Thematic analysis
What it is
Thematic analysis is a method of analysing qualitative data such as transcripts from interviews or free-text survey responses to uncover patterns in meaning and derive themes.
Why this method
This type of analysis is a flexible and simple approach that generates new insights from the data set. This is particularly effective with used in conjunction with quantitative data analysis to make sense of trends and comparisons with specific user input.
How to use
- Familiarise yourself with the data you have collected. If needed, transcribe your interview or survey data first. Remove null responses and exclude responses from your analysis such as "nothing" "N/A" or "don't know".
- Start to establish a set of initial codes or themes that reflect the observed patterns in the data and develop theories based on the frequency of responses within each code category and their relationships. Simple techniques such as colour coding, tagging, and sorting can be used for short responses. You can use Excel to do this step or advanced software such as NVivo, R, or Power Bi AI tools.
- Group together all the excerpts associated with a particular code or theme.
- Review your results again, and sort codes or themes into larger groups or even sub-themes if applicable. Ensure each theme has enough data to support them and is distinct. Consider merging themes if they are similar or removing themes with not enough data to back them up.
- Ensure you are subjective through this process but specifically at this step. You can also pull others to help you with thematic analysis to avoid biases when sorting data.
- Write a narrative report or visualise this data along with quantitative data. Make sure you are telling a coherent story about what you have learned and pull quotes where necessary. Include your interpretive analysis and be prepared to back up the claims you present.