Sifting through hundreds of interview transcripts, survey responses, and field notes?
For researchers, this mountain of qualitative data can feel overwhelming. Each video to transcribe, each conversation to analyze, and each response to categorize demands meticulous attention and countless hours.
This is where thematic analysis shines. It's a systematic method that helps researchers navigate through complex qualitative data to uncover meaningful patterns. By examining texts, interviews, and surveys, researchers identify recurring themes that tell a deeper story. These emerging patterns can either support existing theories or lay the groundwork for groundbreaking new insights.
In this article, we discuss the top 5 thematic analysis examples that will help you understand thematic analysis in detail.
What is thematic analysis?
Thematic analysis is a powerful qualitative research method that helps researchers systematically identify, analyze, and interpret patterns of meaning within data. Think of it as a sophisticated lens that brings clarity to complex information gathered from interviews, focus groups, written documents, or any form of communication.
Example: When analyzing interviews about people's hobbies, a product researcher might notice distinct patterns emerging. Some participants light up when discussing creative pursuits like painting or music; others become animated describing outdoor activities, while another group focuses on social hobbies. The thematic analysis process codes these individual responses and organizes them into broader themes that reveal deeper insights into how people find meaning and enjoyment in their leisure activities.
What makes thematic analysis valuable is its ability to transform raw, unstructured data into meaningful insights that can inform theory and practice. It's not just about counting occurrences of words or ideas—it's about understanding the underlying narrative that connects different pieces of information together.
There are several types of thematic analysis, including: Inductive (bottom-up approach)- Deductive (theory-driven approach)- Semantic (explicit meanings)- Latent (underlying meanings). Each type serves different research purposes and can be chosen based on your specific research goals.
Top 5 examples of thematic analysis
Thematic analysis helps researchers understand what people are talking about, what matters to them, and what trends appear across many pieces of information. Let’s look at 5 solid examples of how thematic analysis is used in different areas.
1. Patient experience in healthcare settings
Focus of research: How do patients perceive and experience their hospital care journey?
Thematic analysis example: A researcher conducts comprehensive user interviews with hospital patients, gathering their stories about care quality, staff interactions, and overall satisfaction during their stay.
Themes identified:
- Healthcare provider empathy: Patients consistently report more positive healing experiences when medical staff demonstrates genuine care and compassion. Simple acts of kindness, such as a nurse's gentle explanation or a doctor's attentive listening, significantly impact patient well-being.
- Communication quality: When hospital staff clearly explains treatment plans and medication instructions, patients feel more confident and satisfied. However, unclear communication or medical jargon often leads to frustration and anxiety among patients.
- Care coordination: The smooth transition between different departments and consistency in the care approach affect how patients view their overall hospital experience. When care feels coordinated, patients report higher satisfaction levels.
These identified themes help hospitals enhance their service quality, improve staff training programs, and create more patient-centered care approaches.
2. Social media trends on mental health
Focus of research: How do people discuss and share their mental health experiences on social media platforms?
Thematic analysis example: A researcher analyzes popular mental health hashtags on Instagram, examining posts, comments, and shared stories to understand how people express their mental health journeys online.
Themes identified:
- Mental health stigma: Content creators frequently share personal experiences of facing judgment or discrimination due to their mental health conditions. These narratives often highlight workplace stigma, family misunderstandings, and societal misconceptions about mental illness.
- Community support: Social media users emphasize the crucial role of online communities in their mental health journey. They describe finding acceptance, understanding, and encouragement through virtual connections with others sharing similar experiences.
- Professional intervention: Many posts discuss experiences with therapy and counseling, sharing both successes and challenges in seeking professional help. Users often emphasize how professional guidance helped them develop coping strategies and achieve better mental well-being.
These insights help mental health professionals better understand patient needs, improve outreach methods, and develop more effective support systems that complement traditional therapy approaches.
Learn about the Top 5 Tools for AI Thematic Analysis in 2025 in this blog.
3. Interaction of teachers and students in the classroom
Focus of research: How do teacher-student classroom interactions influence learning effectiveness?
Thematic analysis example: A researcher observes classroom dynamics over several weeks, documenting teaching methods, student responses, and learning outcomes to understand effective educational practices.
Themes identified:
- Psychological safety: Students demonstrate higher engagement and learning when they feel safe making mistakes and asking questions. The teacher's response to errors and questions significantly impacts student confidence and participation levels.
- Active engagement: Teachers who incorporate interactive discussions, hands-on activities, and collaborative projects see increased student participation and better retention of material. This engagement extends beyond traditional lecture-style teaching.
- Critical thinking development: Successful teachers encourage students to explore alternative explanations and challenge existing theories. When students feel empowered to question and explore ideas, like proposing different theories about dinosaur extinction, they develop stronger analytical skills.
These findings help educational institutions develop more effective teaching strategies, improve teacher training programs, and create learning environments that foster both academic success and student confidence. The insights directly contribute to enhancing teaching methodologies and student learning outcomes.
4. Employee feedback on work-life balance
Focus of research: How do employees perceive and manage their work-life balance in modern workplaces?
Thematic analysis example: A company conducts in-depth interviews with employees across departments to understand their experiences balancing professional responsibilities with personal life.
Themes identified:
- Schedule flexibility: Employees consistently report higher job satisfaction and productivity when they have control over their work hours. The ability to adjust schedules based on personal needs leads to improved performance and reduced stress levels.
- Professional burnout: Many employees describe experiencing exhaustion from extended work hours and high pressure, impacting both their work quality and personal relationships. They express difficulty disconnecting from work responsibilities during personal time.
- Workplace culture: The presence of understanding managers and supportive colleagues significantly impacts employee wellbeing. When team members show empathy and provide backup during personal emergencies, employees report feeling more valued and motivated.
These insights help organizations develop more effective workplace policies, improve employee retention, and create a more balanced work environment that benefits both the company and its workforce.
5. Customer Feedback on Apps
Focus of Research - What is the customer feedback on an app's functionality and features, and would they continue to use it?
Thematic Analysis in Qualitative Research Example - An app developer might seek to understand what makes their app desirable and user-friendly by utilizing an in-app survey, app store reviews, and an online survey.
Themes Identified:
- Ease of Use - The app design allows users to navigate different functions without confusion.
- Feature Requests - Users suggest additional features that could enhance the app's utility. For instance, implementing a dark mode in a gaming app could improve nighttime gaming experience.
- Notification and Reminders - Users desire customization options, such as a Do Not Disturb feature that allows muting notifications for specified hours.
This analysis empowers the app developer to make targeted improvements that can expand the app's reach and increase user satisfaction.
How to conduct thematic analysis?
Researchers often come across the question: what are the 5 stages of thematic analysis?
Here are the 5 steps of thematic analysis you can follow:
- Familiarization with the data: When you read the data thoroughly and understand what it contains.
- Generating initial codes: In the data that you possess, you identify the parts that are important and give certain codes to them for the study of an idea.
- Themes: Similar codes identified are grouped to form a theme, which helps create a data pattern.
- Reviewing themes: These themes are then rechecked to make sure they are relevant and in alignment with the research.
- Defining and naming themes: Define the themes that you find and label them in a way that explains the meaning behind each theme.
Thematic analysis becomes a lot more easier and simpler when you use modern UX research tools like Looppanel.
Looppanel is an AI UX research tool that automatically transcribes video interviews with over 90% accuracy, identifies key themes, and categorizes insights across various data formats, significantly reducing the time and effort researchers traditionally spend manually coding and analyzing qualitative data.
The platform also quickly extracts meaningful patterns, tags important segments, and generates comprehensive reports, allowing researchers to focus on deeper analysis and strategic insights rather than getting bogged down in time-consuming data processing.
This AI-powered platform transforms thematic analysis from a labor-intensive task into an efficient, precise, and accessible research method.
Thematic analysis template
When conducting your research, having a structured thematic analysis template can make the process more organized and efficient. A basic template should include:
- Research question/objective
- Data collection method
- Initial codes list
- Theme development worksheet
- Final theme definitions
You can customize this template based on your specific research needs and data types.
Conclusion
Thematic analysis is a powerful tool for understanding data by unmasking themes that come from customer feedback or other qualitative data. By coding the data systematically and marking categories of responses. In the case of thematic content analysis example, customer feedback on an app, like user experience, performance issues, and requests for features, can guide app developers to improve its functionality and user satisfaction. This analysis is based on real-world data, which provides insights that require action that can improve and enhance overall user experiences, making thematic analysis a vital tool for practical, data-driven research.
Make your thematic analysis journey more manageable by using AI tools such as Looppanel to help create transcripts for you and mark themes in the transcript generated. It can also help you to find answers to any question that you might come across in the transcripts with an advanced feature to share your findings easily with your other researchers. Book a demo with Looppanel now!
Frequently asked questions (FAQs)
1. How do you structure a thematic analysis?
Thematic analysis is structured in several stages:
- Data familiarization: Read and understand data.
- Coding: Identify and label key parts of data.
- Theme development: Group related codes into one theme.
- Theme review: Recheck and make sure themes represent the data correctly.
- Result: Describe the themes that are offering interpretations and conclusions.
2. Can Excel do thematic analysis?
Excel helps organize your data with thematic analysis. You can put down feedback or comments, then highlight important parts and give them codes. Next, you can group similar labels into one big theme. Excel has features like sorting and filtering, which make it easier to find patterns and organize your findings. However, this process is manual, and it might not be as advanced as modern solutions like Looppanel.
3. What is an example of a thematic analysis?
Let’s consider you collected feedback from a group of people about a new app. When you read their comments, you might notice common themes like "easy to use," "too many ads," and "needs more features." You can group these into themes- "User Experience" and "Suggestions." This will help you understand what people like and what can be improved. This is an example of thematic analysis.
4. How do you write a thematic analysis?
While writing a thematic analysis, you should start by reading through your data, such as feedback or interviews. Find repetitive ideas or patterns and tag them with codes. Group these similar codes into themes. Then, you can explain each theme in detail, with examples from the data. Finally, conclude your findings and how they can help answer your research question.
5. What is an example of thematic content?
A group of comments about a new video game can be a thematic content analysis example. Some players might say how fun the game is, others might talk about its difficulty levels, and some can also suggest improvements. You can group these comments into individual themes like "Gameplay," "Difficulty," and "Suggestions," displaying the main topic that players are discussing.
6. What is an example of codes in thematic analysis?
Thematic analysis coding example can be if you analyze customer feedback for a website, your codes might say "easy navigation," "slow loading," and "lack of features." These codes help understand the feedback in smaller parts. Moving forward these codes can be changed into broad themes like "user experience" or "performance issues.
7. What is an example of qualitative analysis?
An example of qualitative analysis at a corporate level can be studying employee feedback from their surveys or interviews. For example, employees may have shared their thoughts on company culture, leadership, or work-life balance. By coding and placing responses into categories, you can create themes like "employee satisfaction," or "work environment," helping management make better decisions that can improve performance and employee satisfaction.
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