Role Of Thematic Analysis In Qualitative Research


Thematic Analysis: Definition, Methods & Examples survey
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Whether you are a market researcher gathering customer insights or a social scientist exploring human behavior, listening to respondents’ unfiltered and unrestricted voices can provide more valuable insights. And, so thematic research stands as a powerful data analysis method that empowers researchers to gather textual feedback and harness the potential of data. 

In this blog, we’ll dive into thematic analysis and how it aids the world of research. 

What is thematic analysis?

As the name suggests, Thematic Analysis means analyzing the patterns of themes in data. It is a method of qualitative data analysis. It means this method can be used to analyze non-numerical data such as textual feedback you gather using surveys. 

The process involves systematically organizing and interpreting open-ended feedback to uncover meaningful insights and identify underlying patterns within the data. Tools such as text analysis software help you automatically perform analysis and identify themes and patterns. 

The analysis approach enables you to contextualize experiences, understand participants’ perspectives, and explore the hidden meaning behind their behavior. 

Example of a real-world application of thematic analysis.  

Say a tech company conducts market research to understand customer satisfaction. The company collects textual feedback from all its active customers. 

The company uses text analysis tools to perform thematic analysis to make sense of the data. After careful analysis, they identify several recurring themes such as “customer support,” “billing,” “ease of use,” and “product performance.” 

Through this analysis method, the tech company can now quantify the recurrence of each key theme and draw insights into areas that need improvement and where they excelled. 

Read how Voxco helped HRI to conduct complex research studies & speed up insight generation.

How does thematic analysis help in research questions?

Thematic Analysis: Definition, Methods & Examples survey

The patterns can be analyzed by repetitive data reading, data coding, and theme creation. The importance of thematic analysis is in exploring human experiences, attitudes, and behavior. 

  • It allows you to discover patterns and trends, thus revealing recurring themes that may otherwise go unnoticed. 
  • You can generate a rich and nuanced understanding of respondents’ perspectives. 
  • It helps you contextualize data by offering a comprehensive interpretation. 

Let’s take an example to understand how thematic analysis helps in research questions

How has social media changed over the years?

The above research will need you to gather data from sources, blogs, news, interviews posted online. Interview a few new generation users of the platforms and the old users to gather intel about how they use the social platforms and what their experience is. 

Also read: Quantitative Research Question

Who does thematic analysis?

Some of the established players have started implementing Thematic Analysis to improve their Manual Rules processes but tend to produce a list of terms that are difficult to review. This approach works well for text analytics platforms that are focused on improving the customer experience. However, it avoids generating generic solutions that are usually not designed to solve the problem. 

Only a small portion of feedback is linked to the top 10 themes. Uncategorized feedback means that you can’t slice the data to get deeper insights. Thematic research is a method that can easily analyze text-based feedback from multiple sources, such as email, social media, and real estate brokers.

Empowering decision-makers with text analysis.

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What are some best practices for survey data visualization?

As we are towards the end of the article, let’s look at some of the best practices to ensure consistent, efficient, and comprehensive data visualization. 

1. Ensuring interpretability and clarity: 

Use visualization elements that are clear, concise, and easy to interpret. Use appropriate labels, titles, and context to communicate complex information with completeness clearly. 

2. Consider accessibility of the report: 

Make survey the survey data visualization tools accessible to all responsible users. The platform must adhere to data security standards and guidelines to ensure any authorized user is unable to access it. 

3. Ethical data handling: 

Leverage a survey analytics software that adheres to data privacy regulations and ethical standards when handling survey data. Obtain informed consent from respondents and implement robust data security to protect data integrity and uphold ethical principles. 

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→ Learn how your customers feel & why

→ Identify recurring trends & patterns

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What are the advantages of using thematic analysis?

Thematic analysis in qualitative research is an unsupervised approach that enables you to create categories and perform statistical tests without having to set up any rules or procedures in advance.

  1. In-depth insights: 

The method allows you to gain deeper insights into participants’ motivations, emotions, and perspectives. 

  1. User-friendly: 

The analysis is highly accessible as most modern survey software provides you with the capability of text analysis. 

  1. Holistic understanding: 

Exploring multiple recurring themes in context with the research objective creates a comprehensive understanding of the topic. 

  1. Applicability: 

The data analysis method is useful for various fields like market research, customer experience research, social research, healthcare research, etc. 

What are the disadvantages of using thematic analysis?

Thematic analysis is an unsupervised approach that enables you to create categories and perform statistical tests without having to set up any rules or procedures in advance.

  1. Overlooks minor themes: 

Often times, you may overlook minor themes or less recurring patterns, leading to oversight of crucial insights. 

  1. Limited context: 

Thematic analysis is typically phrase-based. Sometimes, it can’t capture the meaning of a phrase correctly. For instance, in a complex narrative it can’t capture the customer’s intent to stop using the service.

What are the different types of thematic analysis?

With an adequate understanding of the method, let us dive into the various types of thematic analysis in qualitative research. 

1. Inductive:

Focuses on developing a theory. This approach is used when there is not much information available on a topic and you have to build a theory straight from scratch. You can always validate this approach but it is hard to prove that observation made from this approach is correct. The inductive approach consists of three stages:

  • Observation- a road has a busy traffic
  • Look for a pattern- the road has busy traffic from 9 am to 6 pm.
  • Develop a theory- a road has busy traffic during working hours.

2. Deductive:

Focuses on testing an existing theory. It totally depends on the Inductive approach as you start from working on an already existing theory. You go on formulating the theory and derive a conclusion out of it. The genuineness of deductive theory depends on how much true inductive theory is. The deductive theory has four stages:

  • Starting with a theory- the road has busy traffic during working hours. 
  • Formulate a hypothesis- generally, all roads are busy during working hours.
  • Collecting data to study hypothesis- observing all the roads during the working hours every day. 
  • Analyze the result (does the collected data reject or validate the hypothesis)- since all the roads are busy during working hours -> support a hypothesis. 

3. Semantic:

Focuses on the details of the data. We research the data on the grounds that it has some secondary meaning and purpose to it. This will help to construct insights and information regarding how the data was being used. 

4. Latent:

Focuses beyond the semantics of the data and works more on the underlying meanings, concepts, and assumptions that we made earlier with the semantic approach.

In order to choose the best-fit approach for your study, go through its requirements and which approach or combination of approaches will best align with your data. 

Also read: How to make the most of your data analysis in research?

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How to conduct thematic analysis?

There are six steps involved in conducting thematic analysis:

1: Familiarization

2: Coding

3: Generating themes

4: Reviewing themes

5: Defining themes

6: Writing

Once you have gathered adequate data and chosen your suitable approach, it is time to follow the following steps to build your thematic analysis for your problem statement. 

Step 1: Familiarization 

It is important to be familiar with the data before we begin to dig deep into the individual topics. This can include re-reading the whole data, having an overview of its context, and taking out personal notes if necessary. This is will help you to know your data. 

Step 2: Coding 

This includes highlighting or labelling certain words or group of words or even phrases in the data that all together indicates something. This something will come in handy when you are trying to grab the essence of the data. Let’s take an example to understand this:

Example: How has social media changed over the years?

Let’s say we are interviewing an old social media user here and her opinion on the problem statement. She says, 

I think the social media platforms are not for us oldies anymore. The trends are rapidly changing and there is always something new on the wall every day. It becomes difficult for people like me to keep up with those. Hence we often feel disconnected.” 

Now we can derive codes for the highlighted phrases like; Fast change | Uninterested | Discomfort

Step 3: Generating Themes

Now that we have our codes, we can derive themes from them. Themes can have several codes indicating the same expressions. As for our above example, we can have a theme called “not satisfied” for all the codes we derived from the interview. This will give an idea about how many codes are being used again and again and which ones of them serve no purpose so we can just discard them. 

Step 4: Reviewing themes

Here we compare the themes with our original data and look for any missing points or irrelevant results. We can modify our themes depending on how they satisfy and justify the data after tracing them back to it. 

Step 5: Defining themes

Further ahead, we can name the themes depending on what they indicate and what we get to understand from it about the data. 

Step 6: Writing

For the last step, we will the results that we have come to and the conclusion that our thematic analysis has helped us to understand. As per our example, we can conclude that social media has changed so much that the older generations find it hard to interact with and result in their dissatisfaction on the matter. 

So that is how to regulate your perfect Thematic Analysis for the next time you decide to research a problem statement. 

Voxco helps the top 50 MR firms & 500+ global brands gather omnichannel feedback, measure sentiment, uncover insights, and act on them.

See how Voxco can enhance your research efficiency.


In qualitative research, thematic analysis is a powerful and flexible data analysis tool with an ability to produce comprehensive findings, reveal underlying meanings, and detect patterns that aid in drawing data-based conclusions as well as decisions by researchers. To leverage the full potential of this approach, integrate it with quantitative and other qualitative data analysis methods. Mixed-method blends the benefits of both analysis approach and empowers you to generate broader and rich insight. 


What is the thematic analysis method?

The thematic analysis refers to the process of identifying, interpreting, and reporting these themes in textual data. It is a method for identifying, analyzing and reporting patterns within data.

What are the 5 steps of thematic analysis?

The common approach to thematic analysis involves five steps: 

  1. Familiarization
  2. Coding
  3. Generating themes
  4. Reviewing themes
  5. Defining and naming themes

What is the meaning of making thematic analysis?

Meaning-making thematic analysis involves interpreting the data to derive deeper insights and understand underlying meanings.

What is an example of doing thematic analysis?

A thematic analysis example could involve studying participants’ experiences on dating sites. Researchers used a thematic analysis to study participants’ experiences on dating sites, analyzing qualitative data to identify trending issues and recurrent patterns, providing insights into young females’ mindsets and social interactions.


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