Qualitative 101: The High-Level Process

The big-picture process you need to understand before you start.

By: Derek Jansen (MBA) | Expert Reviewer: Dr. Eunice Rautenbach | January 2025

Navigating the qualitative research process can feel daunting if you’re not sure where to start. In this post, we’ll provide a big-picture view so that you understand the overall process, before getting into the details.  Specifically, we’ll break the qualitative research process down into four key phases:

1. Collecting the data
2. Reviewing and coding
3. Analysing the data
4. Writing up

Let’s jump into it…

Stage #1: Collecting the data

The qualitative research journey always begins with data collection. This phase is all about gathering rich, detailed information that will serve as the foundation for your study. As with all methodological choices, the specific methods you use will depend on your research design and research questions.

Common data collection methods include:

• Interviews: Ideal for exploring participants’ thoughts, experiences, and perspectives in depth.
• Observations: Useful for understanding behaviours in natural settings.
• Documents: Includes letters, reports, diaries, or any written content relevant to your research.
• Fieldwork: Involves immersing yourself in the research environment to gather first-hand insights.

When choosing your data collection method (or methods), it’s important to keep a few points in mind:

• Be intentional: It’s essential that you align your data collection methods with your research design and research questions. In other words, make sure you’re collecting data that will be relevant and useful.
• Prioritise quality: Focus on gathering detailed, relevant data rather than simply amassing large quantities. Quality of data is key.
• Build trust: It’s critically important that you establish rapport with your participants to encourage openness and honesty. Developing interviewing skills is key.

As you can probably imagine, this phase is crucial because the quality of your data will directly impact the quality of your findings. So, be sure to think carefully and act very intentionally when collecting qualitative data.

Stage 2: Reviewing and coding

Once you’ve collected your data, it’s time to review and code. This is where you start sifting through your dataset, identifying patterns, and organising the information into manageable pieces.

But what exactly is qualitative coding?

Simply put, coding means tagging pieces of data with labels to represent different ideas or concepts. Think of it like sorting puzzle pieces into groups based on colour, size, or some other dimension – you’re breaking the dataset into meaningful chunks to prepare for analysis.

The exact process and approach you’ll take when coding will depend on your research aims and questions. Broadly speaking though, the process will look something like this:

1. Develop a coding structure: Decide whether you’ll take an inductive or deductive approach, based on your broader research design.
2. Familiarise yourself with the data: Read through transcripts, field notes, or documents to get a sense of the content.
3. Identify patterns and groups: Look for recurring words, phrases, or ideas.
4. Apply codes: Assign labels to these patterns, grouping similar pieces of data together.

Practical Example: Imagine you’ve conducted interviews on work-life balance. During the review, you notice recurring mentions of “flexibility,” “stress,” and “time management.” You’d create codes that relate to these themes and tag relevant sections of your dataset.

Importantly, this phase (review and coding) sets the stage for deeper analysis by helping you organise your data in a way that reveals patterns and relationships. While it can be tempting to speed through this stage, it’s important to take the time to set a solid foundation for your analysis.

Stage #3: Analysing the data

With your data prepped and coded, it’s time to move on to the heart of the qualitative research process: analysis. This is where you uncover insights and make sense of the data through the lens of your research questions.

There are many different qualitative methods available, but the four most common ones are:

Thematic Analysis: Focuses on identifying, analysing, and interpreting recurring themes or patterns across the dataset. It’s particularly useful for exploring participants’ experiences, beliefs, and perceptions.

Discourse Analysis: Delves into how language is used in communication to construct meaning, influence social interactions, or reflect power dynamics. It examines the context of language, making it ideal for studying ideologies, social norms, or organisational practices.

Narrative Analysis: Focuses on personal stories and how individuals construct meaning through their narratives. It is ideal for in-depth studies of personal accounts, such as life histories, autobiographies, or interviews, where the “how” and “why” of storytelling are central.

Content Analysis: Provides a systematic method for quantifying and categorising the presence of specific concepts, themes, or words in the dataset. It bridges qualitative and quantitative approaches and is particularly useful for analysing media content, documents, or large-scale textual data.

Each of these methods serves a distinct purpose, so choosing the right one depends on your research questions, aims, and the type of data you’re working with.

Example: Using thematic analysis for work-life balance interviews, you might identify overarching themes like “challenges with time management” or “importance of employer support.” You’d then explore how these themes interconnect and what they reveal about the participant group.

As you can see, this phase is where the richness of qualitative research shines, as you delve into the deeper meanings and implications of your findings.

Stage 4: Writing up

The final phase is writing up your results. This is where you bring your research to life by telling the story of your findings, connecting your insights to the broader context, and showcasing their significance.

While the exact structure and content of the write up will vary across projects, you’ll typically need to at least touch on the following components:

• Presentation: Clearly explain what you discovered, supported by quotes or examples from your data.
• Connection: Show how your analysis answers the questions you set out to explore.
• Integration: Discuss how your findings align with or challenge existing research, drawing on your literature review.
• Implications: Highlight what your findings mean and how they can be applied in practice or further research.

Practical Example: In your study on work-life balance, you might write about how participants described flexibility as a double-edged sword – offering freedom, but also blurring boundaries between work and personal life. You’d provide quotes from your dataset to illustrate these points and tie them back to existing theories on workplace dynamics.

Importantly, the goal here isn’t just to report your findings but to craft a compelling narrative that situates your research within the broader academic conversation.

Iteration is key…

While we’ve presented these phases as sequential, it’s important to remember that qualitative research is often iterative. You might:

• Return to data collection after discovering gaps during the coding or analysis phase.
• Revise your codes as new themes emerge during analysis.
• Refine your write-up as your understanding of the data deepens.

This back-and-forth process isn’t a flaw – it’s a strength. It allows you to stay responsive to your data and ensures that your findings are as robust and comprehensive as possible.

Key Takeaways

We’ve covered a lot of ground here, so let’s do a quick recap.

The qualitative research process typically involves four key phases:

1. Collecting the data: Where you’ll gather rich, detailed information through interviews, observations, or documents.
2. Reviewing and coding the data: Where you’ll organise the data into meaningful chunks to reveal patterns and themes.
3. Analysing the data: Where you’ll use qualitative methods to interpret the data and uncover insights.
4. Writing up the results: Where you’ll present your findings in a clear, meaningful way that connects to existing research.

Remember, the qualitative research process is rarely perfectly linear. So, don’t freak out if you find yourself looping back and forth. Embrace the iterative nature of qualitative research and allow your findings to evolve as your understanding deepens.