How to analyze qualitative data from interview?

How to analyze interview data as in qualitative analysis? Discover the step-by-step process of analyzing interview data through automated analysis.

Chat icon

A Comprehensive Guide to Qualitative Analysis From Interview

Qualitative analysis is a vital part of research, often serving as the backbone of many academic, business, and social studies. Interviews, being a significant source of qualitative data, are rich with insights waiting to be uncovered. However, the process of analyzing interview data can be intricate and demands a meticulous approach.

Embarking on the journey of qualitative analysis begins with a deep understanding of its importance and the meticulous preparation required for an effective analysis. Through the lens of qualitative analysis, the nuanced human experiences captured in interview data can be translated into meaningful insights.

Importance of Qualitative Analysis

Qualitative analysis allows for a profound exploration of the underlying themes and patterns present in human experiences. It goes beyond mere numbers to offer a lens into the human psyche, behavior, and interactions.

Preparing for Analysis

The first step towards a rigorous analysis is to be well-prepared. This entails organizing your data meticulously and familiarizing yourself with the content.

Organizing Your Data

Before diving into the analysis, it's essential to have a well-organized dataset. This includes transcribing interviews, categorizing data, and ensuring that all the necessary information is accurately documented.

Familiarization with Data

  • Reading Transcripts: Engage with the text by reading through the transcripts multiple times. This immersion will help you get a sense of the overall narrative and the context in which statements were made.
  • Identifying Preliminary Themes: Even at this early stage, certain themes may start to emerge. Noting these down can be beneficial as you proceed with your analysis.

Coding Your Data

Coding is a pivotal step in qualitative analysis. It involves tagging or labeling sections of your data with codes that represent specific themes or ideas.

  • Creating a Codebook: A codebook serves as a reference guide for your coding process. It contains definitions and examples of each code, ensuring consistency throughout the coding process.
  • Initial Coding: Start by applying codes to your data based on your codebook. This phase is about getting familiar with your data and beginning to organize it in a meaningful way.
  • Axial Coding: This stage involves looking at the relationships between codes, identifying connections, and beginning to understand the broader themes at play.
Qualitative Data Analysis for Automated Insights

Identifying Themes

Uncovering the themes within your data is like piecing together a puzzle. It requires a meticulous and iterative process.

  • Recognizing Patterns: Look for recurring patterns or ideas within your coded data. These patterns will guide you toward the larger themes present in your data.
  • Refining Themes: As you delve deeper, you may need to refine or merge themes to better represent your data.


Visual representation of your findings can provide a clear and concise way to communicate your insights.

  • Utilizing Software Tools: Software tools like NVivo or Atlasti can be invaluable in visualizing your data.
  • Creating Visual Representations: Whether it's through charts, graphs, or thematic maps, visualizations can help in better understanding and communicating your findings.


The journey of analyzing interview data through qualitative analysis is a rigorous yet rewarding endeavor. By following a systematic approach, you can unveil the rich insights that lie within the narratives captured in your interviews.

Explore on Non-profit analytics

Info icon
POWERUP: Learn how to design effective impact learning and reporting. View tutorial
Search icon

Looking for something else?

Search our extensive library to find the answers or topics you're looking for.
Email icon

Still need help?

Can't find what you're looking for? Reach out for personalized assistance.
Contact support