Thematic analysis explores patterns of meaning within qualitative research data. Thematic analysis is a qualitative research approach that involves the identification of themes in data. Themes are identified through the use of extended codes, which are assigned to research content based on similarities. These thematic codes tend to be more of a phrase than other codes. These themes aim to indicate what a section of data is about and how the researcher is interpreting the data. In UX research, thematic analysis is often used to gain a better understanding of user needs, behaviors, and experiences by analyzing qualitative data such as user interviews or open-ended survey responses.
There is no one way to conduct thematic analysis - different approaches can be used depending on the researcher's preferences and needs. There are several different approaches to thematic analysis, with the two main approaches being categorically and phenomenologically (Saldana p259).
Thematic analysis is often used to explore data that is rich in meaning and context. From Clarke, Braun, and Hayfield, thematic analysis is appropriate for research around: Participants' experiences, participants' perspectives, social factors around specific phenomena, participants' practices, representations of topics and contexts, and social construction of a topic.
The Benefits of a Thematic Analysis
Reflexive approaches to thematic analysis allow for greater flexibility in coding and theme development. Flexibility is a main strength because it can be used with different research approaches. Thematic methods for coding are used by mixed method studies for quantitative data results to compare and relate to themes discovered during qualitative data analysis. Thematic analysis is a good fit to help research teams see related topics across large sets of data.
How to Conduct a Thematic Analysis
Thematic analysis can be conducted with or without a specific method to guide the process. Using a thematic analysis method ensures less subjectivity in coding and pattern identification, which contributes to the trustworthiness of results.
Let's have a look at Brauns' 6 phase approach to reflexive thematic analysis:
- Becoming familiar with the data: Review, and re-read the data to get beyond surface interpretations of the data. Focus on the data and not on researcher's prior conceptions, unless you are using a deductive approach guided by pre-existing theory.
- Generating codes: Explore both overt (semantic) and implicit (latent) meaning in the data and assign codes to later retrieve important data and generate themes. This should be an iterative process, codes can be updated each time the data is reviewed to further refine them.
- Generating initial themes: Review how the codes combine to create overall themes in the research. Themes are going to be more descriptive than codes and are likely in the form of phrases to describe ideas.
- Reviewing themes: It's always good to review your initial themes, you will want to go over the themes to ensure they didn't drift from the data's big picture and that they form coherent patterns. You may find you combine, add, or delete themes. You can compare the themes against the coded data as well as the entire data set.
- Defining and naming themes: This is where you will define and refine your themes for presentation in the final analysis. You can create sub-themes but beware of fragmenting your analysis too much (Clarke & Braun p84-103). Provide a description for each theme.
- Producing the report: Since we are focused on UX research, this would be sharing insights, instead of a "report" since reports are often not the best way to evangelize research results in an organization like a company. These should tie back to your original research questions.
Why Use a Thematic Analysis Approach
Thematic analysis methods are often used by researchers who seek to understand participants' experiences, social factors around specific phenomena, participants' practices, and representations of topics and contexts. It can be used with a variety of research methods, including mixed methods to discover across qualitative and quantitative data. User researchers should consider using thematic analysis for several reasons:
- Provides a deeper understanding of user experiences: Thematic analysis allows researchers to gain insights into the underlying meaning and context of user experiences. This can help researchers to identify patterns, trends, and key themes that may not be apparent through quantitative data alone.
- Helps identify areas for improvement: By analyzing qualitative data using thematic analysis, researchers can identify pain points and areas for improvement in the user experience. This information can be used to inform design decisions and ultimately create a better product or service.
- Complements other research methods: Thematic analysis can be used alongside other research methods such as surveys or usability testing to provide a more complete understanding of user needs and behaviors.
- Enables triangulation of data: Triangulation involves using multiple sources of data to confirm or refute findings from one source. Thematic analysis can be useful in triangulating data because it allows researchers to analyze qualitative data alongside quantitative data, providing a more comprehensive view of the research question.
- Supports iterative design: Thematic analysis helps researchers to identify themes and patterns that can guide iterative design. By analyzing user feedback through thematic analysis, researchers can identify areas for improvement and make changes to the product or service in response.
Overall, thematic analysis is a valuable tool for user researchers because it helps to uncover insights that may not be apparent through other research methods. By using thematic analysis alongside other research methods, researchers can gain a more comprehensive understanding of user needs and behaviors, which can inform design decisions and ultimately create a better user experience.
A High Level Example of Thematic Analysis
Here is an example of how thematic analysis can be used in user research:
Let's say a UX researcher is conducting a study to understand how users feel about a new mobile app that helps people track their fitness goals. As part of the study, the researcher conducts several user interviews and asks participants about their experiences using the app.
After transcribing and reviewing the interview data, the researcher begins to identify common themes that emerge from the interviews. For example, several participants mention feeling overwhelmed by the amount of data presented in the app, while others express frustration with how difficult it is to navigate certain features.
The researcher continues to analyze the data using thematic analysis and identifies several key themes:
- Overwhelming amount of data: Many participants felt that there was too much information presented in the app, making it difficult to focus on their specific fitness goals.
- Confusing navigation: Several participants had difficulty finding certain features within the app or understanding how to use them.
- Motivational aspects: A few participants mentioned that they appreciated certain motivational aspects of the app, such as receiving encouraging push notifications or being able to track progress towards their goals.
Based on these themes, the researcher is able to identify specific areas for improvement in the app's design. For example, the researcher may recommend simplifying the user interface, improving navigation, and adding more motivational features. These recommendations can then be used to guide iterative design and create a better user experience for the app's users.
Overall, this example demonstrates how thematic analysis can be used in user research to uncover insights about user experiences and inform design decisions. By analyzing qualitative data using thematic analysis, researchers can identify patterns and themes that may not be apparent through quantitative data alone.
In conclusion, thematic analysis is a powerful qualitative research method that can be used to uncover patterns and themes within user data. By analyzing qualitative data through thematic analysis, UX researchers can gain a deeper understanding of user experiences and perspectives, identify areas for improvement in product design, and generate insights that may not be apparent through quantitative data alone. Thematic analysis is particularly useful for identifying patterns and trends within open-ended responses from user surveys or interviews. This approach allows researchers to develop a more nuanced understanding of user needs and behaviors, which can ultimately lead to the creation of better products and services that meet the needs of their users.