tell the story. Your report shouldn’t just be a list of themes. It should be a narrative that weaves your themes together to answer your research questions and provide actionable insights. Use vivid quotes and examples from the data to bring your themes to life.
Thematic analysis is most powerful when it’s a team sport. Involving colleagues from different functions (like product, marketing, and engineering) in the analysis process has several benefits:
- It reduces bias. Everyone brings their own perspective and assumptions to the data. Analyzing as a team helps to challenge those biases and arrive at a more objective interpretation(4).
- It builds empathy. There’s no better way for your stakeholders to understand your customers than to engage directly with their feedback.
- It creates shared ownership. When your team is involved in creating the insights, they’re more likely to be invested in acting on them.
Qualitative data is a goldmine of customer insight, but only if you have the right tools to extract it. Thematic analysis provides a systematic, credible, and accessible way to move from a mountain of raw data to a clear, actionable story. By taking the time to listen deeply to your customers and find the patterns in their feedback, you can ensure that their voice is at the heart of every business decision.
(1) Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.
https://www.tandfonline.com/doi/abs/10.1191/1478088706qp063oa
(2) Tie, Y. C., Birks, M., & Francis, K. (2019). Grounded theory research: A design framework for novice researchers. SAGE Open Medicine, 7, 2050312118822927.
https://pmc.ncbi.nlm.nih.gov/articles/PMC6318722/
(3) Lucero, A. (2015). Using affinity diagrams to evaluate interactive prototypes. In IFIP Conference on Human-Computer Interaction (pp. 231-248). Springer.
https://link.springer.com/chapter/10.1007/978-3-319-22668-2_19
(4) Cornish, F., Gillespie, A., & Zittoun, T. (2014). Collaborative analysis of qualitative data. In The SAGE Handbook of Qualitative Data Analysis (pp. 79-93). SAGE Publications.
