When it comes to research, gathering data is only half the battle. The actual value lies in uncovering hidden patterns in the data and unlocking meaningful insights. One of the leading research methods for this is thematic analysis, a tool for making sense of complex narratives.
However, with several available approaches to thematic analysis, which method best suits your research goals?
In this article, we discuss the 7 types of thematic analysis and provide examples to help you understand them in detail.
TL;DR – Types Of Thematic Analysis
In a rush?
Here’s a list of thematic analysis approaches:
- Inductive thematic analysis
- Deductive thematic analysis
- Semantic thematic analysis
- Latent thematic analysis
- Reflexive thematic analysis
- Codebook thematic analysis
- Coding reliability thematic analysis
Whichever method you use, there will be a ton of data. So, how do you turn messy data into meaningful insights?
With Marvin, your thematic analysis will be much easier, whether you’re a student, researcher, or professional. It is an AI research assistant tool that automatically transcribes your interviews, identifies key themes, and categorizes the insights. It reduces the time and effort you spend manually coding and analyzing qualitative data.
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What Is Thematic Analysis?
Thematic analysis is a research method of analyzing qualitative data and spotting patterns (themes) to help you understand what your respondents say.
It’s like detective work, but for researchers, where they uncover hidden insights within all that content and imagery.
For example, businesses can analyze customer feedback, reviews, and social media posts to identify moments of disappointment, performance concerns, or missing features in a specific product.
Why Use Thematic Analysis in Qualitative Research
Have you ever been swimming in a sea of qualitative data and unsure where to begin?
Let’s see how thematic analysis jumps in as a life raft:
- Provides a Structured Framework: It provides a straightforward process to make sense of large volumes of data and identify patterns.
- Applicable in Different Contexts: It appeals to researchers who want to access disciplines like marketing, UX, HR, and health.
- Applicable to Various Data Sources: Thematic analysis is a consistent approach to spotting recurring trends and sentiments, whether using interviews, surveys, or social media mentions.
- Compatible with AI: If you want to automate your thematic analysis, you can use AI research tools like Marvin to cut the costs and time you spend on manual coding and improve the accuracy of your insights.
- Rich Insights: Thematic analysis can help you identify qualitative and quantifiable patterns in your research and deeply understand complex scenarios.
Different Types Of Thematic Analysis
Thematic analysis can be done with different approaches, each with its own structure and purpose.
Let’s break them down to see which one will work for your project:
1. Inductive Thematic Analysis
Also known as bottom-up or data-driven thematic analysis, it is based on grounded theory. In this method, you can explore patterns that come directly from data.
Use When: You want to generate insights or understand data without a pre-existing theoretical framework.
2. Deductive Thematic Analysis
Unlike the inductive method, deductive analysis (top-down or theory-driven thematic analysis) starts with a theoretical framework derived from existing literature and studies. You can explore existing concepts and see how they manifest in your data.
Use When: You are on subsequent analysis and already have predetermined codes/themes.
3. Semantic Thematic Analysis
Rather than interpreting the hidden meanings of data, this approach focuses on what is directly stated.
Use When: You want to organize feedback into actionable insights, making summarizing and presenting your findings easy.
4. Latent Thematic Analysis
Unlike semantic analysis, this approach goes below the surface-level meanings to find underlying meanings and assumptions in the collected data.
Use When: You want to focus on what is implied rather than stated.
5. Reflexive Thematic Analysis
This type of thematic analysis acknowledges the subjective perspective, bias, and interpretation of the researcher with the data.
As a researcher, you must reflect and consider how your background and experiences might influence your data analysis and the outcome.
Use When: You want to explore sensitive or complex topics, allowing you to understand the participants’ experiences and meanings.
6. Codebook Thematic Analysis
This approach lets you create and apply a defined codebook (framework) to analyze data. The codebook contains (or includes) predefined codes and their definitions, themes, and relevant concepts.
Use When: You want a structured way of analyzing data and ensuring consistency in coding across multiple researchers and datasets.
7. Coding Reliability Thematic Analysis
In this approach, multiple coders independently work on the same dataset based on a predefined codebook.
Use When: You want trustworthiness in the findings by demonstrating consistency in coding.
Note: When choosing the best thematic analysis approach, you should consider your objectives, the nature of your research, and the flexibility you’re looking for in your analysis. Sometimes, the most insightful research can emerge from skillfully combining elements of these approaches, where appropriate.
Inductive vs. Deductive Thematic Analysis
Although we’ve discussed several approaches above, inductive and deductive thematic analysis are the most popular ones for identifying patterns and meaning.
So, in this section, we’ll look at their distinct ways to uncover meaning.
Let’s break them down below:
| Criteria | Inductive Thematic Analysis | Deductive Thematic Analysis |
| Definition | Researchers develop themes from data without a pre-existing framework | Researchers create themes from existing theories or frameworks |
| Based On | Raw data | Pre-existing theories or literature |
| Flexibility | Open and highly flexible | Structured and efficient |
| Risks | Overload of data and might lack structure | Missing unexpected insights while trying to fit data into predefined theories |
| Best For | Exploratory research | Testing hypotheses, confirming theories, or comparing studies with existing literature |
How to Conduct Thematic Analysis with Confidence
Not sure how you should dive into thematic analysis?
Here’s our step-by-step guide to help you master thematic analysis for your qualitative research:
Step 1: Familiarize Yourself with Data
You should know the data you have collected before analyzing it. Sometimes, you might need to transcribe the audio or take initial notes.
Step 2: Assign Initial Codes
Next, you should highlight phrases and sentences (codes) that capture key aspects of your text, ideas, or feelings.
For example, if your research concerns working mothers, you can develop codes like ‘loss of identity’ and ‘work-life balance’ for interview extracts, such as ‘there is never enough time in a day to be a good mother and employee.’
Step 3: Group Codes into Themes
At this stage, you should review the codes you’ve created, identify patterns, and develop themes (usually a combination of several codes).
In our example, you can turn the codes we created into a theme like ‘balancing motherhood and career.’ You could also discard the codes that are too vague or irrelevant.
Step 4: Review the Themes
You want to be thorough here. Ensure that each code accurately describes the feeling or idea in the highlighted text. Check if anything is missing and what you can change in your theme, such as splitting, combining, or creating new ones, to make them even more helpful.
At this stage, you should also come up with easily understandable names for each theme.
Step 5: Write Up a Report
Finally, create a comprehensive report detailing your thematic analysis. You should include the introduction and the methodology you used to collect data. You should also have a section with the results or findings of each theme and what they mean.
Lastly, you should have a conclusion section with the main takeaways and whether the analysis answered the research question.
Although it sounds easy, conducting thematic analysis can be tiresome. Consider using an AI tool to identify actionable themes without second-guessing. Say goodbye to tedious manual transcription, coding, and report generation.
With the Marvin AI assistant research tool:
- You can effortlessly get smart summaries that capture your themes.
- Identify patterns and get insights in minutes.
- Analyze sentiments and categorize responses with built-in AI analysis.
Book a demo with Marvin now and experience the power of smarter thematic analysis!
Thematic Analysis Example to Deepen Understanding
Let’s use these interview excerpts to give thematic analysis some context:
Interviewee A: ‘Remote working is convenient because I can work from anywhere. But I often get distracted at home. It’s also hard to stay motivated without seeing my colleagues.’
Interviewee B: ‘I love the flexibility of remote working. However, I feel isolated, and I miss team discussions.’
Interviewee C: ‘It’s great to work at my own pace. But I struggle with technical issues and sometimes feel disconnected from the company.’
Let’s generate some initial codes:
- Convenience
- Flexibility
- Distractions at home
- Lack of motivation
- Isolation
- Missing social interaction
- Self-paced working
- Technical difficulties
- Disconnection from the company
Let’s group similar codes into broader themes. We shall then name and refine the themes. Below is a breakdown of this process:
| Original Theme | Associated Initial Codes | Renamed Theme Names |
| Theme 1: Convenience | Convenience Flexibility | Freedom and control over working |
| Theme 2: Social Challenges | Lack of motivation Missing social interaction Disconnection from the company | Emotional disconnection and social isolation |
| Theme 3: Possible Barriers | Technical difficulties Distractions at home | External barriers that affect working |
The conclusion: The participants highlighted freedom and control over work as the main advantages of remote working. However, it also has disadvantages, such as emotional disconnection and social isolation. Additionally, external barriers pose possible challenges to their working experience.
Real-World Examples: Here is how Field Nation, an IT labor marketplace, used our software to analyze 20 hours of data, capture key notes, and find themes. It then used the insights in product designs.
Frequently Asked Questions (FAQs)
We understand that thematic analysis can feel overwhelming, so we’ve compiled answers to the most common questions to make things easier.
What Is the Best Way to Start a Thematic Analysis Research Project?
The best way to start a thematic analysis research project is to become thoroughly familiar with the data, generate initial codes, and subsequently group these codes into themes.
What Are the Common Mistakes in Thematic Analysis?
Here are some of the common mistakes that might indicate you might be doing your thematic analysis wrong:
- Treating thematic analysis as a simple word search and assuming frequently appearing phrases represent key data.
- The researcher gets biased and brings their perspectives into the coding and theme creation process.
- Creating themes that are simply labels and don’t provide in-depth interpretation.
- Generating themes that are either too few, so that the analysis risks being general, or too many, so that they are difficult to conclude from.
- Not explaining how themes were chosen from the data.
To counteract these challenges, you can use Marvin to code and create themes and automatically reduce individual biases. Our software also allows real collaboration with your colleagues to provide a fresh perspective and ensure the conclusions are credible and meaningful.
How Can We Present Themes in Qualitative Research?
Some of the ways to present themes include:
- A table with an overview of the themes, the description, and the key codes.
- Flowcharts and mind maps that show a visual representation of the themes and codes.
- Case studies or storytelling that incorporate the themes.
- Quotes in the transcripts, along with their interpretation.
Conclusion
Thematic analysis is the perfect fit for any data format applicable in different industries, including UX and healthcare. These approaches can help you understand and interpret qualitative data to make better business decisions.
To recap the process, understand the data you’ve collected, create the initial codes, and turn the codes into themes. You should also review the themes and write a report.
Feeling overwhelmed?
With our intuitive software, Marvin, you can automatically transcribe and code your qualitative data in minutes, giving you time to focus on interpreting and implementing the insights.
Sign up for a free account and take charge of your research process!
