15 May 2025
|17 min
Qualitative research: Types, methods & when to use each
Explore different qualitative research methods, including interviews, ethnography, and grounded theory. Learn when to use each to gain deep user insights.

Key takeaways
Qualitative research helps you uncover the why behind user behavior – motivations, emotions, and context that numbers alone can’t explain.
From ethnography to interviews, different qualitative methods offer flexible ways to explore user experiences in depth.
Mixed-methods research – blending qualitative and quantitative – gives you a fuller picture and more confident decision-making.
Lyssna supports both approaches, with tools for collecting rich user insights and validating ideas at scale.
Choosing the right method depends on your goals, timeline, and the kinds of questions you’re asking.
Qualitative and quantitative research may go together like peanut butter and jelly, but, as any sandwich fan knows, there are numerous nuances to consider. What kind of nut butter is being used – is it crunchy or smooth, peanuts or almonds, ready-to-use or in need of stirring?
The same is true with types of research.
Understanding the key differences in qualitative vs quantitative research, such as their respective focuses on subjective experiences versus numerical data – can help guide the selection process.
While it’s easy enough to determine that a question or problem should be explored further with qualitative research, determining the specific type of qualitative research you'll use is an important first step.
Qualitative research balances out quantitative research. If quantitative research answers questions like “what,” “how much,” and “how many,” qualitative research answers questions like “why” and “how.”
Not only are qualitative and quantitative research methods often used in combination with each other, multiple styles of qualitative methods may be combined – using interviews and deep historical research to build out a phenomenological study, for example.
The key to successful research is choosing the right frameworks and methodologies to complement each other.
Turn insights into action
Lyssna offers a range of tools to help power your qualitative research. Sign up today and gain a deeper understanding of user behavior.
What is qualitative research and why does it matter?
Qualitative research is a methodology that uses non-numerical data to better explore the motivations, responses, and experiences of people. This data can be obtained through techniques like interviews, observations, or open-ended surveys, and it produces insights that can, in turn, inform decisions in fields like UX research, marketing, product management, and UX design.

Qualitative research can help answer questions like:
What do target users need, specifically, when interacting with our website/product?
Why do users feel the way they do, and what do happy and unhappy users say about their experiences?
How do consumers feel about our brand, and what might strengthen our brand appeal?
What do heavy users of our application think about a dramatic visual overhaul proposed by marketing?
Characteristics of qualitative research
Before we dive into specific types of qualitative research, let’s run through some of its characteristics at a high level, to help differentiate its utility from more quantitative methods.

It’s exploratory
Qualitative research helps us better understand a phenomenon. It describes and interprets rather than quantifies. (Leave the quantifying to quantitative research.)
It’s non-numerical
Qualitative research deals with data types such as text, audio, images, and video, focusing on the variety of human experiences. While this data can be tagged and eventually quantified, that’s not its primary utility. If you want numbers, go for quantitative research.
It uses smaller sample sizes
Qualitative research uses smaller samples chosen for their relevance to the research question. The answers aren't intended to be extrapolated to the broader population, but rather used to better understand more quantitative trends in the broader population.
It’s highly contextual
Qualitative research emphasizes the importance of understanding the context in which behaviors or experiences occur. The background and context of a person’s experience matters.
It’s highly subjective
Not only are participants’ subjective experiences being collected, but researchers' own perspectives and biases must be acknowledged. The way in which you interpret nonverbal cues and ethnographic details are undeniably influenced by your own lived experiences.
It can be time-intensive
Qualitative research often takes longer because data collection and analysis are hands-on. Yes, it can feel slow, but shipping a redesign that misses the emotional mark is slower. You end up paying the delay in churn and rework instead of researcher hours.
Pro tip: Before choosing a research method, map out your timeline, budget, and team capacity. Some qualitative approaches (like ethnographic or grounded studies) require more time and resources, while others (like interviews or focus groups) can yield faster insights with less overhead. Picking the right fit upfront can save you from costly course corrections later.

Types of qualitative research design
These foundational approaches guide how you structure qualitative studies. Each one offers a different lens for exploring user behavior, context, and lived experience – from in-depth cultural immersion to focused case studies. The right approach depends on what you’re trying to learn and how deep you need to go.
Ethnographic research
Ethnographic research involves being immersed in a participants’ natural environment over a period of time, aiming to gain a more in-depth understanding of their experiences. Taking into account cultural differences, it provides contextually rich data about behaviors and beliefs – often revealing unarticulated needs and pain points.
As Nate Bolt, former Design Research Manager at Facebook, put it: “Watching real people all over the world trying to use stuff, all in the spirit of improving design is extremely powerful.”
It’s this firsthand observation that makes ethnography so valuable – helping researchers see beyond what users say and into how they actually behave.
For example, a UX researcher redesigning an employee scheduling tool might spend time in restaurants or retail stores observing how shift managers and staff use existing tools in fast-paced environments. They might notice workarounds, sticky notes, or verbal cues that never come up in interviews – insights that can directly inform more intuitive scheduling features.

Historical research
Sometimes the solution to a question is already out there, waiting to be uncovered. Historical research, true to its name, involves examining historical records, documents, and artifacts to gain insights into past events, contexts, and social phenomena, providing a more longitudinal perspective.
In a UX context, historical studies can help uncover user preferences or market dynamics that have evolved over time, informing branding strategies or product design decisions.
Let’s say a UX designer working on personal budgeting software wanted to figure out how user preferences have evolved in financial software over time. They could conduct a historical study by examining the user interfaces and features of banking apps from the past decade. By tracing the evolution of these design choices, they can identify trends in user preferences, navigation patterns, and security features.
Pro tip: Don’t just look at what’s changed – look at why it changed. When reviewing older user studies, product designs, or usage data, pair the findings with contextual research like market trends, tech shifts, or customer feedback from that period. This helps you understand the drivers behind evolving user needs – not just the outcomes – so you can anticipate future shifts rather than just reacting to them.

Phenomenology
Phenomenology focuses on understanding the lived experiences of individuals – how they perceive and make sense of specific events or interactions.
Rather than analyzing behaviors from the outside, this approach explores the meaning behind those experiences from the user’s point of view. It’s especially useful for building empathy and designing with a more human-centered lens.
As Matt Leppington, a UX research lead, puts it: “Empathy is crucial to qualitative research in UX. If you don’t connect with the user, you don’t build for the user.”
For example, a UX researcher trying to improve a project management app might explore how team members and managers experience collaboration features – not just whether they use them. They may uncover that while managers see these tools as helpful oversight mechanisms, team members view them as micro-management. These kinds of subjective insights can lead to more thoughtful, balanced design changes that improve buy-in across the board.

Grounded studies
Grounded studies seem like quantitative research, in that they involve the collection of raw data. However, where quantitative studies test predetermined hypotheses, grounded studies develop theories or models through the ongoing, systematic collection of data, generating new insights and theories based on observed patterns and themes. It allows for the development of new theories and models inspired by the participants’ ongoing usage, making it a flexible and iterative approach to qualitative research.
The findings of a grounded study can be doubly credible because they’re based on empirical data rather than just subjective user experiences.
Imagine a UX designer working on a social media platform who is interested in understanding how users develop online relationships. Through interviews and content analysis, the designer could identify patterns of interaction and communication that lead to the development of a grounded theory about the stages of online relationship formation. This theory could then inform the design of features that facilitate these stages for users.
Pro tip: When conducting grounded studies, resist the urge to start with a hypothesis. Instead, focus on collecting raw, open-ended data – then analyze it iteratively to let patterns emerge. Start with a few exploratory interviews or observations, code the results for themes, and refine your questions as you go. Tools like affinity mapping or thematic analysis can help you spot meaningful connections across different user narratives. This bottom-up approach may feel messy at first, but it often reveals insights you’d miss with a more structured method.

Narrative research
Narrative research focuses on how people tell stories about their experiences – not just what happened, but how they interpret and communicate it. These stories often reveal motivations, values, and emotional touchpoints that more structured methods might miss.
Unlike phenomenology, which aims to understand the experience itself, narrative research is about the meaning users assign to their experiences. This makes it especially useful when you're trying to uncover the deeper “why” behind user behavior.
To gather meaningful narratives, researchers need to listen more than they speak. As Erika Hall, co-founder of Mule Design, says: “Conducting a good interview is actually about shutting up.” Giving participants the space to talk freely often leads to the most revealing and unexpected insights.
For example, a marketing manager for a habit-tracking app might collect user stories about building healthier routines. Analyzing these narratives, they may notice recurring emotional themes – like the impact of community, the fear of failure, or the pride of consistency – that can inform more resonant messaging and features.

Case studies
Case studies take an acute approach to qualitative research, zeroing in on a specific instance to explore in greater depth. This could mean isolating an individual, a group, an organization, or an event, and exploring it intensively as a way to better understand the broader whole.
By comprehensively collecting data and insights on this narrow instance, it generates findings and illustrative examples that can be directly applied to other practical scenarios.
For example, a marketing manager at an enterprise resource planning solution may wish to use a case study framework to explore the impacts of their software on a manufacturing company’s operations.
By detailing the full narrative of the manufacturing company’s transition from a previous ERP platform to the new one, the marketing manager may uncover areas for improvement (like a rocky transition) as well as metrics the new platform improved (like new efficiencies in logistics).
Pro tip: Case studies work best when you want to showcase real-world impact – but they’re more than just storytelling. To make your case study genuinely useful, collect data from multiple sources (e.g. user interviews, support tickets, analytics, stakeholder feedback) and look for patterns that can be applied beyond the single case. Structure it like a narrative: start with the problem, walk through the solution, and highlight measurable outcomes. Well-crafted case studies can double as internal learning tools and compelling content for stakeholders or clients.
Qualitative research methods
While design research approaches help you frame your study, below are some hands-on methods that bring your research to life. From one-on-one interviews to group discussions, these techniques help you gather rich, first-person feedback straight from your users.
Interviews
Interviews are one of the most common methods of qualitative research, and can be used as part of almost any of the research approaches listed above. They’re just what they sound like: one-on-one conversations between a researcher and a participant.
Interviews can be conducted face-to-face or remote, and follow a structured interviews format (in which each interviewee is asked the same set of questions), unstructured interviews format (in which all interviewees are asked different questions), or a semi-structured interviews format (in which a loose structure is followed but deviations are encouraged).
Interviews provide in-depth insights and generate useful direct quotes from participants on their experiences. They’re also wildly scalable and flexible, generating insights about practically any aspect of the user experience.
For example, if a product manager for a shopping app wanted to uncover specific reasons for user churn, they could talk to users who have recently canceled their subscriptions to uncover added nuance beyond what raw data analysis might provide. They could then use these insights to address pain points and hopefully retain future users.
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Focus groups
Focus groups are similar to interviews, but they involve interviewing small groups of participants simultaneously. These structured discussions are typically led by a moderator and aim to take advantage of the group dynamic, gathering diverse perspectives, opinions, and insights on a particular topic.
Focus groups help gather diverse perspectives on a particular topic by encouraging group interactions and discussions. They can provide immediate feedback to concepts, ideas, and product prototypes, and are particularly useful in the exploratory phase of research, identifying issues and gut reactions before conducting more extensive prototyping and testing.
For example, if a clothing outlet wanted to field test some new branding, they could gather representative users from the target audiences and encourage them to discuss what they liked and didn’t like about the proposed direction of the brand. These conversations could generate lots of quick feedback about possible tones and themes for the re-brand, which could be fed into a broader test marketing effort by the marketing team for immediate iteration.

Observation
Observation is a foundational qualitative method that involves watching users interact with a product or service in real-world or controlled settings. It’s especially useful for identifying usability issues, workarounds, and behaviors that users might not articulate in interviews.
As Jakob Nielsen, co-founder of Nielsen Norman Group, puts it: “Pay attention to what users do, not what they say.” This is the core value of observation – it surfaces insights that traditional self-reported methods often miss.
Observation can be passive (the researcher doesn’t interfere) or participatory (the researcher engages with the environment), depending on the goals.
For example, a researcher might observe commuters using a transit app at a busy train station. They could notice that users struggle to find platform information due to glare on their phone screens or crowding around signage – revealing environmental factors that impact usability and that might not come up in a survey.
Pro tip: Use observation as a complement to interviews or surveys. Watching real-world behavior helps validate what users report – and often uncovers mismatches between intention and action.
Analysis
Analysis is where raw qualitative data transforms into meaningful insights. It involves reviewing transcripts, notes, recordings, or visuals and identifying recurring themes, behaviors, and pain points.
Common analysis techniques include thematic analysis (identifying patterns), affinity mapping (grouping related ideas), and coding (labeling key data points). This step is often iterative, requiring multiple passes through the data to surface what matters most.
As David Travis, UX researcher and author, explains: “Quantitative data tell us what people are doing. Qualitative data tell us why people are doing it. The best kind of research combines the two kinds of data.”
This is especially true during analysis – where pairing qualitative context with quantitative trends helps teams understand not just what’s happening, but why.
In UX research, analysis might involve coding interview transcripts to find common frustrations with a checkout process – then grouping those into themes like “lack of feedback,” “unexpected costs,” or “confusing flow.”
Pro tip: Tag insights by theme, persona, or stage of the user journey. This not only helps structure your findings, it also makes it easier to communicate them to stakeholders in a way that’s actionable.
Advantages of qualitative research
Quantitative data tells you what’s happening – but qualitative research tells you why. It gives you a way to explore user motivations, emotions, and context in a way numbers can’t. Whether you're refining a product or shaping an entire strategy, qualitative methods offer the depth and flexibility to uncover what truly matters to your users.

Here are the key advantages of qualitative research:
Adapt as you go:
Qualitative research is flexible by design. You can adjust your approach in real time based on what you're learning – refining questions, probing unexpected themes, or shifting focus as new insights emerge.
Go beneath the surface:
Move beyond surface-level observations to understand the emotions, experiences, and cultural context that shape user behavior. This depth is what drives more empathetic, user-centered design.
Tailored to your goals:
Every study can be customized – from the method you choose to the participants you engage – allowing you to align the research closely with your product, audience, or stage of development.
Beyond the numbers:
Quantitative data can show you what’s working or not – but qualitative insights help explain why users behave the way they do. That’s the kind of context that drives smarter decisions and stronger solutions.
Explore qualitative research for deeper insights
you need to understand the why behind user behavior. A mixed-methods approach – combining qualitative depth with quantitative scale – gives you the clearest picture of what your users need, expect, and value.
Lyssna supports both sides of the research equation, with tools for rich qualitative insights (like interviews and preference testing) and fast, scalable quantitative data (like surveys and usability tests). Whether you're exploring motivations or validating trends, you’ll have everything you need to turn insight into action.
Because the best products don’t just measure behavior – they understand it.
Get started with Lyssna today and start uncovering the insights that move your product forward.
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