What’s the ideal focus group sample size?
What is a good sample size for qualitative research, in general?
How can you tell you’ve reached qualitative research saturation?
While all these aren’t exactly dinner table conversations, they’re burning questions for researchers. And for good reasons.
Too few interviews leave you guessing. Too many, and you’re drowning in data. Are you unsure how many users to include in your qualitative research? This guide will give you expert-backed tips on how to:
- Find the sweet spot in product research
- Get insights you can trust
TL;DR – What Is a Good Sample Size for Qualitative Research?
Ideal sample sizes in qualitative research depend on your chosen method:
| Research method | Recommended sample size |
| Interviews | 12-15 participants |
| Focus groups | 4-6 groups with 5-10 users each |
| Usability tests | Multiple small rounds with 5 users per test round |
| Diary studies | 10-30 participants |
| Card sorting | 20-30 participants |
The type of saturation you’re aiming for can be another factor, which we’ll detail below. But selecting the right sample size isn’t the whole story. You’ll also need a smart way to manage and analyze qualitative data.
Marvin’s AI-powered workflows simplify this process. From capturing and tagging notes to identifying themes, our tool helps you find the point of saturation quickly.
Create a free Marvin account today and streamline your entire qualitative research.
Why Sample Size Matters in Qualitative Research?
When talking to one user, you get an opinion. But talk to ten, and patterns will start to emerge. Sample size matters in qualitative research because it:
- Shapes the insights you’re getting
- Boosts the confidence you have in them
For UX research to accurately reflect user needs, it has to balance depth and breadth. This balance depends on context, and sample size is one significant factor.
Here’s why it’s so important to get the right sample size for your specific qualitative research project:
- More voices, richer insights: A small sample might miss key perspectives. A balanced size captures diversity.
- Pattern detection: Too few participants? You might see randomness instead of real trends.
- Resource balance: More data is great, but analysis takes time. The right size avoids overload.
- Stakeholder trust: A well-chosen sample builds credibility. Too small? People might doubt the findings.
You stop learning new things when you reach saturation of data in qualitative research.
What Is Qualitative Research Saturation?
Saturation is the moment when new data stops adding new insights. You’ve captured the core insights and heard the same themes enough times. No fresh patterns emerge, just repetition.
Maria Rosala, Director of Research at Nielsen Norman Group, explains:
“Saturation in a qualitative study is a point where themes emerging from the research are fleshed out enough such that conducting more interviews won’t provide new insights that would alter those themes.”
In practice, saturation is a bit more nuanced and can have different meanings:
| Type of saturation | What it means |
| Theme saturation | Finding most of the main themes in your data |
| Meaning saturation | Capturing deeper details and variations within themes |
| Theoretical saturation | Understanding themes and their relationships fully |
| Metatheme saturation | Identifying themes across different groups or locations |
| Saturation in salience | Discovering themes that matter most to your participants |
But regardless of the type involved, data saturation in qualitative research is so important because it:
- Stops at meaningful insights: You don’t collect more data just for the sake of it.
- Prevents over-researching: More interviews past saturation add effort but not value.
- Keeps research efficient: You focus on depth, not just volume.
Differences Between Quantitative and Qualitative Sample Sizes
Sample size works differently in qualitative and quantitative research. In quantitative studies, bigger is usually better since large numbers increase reliability and statistical power. In qualitative research, the goal isn’t quantity but depth. That’s because a small, well-chosen sample can reveal rich insights.
Here’s how their sample sizes compare:
| Characteristics | Qualitative Research | Quantitative Research |
| Typical sample size | Small (often 5–30 participants) | Large (hundreds or thousands) |
| Why size matters | A few deep conversations uncover patterns | More data makes findings statistically valid |
| How do you know it’s enough | Reach saturation — no new themes emerge | Reach statistical significance — data is stable and results are reliable |
| Flexibility | Sample size can change as insights develop | Usually determined before research begins |
| Impact of a small sample | Can still provide strong insights | Can lead to weak, unreliable data |
Factors That Influence the Sample Size of Qualitative Research
There’s no magic number for sample size in qualitative research. Some studies need just a few participants, while others require more to capture diverse perspectives.
Here’s what influences the sample size:
- Research goal: Exploratory studies need fewer participants. Complex topics require a broader range of voices.
- Data saturation: When new data stops adding fresh insights, you’ve reached the right sample size.
- Participant diversity: If you need more varied perspectives, you would require a larger sample to capture key differences.
- Study method: In-depth interviews need fewer participants. Focus groups and ethnographic studies often require more.
- Available resources: More participants mean more time, effort, and cost. Smaller studies balance depth and feasibility.
For some companies, these factors mean choosing a small, focused sample. Others need a much broader approach. Microsoft, for example, decided to study responsible AI across industries. The research team had to capture diverse perspectives from AI practitioners, policymakers, and developers.
They conducted 47 interviews with 90 AI practitioners, generating 2,000+ notes from 80+ hours of discussions. This large sample captured key variations in AI maturity.
However, analyzing such a massive dataset manually would have been overwhelming. Using Marvin, they efficiently tagged interviews, synthesized insights, and built a clear framework from complex data.
Do you also need to analyze large amounts of qualitative data without losing key insights? Create a free Marvin account today. Our AI-powered research assistant can turn complex research into clear, actionable findings in hours.
How to Determine Sample Size for Qualitative Research
Choosing the right sample size isn’t guesswork. It follows a clear process that ensures meaningful research.
Take the steps below to get the right sample size for reliable, actionable insights:
1. Define Your Research Goal
Clear goals help you focus on depth or breadth.
Decide what you need to learn. Are you exploring a new problem or testing a known issue?
2. Identify Your Target Participants
The right mix ensures that you capture diverse experiences.
List who you need to talk to. Consider user roles, behaviors, and perspectives.
3. Choose Your Research Method
Different user research methods need different sample sizes.
Decide if you’ll use interviews, focus groups, diary studies, or observations.
4. Estimate an Initial Sample Size
A starting point helps you plan time and resources.
Start with a reasonable number based on past research or expert recommendations.
(Also, check our tips below on the recommended sample size for qualitative research in different methods.)
5. Conduct Research and Look for Patterns
As you start your research, see if you notice common themes emerging.
Spotting these patterns early shows if your interviews bring fresh insights or just repetition.
6. Check for Saturation
In qualitative research, saturation signals that you have enough data for strong conclusions.
Stop adding participants when no new themes emerge from the data.
7. Adjust If Needed
Adjustments will keep your research balanced and complete.
If gaps remain, add more participants from underrepresented groups.
Recommended Sample Size for Qualitative Research in Different Methods
The answer to “What is a good sample size for qualitative research?” depends on:
- What method you use
- What type of saturation you want to reach
A recent review in Sage Journals by researchers Amber Wutich, Melissa Beresford, and Russell Bernard explores saturation. Here are their suggested participant numbers for five key types of saturation:
- Theme saturation: 9-12 interviews or 4-6 groups
- Meaning saturation: 24 interviews or 8 groups
- Theoretical saturation: 20-30+ interviews
- Metatheme saturation: 20-40 interviews per site
- Saturation in salience: 10 detailed interviews
Let’s say you’ve chosen your sample size based on saturation. Next, you’ll want to consider the specific method you’ll use in your study.
Different qualitative methods have their own suggested participant numbers to get reliable results. Here’s a quick look at recommended sample sizes by research method:
In-depth Interviews
Interviews typically need 5–30 participants, although 12 is often enough. Aim for fewer participants if the topic is narrow, more for broader studies.
Focus Groups
A 2019 study published in the Sage Journal found that 4–6 groups in total are usually enough. Each group should have 5–10 participants.
Two groups per demographic category (men, women, younger, older) are ideal for deeper insights.
Usability Testing
Multiple small rounds provide stronger findings than one large round.
Jakob Nielsen’s famous research found that 5 participants uncover about 85% of usability issues. Therefore, using 5–8 users per usability testing round is enough to identify most problems.
Diary Studies
Diary studies aim to capture meaningful patterns across repeated behaviors or interactions. They typically involve 10–20 participants.
According to a guide in the NN Group, the approximate number of participants for saturation is:
- 5-12 in small discovery projects
- 12-30 in large discovery projects
- 30-50 in large research projects or academic research
Card Sorting
Tullis and Wood (2004), respected UX researchers, found that 20–30 participants are enough for card-sorting studies.
At the same time, Jakob Nielsen suggested testing just 15 users. He recommended allocating any extra resources to usability tests rather than seeking marginal gains from additional participants.
Tips to Justify Sample Size in Qualitative Studies
People might question your sample size. Justifying your choice makes your research stronger and more credible.
Use the tips below to build trust in your findings:
- Emphasize research depth, not quantity: Explain how your qualitative research valued rich, detailed insights over large numbers.
- “A diary study with 10 participants over two weeks provided deep, contextual insights into daily app usage.”
- Connect sample size to study complexity: Show that simpler topics require fewer participants, while complex issues need broader representation.
- “For our high-risk healthcare tool, we conducted 25 usability tests to ensure we captured nuanced concerns.”
- Demonstrate that you’ve reached saturation: Prove that new data stopped adding insights. Saturation matters more than hitting a fixed number.
- “After analyzing 40 open-ended survey responses, no new themes emerged, indicating we had enough data.”
- Explain how participant selection adds value: Highlight how you chose participants strategically, including the right voices.
- “For an ethnographic study, we observed 8 participants in their real work environments to uncover workflow gaps.”
- Justify the sample size with data, not assumptions: Use real examples from your research to show why more participants wouldn’t change the findings.
- “The last two focus groups repeated the same frustrations as earlier ones, confirming our key insights.”
- Compare with industry standards: Reference past studies with similar sample sizes to support your decision.
- “Prior field studies on shopping behavior found that observing 12–15 customers revealed most usability barriers.”
- Address practical realities without weakening credibility: If time or budget limited your study, explain how you still ensured strong, reliable insights.
- “With a tight timeline, we conducted remote diary studies, allowing participants to document experiences in real-time.”
Frequently Asked Questions (FAQs)
Before choosing the sample size for your qualitative research, also consider the following aspects:
What Is the Best Focus Group Sample Size for Effective Research?
In the Sage Journal (2019) study on the topic of saturation in focus groups (linked above) found that:
- Code saturation (no new topics come up) typically happened after 4 focus groups. By then, about 94% of topics were covered.
- Meaning saturation (fully understanding the topics) required about 5–6 focus groups, depending on how groups were divided (age, gender, etc.).
- Doing two groups per demographic category ( men, women, younger, older) usually gave the most complete picture.
- Adding more than two groups per category didn’t offer many extra insights.
When Should I Stop Collecting Data in Qualitative Research?
Stop collecting data when you’ve reached saturation:
- No new insights emerge from additional data.
- Themes repeat consistently.
- Further collection adds no significant understanding or nuance.
How Many Interviews Are Needed for Interview Saturation?
Interview saturation usually occurs within 12–15 interviews. Initial interviews reveal major themes, but after about 15, insights often repeat. The most complex topics can sometimes require up to 20–25 interviews.
For example, Field Nation’s marketplace redesign required interviewing over 20 accounts multiple times. Marvin streamlined note-taking, tagging, and thematic analysis, saving countless hours.
Book a free demo to see exactly how Marvin simplifies qualitative interviews and other research processes.
How Do I Ensure the Sample Characteristics in Research Are Representative?
To draw valid conclusions, your sample’s characteristics must represent the target population accurately. Here’s how you can ensure representativeness:
- Clearly define your target population.
- Use random or purposive sampling methods.
- Compare sample characteristics with population demographics.
- Regularly assess for biases and adjust your sampling accordingly.
What Are the Ethical Considerations in Determining Sample Size?
Ethical sample size decisions balance research validity with participant well-being. You want to avoid:
- Wasting the participants’ time or their contributions
- Using samples that are too small to produce valid insights
- Using samples that are larger than necessary and increase research risks
Conclusion
The importance of sample size in qualitative research is undeniable if you want to gain:
- Rich insights
- Resource efficiency
- Credibility
Too few participants might leave you with unclear data, while too many can overwhelm your team. The good news is that often, your findings will guide you. You just need to recognize emerging patterns, watch for repetition, and trust saturation.
This strategic process becomes more manageable with help from a tool like Marvin. Our end-to-end UX research repository with AI-powered workflows can handle data collection, tagging, and thematic analysis.
Ready to simplify your research? Try Marvin for free and quickly turn qualitative insights into action.
