This document provides a comprehensive overview of analyzing qualitative data from UX research, focusing on thematic analysis as a widely used method. It outlines the significance of coding and theme development, detailing six steps for effective thematic analysis including familiarization with data, coding, and producing reports. The document emphasizes the importance of methodical analysis to uncover insights and patterns in qualitative data.

1. How to analyze
qualitative data from UX
research.
Thematic Analysis

2. Topic Overview
Today we will cover:
1. Qualitative Data Analysis
2. Thematic Analysis - What it is?
3. Code, Coding and Theme development
4. Six steps of thematic analysis.

3. Qualitative Data Analysis
• Qualitative data refers to non-numeric information such as interview transcripts, notes,
video, and audio recordings, images, and text documents. Qualitative research/analysis
involves collecting and analyzing non-numerical data to understand concepts, opinions, or
experiences. It's used to gather in-depth insights into a problem or generate new ideas for
research.
• Popular Qualitative Data Analysis methods are Grounded Theory Analysis, Content
Analysis, Framework Analysis, Discourse Analysis, Narrative Analysis, Interpretative
phenomenological analysis(IPA) & Thematic Analysis.

4. Thematic Analysis (TA)
• Thematic analysis (TA) is a widely used method of analysis in qualitative research. In 2006
Braun and Clarke published an article that described to novice researchers how to use
thematic analysis in a step-by-step manner. This is the most used research method in the field
of user experience (UX). Identifying the main themes in data from user studies (interviews,
focus groups, diary studies, and field studies, Secondary sources, etc.) is often done through
thematic analysis.

5. Key Terms: Code, Coding & Theme
• Code is a word or phrase that acts as a label for a segment of text. Code are the building
blocks of themes. Codes allow us to sort information easily and to analyze data to uncover
similarities, differences, and relationships among segments.
• Coding refers to the process of labeling segments of text with the appropriate codes.
• The theme is a description of a belief, practice, need, or another phenomenon that is
discovered from the data. Also, an idea or concept that captures and summarizes the core
point of a coherent and meaningful pattern in the data. (Braun and Clarke 2009).

6. Key Terms: Descriptive & Interpretive
Codes can be:
• Descriptive: They describe what the data is about.
• Interpretive: They are an analytical reading of the data, adding the researcher’s
interpretive lens to it.

7. Key Terms: Inductive & Deductive
Coding can be:
• Inductive coding (data driven coding) is a ground-up approach where you derive
your codes from the data. You don't start with preconceived notions of what the
codes should be, but allow the narrative or theory to emerge from the raw data
itself.
• Deductive coding is a top down approach where you start by developing a
codebook with your initial set of codes. This set could be based on your research
questions or an existing research framework or theory.
• Hybrid inductive & deductive coding.

8. Example

9. Methods for Conducting Thematic Analysis
3 common methods:
• Using software ( Atlas.ti, Nvivo, MAXQDA, etc.)
• Journaling
• Using affinity diagramming techniques

10. Steps for TA
There are total 6 steps of TA:
• Step 1: Familiarization with the data
• Step 2: Generate Initial Codes
• Step 3: Generate Themes
• Step 4: Reviewing Themes
• Step 5: Defining and naming themes
• Step 6: Producing the report

11. Step 1 - Familiarization with the data
• Gather all data, start with the raw data, such as an interview or focus-group
transcripts, secondary etc.
• Familiarize yourself with the data before you begin the analysis ( read everything A-
Z).

12. Step 2 - Generate Initial Codes
• If anything is important or interesting then highlight it and start coding the
statement. Avoid one word code try to use few words.
• After one member completes coding then pass the transcript to another member.
This step will be repeated until all the team members have engaged with all the data.

13. Step 3 - Generate Themes
• Gather and look across all the codes
and explore relationships,
similarities, differences,
contradictions to uncover underlying
themes/sub-theme (Group of Code or
labels for the data).
• Ask yourself the following questions
for generating themes. What’s going
on in each group? How are these
codes related? How do these relate to
my research questions?

14. Step 4 - Reviewing Themes
• It's a good idea to take a break and come back and look at the data with a fresh pair of
eyes.
• Review code by merging, re-arrange, and removing themes. Ask these questions. Is the
theme well supported by the data? Or could you find data that don’t support your theme?
Is the theme saturated with lots of instances? Do others agree with the themes you have
found in the data after analyzing the data separately?

15. Step 5: Defining and naming themes
• After completing the map, finally, we need to define and name those themes
(data friendly) . So that we could form a complete story for thematic mapping.

16. Step 6: Producing the report
• How to present results is very important (Key). Try to figure out a story that you
will tell with your result. The result includes narrative, insights, themes, how
they are related, and provide data extracts or quotes that provide evidence.

17. Questions & feedback?
• Note: The process is important because it drives the outcome.
If you have any question about this presentation or topic feel free to ask.
Ashphiar Raihan Rumman
Product Designer
Mail: rumman.octanex@gmail.com