Thematic Analysis 101: Step by Step Guide to Analyse Qualitative Data and Discover User Needs

Understanding user needs and their pain points is essential for effective product development, marketing, and service design. Most Product people are aware they need to “talk to their users” and seek feedback – but few know how to analyse the output of those conversations. Thematic analysis, a qualitative research method, offers a structured approach to decipher these needs. This guide provides practical insights into leveraging thematic analysis to uncover user needs, ensuring your strategies are user-centric and effective.

What is Thematic Analysis

Thematic analysis helps you identify patterns or themes within qualitative data. This can be anything from interview transcripts to app reviews. It helps in understanding the deeper meanings and insights that quantitative data can’t capture.

Thematic analysis can be a labour intensive process requiring several iterations.

Step 1: Collect Your Data

The first step is data collection. It’s important to gather rich, detailed qualitative data from a diverse range of users. Methods include:

• Interviews and Focus Groups: Direct interaction with users helps you gather rich quotes and stories.
• Surveys with Open-Ended Questions: Provides more structured data while still allowing for qualitative responses.
• App Reviews and Support Tickets: Offers unsolicited, organic user opinions and experiences.

Step 2: Familiarise Yourself with the Data

Once collected, transcribe your data if necessary. Read through the data multiple times to become familiar with the content. This helps in identifying potential patterns and themes early on.

Step 3: Generate Initial Codes

Coding involves tagging data segments with labels that summarize their core content. At this stage, codes should be as descriptive as possible.

Step 4: Searching for Themes

After coding, group codes into potential themes. A theme should represent a central idea that emerges from multiple codes. This process is iterative and may require you to go back and refine your codes.

Step 5: Reviewing Themes

Evaluate if your themes accurately reflect the dataset. Themes should be distinct, but also form a coherent pattern when viewed together. This step might involve splitting, combining, or discarding initial themes.

Step 6: Defining and Naming Themes

Once you’re satisfied with the thematic map, define and name each theme. This requires a detailed analysis of each theme and its relation to the data set. The names should be concise yet descriptive.

Step 7: Identify opportunities

In your analysis, weave the themes into a narrative. Explain how these themes address the user needs, supported by direct quotes from your data. This narrative should provide actionable insights for your team.

Step 4 to 7 can be done as a group in an workshop setting – enabling multiple stakeholders and team members to contribute to a shared view of what the users are saying.

Leveraging the Insights Throughout The Business

Thematic analysis is a powerful tool for understanding user needs. While it requires a meticulous approach, the insights gained are invaluable for creating user-centered products and services.

The findings have applications throughout your business:

• Product Development: with a better understanding of needs and outcomes that customers are seeking you can confidently build new features or improvements that target those.
• Marketing Strategies: armed with themes and exact quotes from users your marketing team can develop campaigns that use language that will resonate with users
• Service Design: identify where new service offerings can be developed to better support the needs of your customers.

Ferilla Discovery automates and speeds up all steps of thematic analysis, automating the generation of codes by automatically tagging your data, automatically grouping similar quotes and generating themes, whilst keeping you in control of the opportunities that can be uncovered.