As an essential tool in qualitative inquiry, thematic analysis transforms thoughts, feelings, and opinions into powerful, actionable insights. By identifying and analyzing underlying themes in text, video, and audio data, thematic analysis offers business owners, managers, and professionals a systematic approach to optimizing strategies and guiding more informed decision-making.

To help you unleash the power of thematic analysis in your own strategic efforts, we’ll be using our expertise at Business2Community to walk you through everything you need to know about thematic analysis including how to do one, real-life examples, and more.

Thematic Analysis – Key Takeaways

  • Thematic analysis is a qualitative analysis method for discovering themes in subjective data such as survey opinions, interview transcripts, and feedback forums.
  • It allow professionals in business contexts to gain key insights into qualitative data, driving strategic planning, efficient resource allocation, and more informed decision-making.
  • To address key limitations such as subjectivity and a lack of replicability, consider combining thematic analysis with quantitative analysis methods like descriptive analysis, cluster analysis, or factor analysis.

What is a Thematic Analysis?

Thematic analysis is a qualitative data analysis method that offers a systematic and rigorous approach to identifying, organizing, and revealing underlying themes in a data set. It involves understanding thoughts, feelings, and ideas as well as other descriptive information and categorizing them into themes.

thematic analysis

Thematic Analysis vs. Discourse Analysis

Unlike discourse analysis, which is a type of qualitative research that focuses on the nuances of spoken or written texts, thematic analysis is broader in scope, aiming to identify themes across many kinds of qualitative data.

Thematic Analysis vs. Narrative Analysis

Narrative analysis focuses on personal stories to understand how individuals interpret experiences. On the other hand, thematic analysis focuses on uncovering common themes and exploring shared meaning across different types of qualitative data.

Who Needs to Do a Thematic Analysis?

Anyone wanting to understand broad themes in subjective information and leverage insights from large qualitative data sets needs to do a thematic analysis.

In business contexts, business owners as well as research teams in functional areas like marketing, customer service, and human resources can benefit from using thematic analysis to unlock insights that quantitative data alone doesn’t provide.

By revealing underlying themes in customer and employee sentiments, businesses can tailor and optimize resource allocation, strategic planning, and general decision-making for a greater competitive edge.

How to Perform a Thematic Analysis

Before we go into a simple step-by-step process for performing a thematic analysis, let’s look at the main approaches to thematic analysis as well as the types of thematic analysis.

Approaches to Thematic Analysis

The main approaches to thematic analysis include:

  • The inductive thematic analysis approach focuses on analyzing qualitative data and identifying themes with no expected outcomes.
  • The deductive thematic analysis approach focuses on analyzing data and identifying themes through expected outcomes based on prior knowledge, previous research, or existing theories.
  • The latent thematic analysis approach focuses on the underlying meaning of data to uncover hidden insights.
  • The semantic thematic analysis approach ignores the underlying meaning of data and focuses on identifying themes based on what is written or explicitly stated.

Thematic Approaches


Types of Thematic Analysis

Now that we’ve looked at the approaches to thematic analysis, let’s dive into the main types of thematic analysis:

  • Coding Reliability Thematic Analysis adopts a technical or pragmatic view, and focuses on using a codebook and codes being replicable between different researchers during the coding process.
  • Codebook Thematic Analysis follows a deductive approach and focuses on predetermined codes and structured codebooks to identify themes. Key examples include framework analysis, template analysis, and matrix analysis.
  • Reflexive Thematic Analysis involves a flexible approach where codebooks aren’t used. Instead, it embraces the value of a researcher’s interpretation and how it impacts the coding process.

Now, it’s time to dive into how to conduct thematic analysis in just 9 simple steps.

Step 1: Determine Your Research Questions

In this first step, determining your research questions is crucial as it will help focus and guide your analysis process. Consider what information you need for your business and what has led you to want to complete an analysis. Understanding what you want to know (or at least what kinds of things you want to know) will help bring clarity to your next steps.

Step 2: Select a Research Design and Approach

Select a research design and approach that’s suitable for your research question. Ultimately, what’s right for your research project will depend on your priorities and preferences.

For example, if you want a structured approach, that draws on prior knowledge, opt for a deductive approach. If you’d rather let codes and themes emerge from your data, go with an inductive approach like reflexive thematic analysis.

Research Design

Step 3: Initial Analysis

In this stage, familiarizing yourself with the entire data set is imperative. This typically involves reading, re-reading, and even transcribing your data so you can formulate initial ideas on patterns or themes.

Step 4: Generate Initial Codes

Next, you’ll need to identify intriguing excerpts in your data that are relevant for your goal and type of analysis and assign them appropriate codes that describe what they are about. This sets the stage for more detailed analysis later. For example, this could be sorting your data for customer service, shipping, and product availability and highlighting text with different colors or assigning numbers, or coding the content as generally positive or negative comments on social media.

Step 5: Search for Themes

Once you have a set of initial codes, sort them based on similarity. Consider how various codes can be combined, and see if any potential themes start to emerge. This could be the same type of comments about specific products, bugs, or processes or if your user-generated content all highlights the same feature whereas email feedback tends to cover a different feature.

Step 6: Review Your Themes

Revise and refine your initial themes, checking to see how well the themes support the coded data extracts. At this stage, you may also consider starting to organize the themes into a thematic map, or early theoretical framework.

Step 7: Define and Name Your Themes

As you spend more time reviewing the themes, define each one more precisely, assigning names that capture the true essence of what each theme is about. This could be names for points in your customer journey or the level of experience for your employee data.

Step 8: Report Your Findings

The next step involves reporting on your findings. A typical thematic analysis report has an introduction, a methodology section, your results and findings, and a conclusion. It should also include an interpretive analysis and arguments for your claims.

To highlight the credibility of your findings, ensure that your final report details your research process and any other data relevant to the analysis. Consult your reflexivity journal to answer questions such as:

  • What was the basis of your investigation?
  • How did you conduct your investigation?
  • Why did you select a particular method or approach?
  • Who were your research participants?
  • When and where did data collection occur?

Step 9: Interpret and Apply your Findings

Finally, interpret what these themes mean in the context of your research questions. How can you use them to address the aims of your research study? Ultimately, this final step bridges the gap between analysis and meaningful application. This may mean you need to update HR processes, improve your product offering, or keep going with your highly engaging influencer campaign.

Example of Thematic Analysis

An online store’s marketing team would like to understand customer sentiments about its offerings and service delivery.

Research question: What do our customers value most?

Data collection: 200 customer reviews are collected through the company’s verified Trustpilot page.

Initial analysis: The team reads through the reviews to get a general sense of customer opinions and potential themes.

Some review snippets are shown below:




Customer reviews

Customer reviews

Customer reviews

Initial coding:

By highlighting specific phrases, sentences, and keywords the following initial codes are identified:

  • Fast shipping
  • Helpful customer service
  • Product durability
  • Product is not as described
  • Easy returns

Grouping themes:

Further analysis leads to grouping codes into the potential themes. For example, codes related to “fast shipping”, “helpful customer service”, and “easy returns” are grouped under the broad theme of Customer Service Quality. At the same time, those related to product characteristics are grouped under the theme of Product Satisfaction.

Reviewing themes: The identified themes are reviewed to ensure they accurately represent the review data and don’t miss important feedback.

Defining and naming themes:

Once the themes are finalized, the team defines and names them clearly, providing a detailed analysis of each theme, supported by direct quotes from the reviews.

Reporting findings:

In their final report to executives, the team provides an overview of the thematic analysis process, the themes identified such as the need for product quality improvements, and how these themes help pinpoint what their customers value most such as good shipping and helpful customer service.

Actionable insights:

The customer service quality theme highlights areas where the online store excels, such as fast shipping and helpful customer service, as well as areas for improvement such as streamlining returns to make them even easier.

The product satisfaction theme reveals that while customers are pleased with the durability and quality of the products, many are unhappy about products not matching their descriptions. This indicates a need for better product descriptions and more detail on the website.

When to Use Thematic Analysis

Thematic analysis can be put to great use in any number of different scenarios. It is used when you want to explore people’s views, opinions, knowledge, experiences, and values from qualitative data such as interview transcripts, social media profiles, or survey responses.

Here are a few of the best uses of this analytical technique in the business world.

Optimizing Marketing Strategies

Thematic analysis is a valuable tool for optimizing marketing strategies to better appeal to customer preferences.

For example, a marketing team can use thematic analysis to explore customer preferences, expectations, and pain points based on feedback, social media conversations, and product reviews. Armed with common themes in customer sentiments, the team can then tailor its efforts accordingly.

Informing Product Development

Thematic analysis can be used to inform product development, ensuring a business can meet customer expectations and stay ahead of competitors in the market.

For example, a product team could use thematic analysis to analyze customer sentiments or market research data to spot trends, identify gaps, and drive innovation.

product development

Enhancing Human Resource Management

Thematic analysis can play a crucial role in informing strategies to improve employee engagement, retention, and workplace conditions as a whole.

For example, an HR team can use thematic analysis to examine employee feedback and survey results, to identify common themes and adjust HR policies accordingly.

Improving Customer Service

Thematic analysis offers deep insights into customer preferences, expectations, and pain points, enabling businesses to improve their service delivery.

For example, by analyzing customer inquiries, complaints, and feedback through thematic analysis, customer service teams can understand common issues, concerns, or trends affecting customer satisfaction and address them.

Strategy Development

Thematic analysis helps in identifying emerging trends, opportunities, and threats in the market, giving a business a competitive edge.

For example by analyzing industry reports, competitor analyses, and market research, company directors and other executive managers can enhance strategic planning and long-term business development.

How to Adjust a Thematic Analysis

To adjust your thematic analysis for better outcomes, do the following:

  • Ensure you have well-defined research questions as this will make it easier to identify patterns and relevant themes.
  • Use relevant, high-quality data to ensure that your qualitative analysis findings are valid and insightful.
  • Combine inductive and deductive approaches for a more thorough yet flexible method of identifying expected and unexpected themes.
  • Document your research process through a reflexive journal. This allows you to continuously reflect on the developing analysis. It also increases the transparency and trustworthiness of your analysis.
  • Use thematic analysis software to streamline the taxing aspects of conducting a thematic analysis manually such as coding, categorization, and theme identification.
  • Embrace the power of machine learning for more efficient analysis and even more powerful insights from your thematic analysis.

If you’re not happy with the outcome of the analysis, you can make the improvements indicated and run the analysis again within a defined timeframe. What elements need changing will depend on the question you have asked and what may or may not be in your control.

If you get feedback from your employees that they are feeling burned out, consider introducing a wellness program or if your social media adverts attract comments about delayed service responses, you may want to increase your customer service headcount, for example.

Limitations of Thematic Analysis

Thematic analysis affords qualitative researchers flexibility throughout the process, especially if you opt for reflexive thematic analysis. However, a key limitation is that it isn’t based on any existing theoretical frameworks, and this could limit its interpretive power.

Thematic analysis is also subjective and relies on your judgment and expertise. This can lead to vast differences in interpretation between you or another researcher, which in turn, can affect the consistency and reliability of findings. Where possible, integrate quantitative research methods like descriptive statistics, cluster analysis, or factor analysis to help validate and quantify your findings.

Quantitative analysis

Lastly, thematic analysis can be time-consuming, especially for massive data sets. As mentioned earlier, consider making use of thematic analysis software or machine learning tools. Machine learning tools are efficient at text, video, and audio file analysis, matching qualitative coding, and creating thematic maps, all while respecting your theoretical commitments and research design.

The Value of Thematic Analysis

The value of thematic analysis lies in its flexibility and applicability. This makes it ideal for exploring complex and nuanced themes within qualitative data and providing meaningful insights across various disciplines.

In business, thematic analysis is particularly useful for exploring complex phenomena, especially when quantitative measures are insufficient or inapplicable. It enhances customer understanding, informs strategy, helps improve products and services, and guides more informed decision-making.

There’s little reason not to leverage thematic analysis to analyze your qualitative data, gain insight into key business areas, and drive function-wide success. To address key limitations such as subjectivity and a lack of replicability, consider combining thematic analysis with quantitative analysis methods like descriptive analysis, cluster analysis, or factor analysis.


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