Qualitative methods for product teams: interviews, usability testing, ethnography, diary studies, focus groups, card sorting
Qualitative research methods explore user experiences, behaviors, and motivations through rich narrative data that inform product decisions. Unlike quantitative methods that measure what and how many, qualitative methods reveal why and how through stories, observations, and context.
Product teams use these methods throughout development—from early discovery to post-launch—to understand users deeply, uncover unmet needs, and gain insights users can’t articulate directly. This guide covers six key qualitative methods: user interviews, usability testing, ethnographic studies, diary studies, focus groups, and card sorting, explaining when and how to use each and the insights they provide. It also introduces research tools that support these methodologies.
Mixed-methods research integrates qualitative and quantitative data for a comprehensive understanding of user problems, enabling better-informed decisions.
There are several research approaches available to product and UX teams, each offering unique strengths. Qualitative research focuses on gathering in-depth, non-numerical data to understand user experiences, attitudes, and behaviors. Methods like user interviews, focus groups, and ethnographic research allow teams to explore the “why” behind user actions, uncovering rich, contextual insights that might otherwise go unnoticed. In contrast, quantitative research relies on numerical data and statistical analysis to identify patterns, trends, and correlations at scale. Techniques such as surveys, usability testing, and A/B testing provide measurable, statistically significant results that can validate hypotheses and track changes over time. By combining qualitative and quantitative methods, teams gain a more comprehensive understanding of their users—balancing deep, narrative insights with broad, actionable data. This integrated approach ensures that research findings are both meaningful and generalizable, supporting confident decision-making throughout the product lifecycle.
User interviews are a qualitative research method involving open-ended and guided discussions with users to explore their experiences, needs, behaviors, and motivations. Through these conversations, researchers generate detailed responses revealing problems, contexts, and opportunities.
When to use user interviews
Use interviews for early product discovery identifying user needs and pain points, feature validation testing concepts before development, understanding complex workflows requiring detailed explanation, exploring motivations and decision processes, and investigating sensitive topics requiring privacy and trust. In-depth interviews are particularly useful for exploring lived experiences, emotions, and sensitive topics, providing rich personal accounts that help uncover underlying meanings related to a specific phenomenon or product.
Figma researchers conduct interviews exploring design collaboration challenges, tool switching patterns, and workflow inefficiencies informing feature priorities and product strategy. These conversations reveal unstated needs and contextual factors impossible to capture through other methods.
How to conduct effective interviews
Recruit 5-15 participants per user segment matching target audience. More homogeneous segments need fewer interviews while diverse segments require more achieving saturation where new interviews generate minimal new insights.
Prepare discussion guide with 8-12 primary open-ended questions plus follow-up probes. Questions should begin with “how,” “why,” “what,” “describe,” or “tell me about” inviting storytelling rather than yes/no answers.
Conduct 45-60 minute sessions allowing sufficient depth without fatigue. Start with rapport building, move through core questions using think-aloud and follow-up probes, and conclude with open-ended closing questions capturing additional insights. Customer interviews are also a valuable technique for concept testing, allowing teams to gather qualitative feedback on new ideas or products before development.
Record sessions with permission enabling transcription and detailed analysis. Take notes during interviews capturing key quotes, observations, and follow-up topics but maintain primary focus on active listening and probing.
What insights interviews generate
Interviews reveal workflow details and process understanding, pain points and frustration sources, workarounds indicating feature gaps, decision criteria and prioritization factors, and emotional responses driving satisfaction or dissatisfaction. Analyzing user responses is crucial to uncovering underlying motivations, needs, and preferences that inform product decisions.
Notion interviews revealed new users experience “blank page paralysis” uncertain how to start, database concepts confuse without concrete examples, and users need progressive disclosure rather than overwhelming feature exposure. These insights directly informed onboarding redesign improving activation rates.
Usability testing observes users attempting realistic tasks with products or prototypes, identifying confusion, friction, and experience issues through direct observation of actual interaction rather than reported behavior.
When to use usability testing
Use testing for evaluating interface designs before development, identifying navigation and findability issues, discovering confusion points and unclear terminology, measuring task completion success, and comparing design alternatives through preference and performance.
Slack conducts usability testing with channel organization and notification settings ensuring proposed changes improve rather than complicate experience before engineering investment.
How to conduct effective testing
An important first step for effective testing is ensuring you recruit the right participants. Learn more about how to recruit the right participants for research to enhance the quality and impact of your tests.
Recruit 8-12 participants per user type sufficient for identifying major usability issues. Nielsen research shows 5 users find 85% of problems; testing multiple rounds with small samples proves more effective than single large study.
Create realistic task scenarios matching actual use cases like “Create a new project and invite your team members” rather than “Click the create button.” Realistic scenarios reveal natural behavior versus artificial test compliance.
Usability testing often involves having users complete tasks in either a controlled environment or through remote testing. In a controlled environment, researchers can observe participants in a structured setting, which helps gather detailed insights, though it may not fully replicate real-world conditions. Remote testing allows usability studies to be conducted with participants in their own environments, increasing diversity and convenience, and enabling the collection of data from a broader user base.
Use think-aloud protocol asking participants to verbalize thoughts while completing tasks. Encourage continuous narration: “Tell me what you’re thinking as you try to accomplish this.” Thinking aloud reveals confusion, expectations, and decision-making invisible through observation alone. For more on research-backed UX strategies, explore best practices that improve usability and user experience.
Observe where participants hesitate, click wrong areas, express confusion, or require hints. Note specific usability issues, mental model mismatches, terminology problems, and successful interaction patterns, and synthesize research.
Tree testing is another qualitative research method used to evaluate the information architecture of a website or application. It is often used alongside card sorting to test how well users can navigate and locate content within a hierarchical structure, especially early in the design process.
Conduct moderated testing for complex products needing explanation or unmoderated testing for simple tasks enabling larger samples and faster turnaround. Both approaches provide valuable insights for different contexts.
What insights testing generates
Testing reveals findability issues where users can’t locate features, comprehension problems with unclear terminology or interfaces, workflow friction through inefficient task paths, error recovery difficulties when things go wrong, and delight factors creating positive experiences.
Calendly testing discovered meeting type configuration confused users with too many upfront options creating abandonment. Simplified progressive disclosure showing advanced options after basic creation improved completion rates significantly.
Ethnographic research involves observing users in their natural environment, focusing on real world user behavior to understand how they actually work, interact with tools, and solve problems in real environments. This approach reveals contextual factors and unstated needs invisible in interviews or labs.
When to use ethnography
Use ethnography for understanding complex workflows in context, discovering unstated needs users don’t recognize, revealing workarounds indicating product gaps, understanding tool usage within broader work ecosystems, and informing strategic product direction requiring deep contextual understanding.
Figma embedded researchers with design teams observing actual work including design reviews, handoff meetings, and individual design revealing component maintenance burden, version control struggles, and handoff communication challenges.
How to conduct effective ethnography
Identify research sites providing rich observation opportunities matching target users. Recruit 6-12 teams or individuals allowing extended observation revealing patterns across contexts.
Spend extended time (days or weeks) observing natural work without intervention. Take extensive fieldnotes documenting actions, interactions, tool usage, workarounds, and context. Photograph workspaces, whiteboards, and artifacts providing environmental understanding.
Observe product usage in both natural and controlled environments to understand how users interact with products in real-world settings as well as in more structured scenarios.
Conduct contextual inquiry combining observation with informal questioning asking “Why did you just do that?” or “What are you trying to accomplish?” understanding decisions in moment without disrupting flow.
Schedule follow-up interviews exploring observed patterns asking participants to explain workflows, workarounds, and frustrations deepening understanding beyond observation.
What insights ethnography generates
Ethnography reveals workflow complexity and interdependencies, tool ecosystems and integration needs, workarounds indicating feature gaps, cultural and organizational dynamics affecting adoption, and strategic opportunities beyond incremental improvements.
Field studies involve observing users in their natural environment to inform design decisions with real-world context.
Linear ethnographic research discovered engineering managers spend hours weekly manually aggregating status across tools creating “status compilation tax.” This insight informed unified project views eliminating manual aggregation rather than incremental reporting improvements.
Diary studies track user experiences over time asking participants to document activities, feelings, and events through written entries, photos, videos, or voice recordings revealing longitudinal patterns impossible to capture in single interviews.
When to use diary studies
Use diary studies for understanding behavior changes over time, tracking onboarding experiences through first weeks, revealing usage patterns across varied contexts, understanding decision journeys spanning days or weeks, and identifying critical moments affecting retention or satisfaction.
Notion conducted diary studies with new users tracking first 30 days identifying when users get stuck, succeed, or abandon revealing distinct learning phases with different challenges and intervention opportunities.
How to conduct effective studies
Recruit 20-30 participants committed to regular entries over study duration. Larger samples compensate for dropout and irregular participation common in longitudinal research.
Define study duration matching research questions: 1-2 weeks for onboarding studies, 2-4 weeks for usage pattern research, or 4-8 weeks for behavior change investigations.
Provide clear prompting questions guiding entries without overly constraining responses: “What did you try to accomplish today?”, “What confused or frustrated you?”, “What felt successful?”, “What almost made you quit?”
Diary studies are especially effective for gathering qualitative data, as participants provide open-ended responses in their entries, allowing researchers to understand motivations, unmet needs, and opinions in depth.
Collect entries through mobile apps, email, or online forms making participation convenient. Send regular reminders maintaining engagement throughout study.
Conduct periodic check-in interviews at key milestones (days 3, 7, 14, 30) discussing entries, exploring patterns, and understanding evolving experiences.
What insights diary studies generate
Diary studies reveal behavior evolution and learning curves, critical moments affecting satisfaction, context variation and situational usage, retention risk factors and abandonment triggers, and temporal patterns invisible in single-session research.
Superhuman diary studies revealed first 48 hours critical for habit formation with users either incorporating inbox zero workflow quickly or reverting to previous email habits. This insight focused onboarding on rapid habit creation rather than comprehensive feature education.
Focus groups are a qualitative research method that brings 6-10 participants together in a group setting for moderated group discussions. These sessions explore shared experiences, perspectives, and reactions, with group dynamics revealing collective attitudes and social influences on behaviors and preferences. Focus groups study a group of people, their beliefs, and opinions to inform product development and messaging strategies.
When to use focus groups
Use focus groups for exploring market perceptions and positioning, understanding group decision dynamics, gathering feedback, generating ideas through collaborative brainstorming, testing concepts and messaging with diverse reactions, and understanding cultural or community norms affecting adoption.
Focus groups work best early in research for exploration or late for validation but rarely for detailed workflow understanding or usability evaluation better addressed through individual methods.
How to conduct effective focus groups
Recruit 6-10 participants per group with similar backgrounds or experiences enabling comfortable sharing. Conduct 3-4 groups per study capturing diverse perspectives and identifying consistent patterns versus group-specific dynamics.
Facilitate 90-120 minute sessions with a structured discussion guide balancing prepared questions with organic conversation flow. Strong facilitation of group discussions is essential to explore shared experiences and opinions, and to prevent dominant participants from overwhelming quieter voices while maintaining productive discussion focus.
Use activities beyond discussion including concept sorting, prioritization exercises, or collaborative ideation stimulating engagement and revealing preferences through action versus just talk.
Record sessions and observe body language, group dynamics, agreement and disagreement patterns, and enthusiasm or hesitation about topics providing context beyond verbal content.
What insights focus groups generate
Focus groups reveal shared attitudes and perceptions, social influences on behavior, language and terminology users naturally use, concept reactions and messaging resonance, and group norms affecting adoption decisions.
Calendly focus groups explored scheduling coordination perceptions discovering users viewed automated scheduling as both “professional and organized” and potentially “impersonal or cold” revealing positioning balance needed between efficiency and personal touch.
Card sorting asks participants to organize topics, features, or content into groups and categories revealing mental models about relationships and logical organization informing information architecture and navigation design.
When to use card sorting
Use card sorting for organizing features into menus or categories, structuring navigation and information architecture, grouping related content or functionality, naming categories reflecting user language, and understanding how different user segments conceptualize organization differently. Card sorting can also be used as part of concept testing to evaluate new information architectures or feature groupings before launch, helping to validate and refine concepts based on user input.
Linear used card sorting organizing keyboard shortcuts into categories users could find easily discovering users organized by workflow context rather than technical function.
How to conduct effective card sorting
Recruit 15-20 participants per user segment sufficient for identifying consistent patterns across individual variation. Remote card sorting enables larger samples while in-person provides richer observation of reasoning.
Use open card sorting allowing participants to create category names or closed sorting with predetermined categories depending on research goals. Open sorting reveals mental models while closed sorting validates proposed structures.
Provide clear instructions asking participants to organize cards into groups that make sense to them. Encourage thinking aloud explaining rationale for groupings and category names. To supplement card sorting, include survey questions to gather additional user input on their choices, preferences, and reasoning, which can improve the quality and depth of user responses.
Analyze results identifying frequently co-grouped items, common category names, and disagreement areas revealing different mental models requiring accommodation or analysis methods for effective qualitative insights.
What insights card sorting generates
Card sorting reveals user mental models and conceptual frameworks, logical groupings and relationships, appropriate category names using user language, organization differences across user segments, and navigation structures matching user expectations.
Notion card sorting discovered users organized features by use case (documentation, project management, personal notes) rather than technical capability (pages, databases, embeds) informing navigation redesign around job-to-be-done rather than feature types.
Conducting research involves a series of deliberate steps to ensure that the insights gathered are reliable and actionable. The process begins by defining clear research goals and formulating specific research questions. Selecting the right research method is crucial—user interviews and diary studies are ideal for exploring in-depth motivations and behaviors, while surveys and usability testing are better suited for collecting quantitative data on user interactions. It’s important to carefully consider your target audience, choosing participants who accurately represent your user base. The choice of data collection tools and sampling methods also plays a key role in ensuring the validity and reliability of your findings. By aligning your research design with your objectives, you can confidently gather the data needed to inform product decisions and address user needs.
Select methods matching research questions, development stage, available resources, and information needs using systematic decision frameworks. Choosing the right user research methods is essential for addressing specific research goals and ensuring actionable insights.
Match methods to research questions
Use interviews exploring experiences, motivations, and complex workflows. Use usability testing evaluating specific interactions and interfaces and identifying potential improvements in user experience, functionality, or design. Use ethnography understanding work in natural contexts, though this method can be time consuming due to the need for extended observation. Use diary studies tracking changes over time. Use focus groups exploring perceptions and group dynamics. Use card sorting understanding organization and mental models.
Qualitative research is particularly useful for exploring new concepts, enhancing product development, or deepening brand engagement. It can also provide insights into brand perception and evaluate the impact of marketing campaigns. Qualitative research is best used when an in-depth understanding of consumer attitudes, feelings, or behaviors is needed.
Consider development stage
Early discovery benefits from interviews and ethnography exploring problems broadly. Mid-development uses usability testing and card sorting refining specific designs. Post-launch employs diary studies and interviews understanding actual adoption.
Account for resources and constraints
Methods vary in cost, timeline, and complexity. Interviews cost $3,000-$10,000 for 10-15 participants over 2-3 weeks. Usability testing costs $5,000-$15,000 for 8-12 participants over 3-4 weeks. Ethnography costs $15,000-$50,000+ over 4-8 weeks and is often time consuming due to the need for real-world, extended observation. Diary studies cost $8,000-$20,000 over study duration plus 2-3 weeks analysis.
Combine complementary methods
Strong research programs use multiple methods triangulating insights. Sequential approaches use interviews for discovery then usability testing for validation and to identify potential improvements. Parallel approaches combine interviews with diary studies capturing both depth and temporal patterns.
Qualitative research design is often not linear like quantitative design. Qualitative research is best used in tandem with quantitative research, as it can provide rich, detailed feedback that gives depth to quantitative research. It can also help clarify quantitative data and refine hypotheses for future research. Qualitative research helps generate hypotheses to further investigate and understand quantitative data.
Mixed-methods research allows researchers to explore complex phenomena by combining numerical data with rich, contextual insights. The combination of qualitative and quantitative methods in mixed-methods research can lead to more robust and reliable findings. Using mixed-methods research can help address research questions that require both statistical analysis and in-depth understanding of participant perspectives, which is particularly useful in fields where understanding human behavior and experiences is essential.
Market research often combines qualitative and quantitative data to inform product and marketing strategies, collaborating with consumers and observing real-world behaviors to drive potential improvements in customer experience and product development.
Effective analysis transforms raw data into actionable insights through systematic processes regardless of collection method. Qualitative data analysis is the process of interpreting and extracting meaningful insights from qualitative studies, such as interviews, focus groups, and observations. This involves coding, identifying themes, and developing theories or narratives from non-numerical data.
Organize and prepare data
Transcribe recordings, compile notes and observations, anonymize participant information, and create a centralized repository for all materials.
Code systematically
Apply descriptive labels to text segments identifying themes, patterns, and concepts. Use tools ranging from spreadsheets to specialized software like Dovetail or NVivo supporting coding and theme development. The grounded theory method, or grounded theory, is often used in qualitative research to develop theories directly from data through iterative comparison, especially when exploring complex phenomena without preset hypotheses.
Identify themes and patterns
Group related codes into higher-level themes revealing insights across participants. Thematic Analysis is a key process for identifying, analyzing, and reporting patterns across qualitative data. Document theme definitions, supporting evidence, and implications for product decisions.
Additional qualitative data analysis methods
For more insight into minimizing bias during user research, see Types of Bias in User Research and How to Overcome?.
Content Analysis systematically evaluates patterns in communication across multiple sources, quantifying qualitative data at scale. Document Analysis involves studying existing texts or records for historical, cultural, or social insights. Case Studies are intensive studies of a single individual, group, or event that use multiple data sources to portray a holistic picture, all of which can play a role in formulating research problems.
Validate and triangulate: For more effective research, it's important to start by clearly formulating your research problem, ensuring robust foundations before validation and triangulation.
Check themes against original data ensuring accuracy. Compare findings across participants identifying consensus and variation. Triangulate with other data sources including analytics, surveys, or secondary research.
Connect to action
Explicitly link findings to product opportunities whether features to build, experiences to improve, or strategies to pursue. Strong research clearly answers “so what?” and “what should we do?”
Once data is collected, the next step is to interpret the findings and translate them into actionable insights. In qualitative research, this means coding and categorizing responses to identify recurring themes, patterns, and underlying meanings. For quantitative research, statistical analysis and data visualization help reveal trends, correlations, and outliers within the data collected. The goal is to draw conclusions that directly address your research questions and inform next steps—whether that’s refining a user flow, prioritizing new features, or rethinking a product strategy. It’s also important to acknowledge the limitations of your study, consider potential biases, and identify areas for future research. By thoughtfully interpreting your findings, you ensure that your UX research drives meaningful improvements and supports ongoing learning.
The true value of UX research lies in how its insights are applied to create better products and experiences. Applying research insights means collaborating with designers, product managers, engineers, and other stakeholders to translate findings into concrete design changes and strategic decisions. Effective communication is key—presenting research in clear, concise language ensures that everyone understands the user needs and opportunities uncovered. By centering design and development efforts around real user feedback, organizations can positively impact user satisfaction, engagement, and loyalty. Ultimately, applying research insights leads to user-centered products that not only meet business goals but also deliver meaningful, enjoyable experiences for the people who use them.
How many participants do I need?
Typical ranges: 5-15 for interviews per segment, 8-12 for usability testing, 6-12 teams for ethnography, 20-30 for diary studies, 18-30 for focus groups (3-4 groups), and 15-20 for card sorting per segment.
How much does qualitative research cost?
Costs vary by method: interviews $3,000-$10,000, usability testing $5,000-$15,000, ethnography $15,000-$50,000+, diary studies $8,000-$20,000, focus groups $8,000-$15,000, and card sorting $3,000-$8,000.
How long does research take?
Timeline varies: interviews 2-3 weeks, usability testing 3-4 weeks, ethnography 4-8+ weeks, diary studies span study duration plus 2-3 weeks analysis, focus groups 3-4 weeks, and card sorting 2-3 weeks.
Can I do qualitative research with small budgets?
Yes, methods scale. Conduct 5 guerrilla interviews, test with friends and family, use free tools, or conduct remote research reducing costs significantly while maintaining insight quality.
Should I hire researchers or do it myself?
Product teams can conduct basic qualitative research with training. Consider hiring for complex studies, high-stakes decisions, or when objectivity matters. Many use hybrid approaches. Action research is another option—this participatory method involves researchers working alongside participants to identify and solve problems together.
How do I convince stakeholders to invest?
Share examples of decisions improved by research, calculate costs of building wrong features, demonstrate quick turnaround, involve stakeholders in observations, and start small proving value. Emphasize the importance of customer feedback gathered through qualitative research methods, as it provides actionable insights to improve products and services.
Can I combine qualitative and quantitative methods?
Yes, mixed-methods research is common. Qualitative research can help clarify quantitative data, refine hypotheses for future research, and generate new hypotheses to further investigate and understand quantitative findings. This approach provides a more comprehensive understanding of user needs and behaviors.
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