50+ qualitative research questions examples for user research

Qualitative research is a cornerstone of user research, providing a deep understanding of user preferences, motivations, and behaviors. Unlike quantitative methods that focus on numbers and statistics, qualitative research methods: such as user interviews and usability testing—delve into the “why” and “how” behind user actions. By asking effective qualitative research questions, researchers can uncover valuable insights about how users interact with products, what pain points they encounter, and what drives their decisions.

A well-designed qualitative research project enables teams to move beyond surface-level feedback and gain a clear understanding of user experiences in their own words. This approach is essential for identifying unmet needs, refining product features, and ensuring that solutions truly address user problems. Whether you’re exploring new concepts or improving existing workflows, qualitative research helps you ask the right research questions and collect the rich, descriptive data needed to inform product development and user experience design.

Research design and planning

A successful research project begins with thoughtful research design and planning. Defining your research goals and understanding your target user are crucial steps in selecting the right research methods and crafting effective qualitative research questions. The research objective should guide every aspect of your qualitative research method, ensuring that the questions you ask are aligned with the insights you need to gather.

When planning your research design, focus on developing qualitative research questions that are open-ended and encourage participants to share their experiences in their own words. This approach allows for a deeper exploration of user behaviors, motivations, and pain points, leading to more actionable insights. By maintaining a clear understanding of your research goals and the needs of your target user, you can ensure that your research project yields relevant and meaningful data to drive decision-making.

Types of research questions

Understanding the different types of research questions is essential for designing an effective research project. Qualitative research questions are designed to explore user experiences, perceptions, and motivations, while quantitative research questions focus on measuring and comparing variables. Good qualitative research questions are open-ended, specific, and directly tied to the research topic, allowing participants to provide detailed responses without being influenced by leading questions.

There are several types of qualitative research questions, including exploratory questions that investigate new areas, explanatory questions that seek to understand reasons behind behaviors, descriptive questions that capture detailed accounts of experiences, and predictive questions that anticipate future actions or needs. By choosing the right type of research question for your qualitative research, you can ensure that your research project uncovers the insights necessary to inform product development and user experience improvements.

What makes questions truly open-ended

Open-ended questions invite expansive responses requiring explanation, storytelling, and detail rather than simple yes/no answers or single-word replies. While closed questions constrain responses to predetermined options, open-ended questions create space for users to share unexpected insights, reveal hidden motivations, and explain complex behaviors in their own words.

Using a mix of closed-ended and open-ended questions can provide both quantitative and qualitative feedback for better insights. Closed-ended questions are valuable for gathering quick, measurable data, while open-ended questions allow for deeper understanding and richer context.

A closed question asks: “Do you like our dashboard?” limiting responses to yes or no. An open-ended alternative asks: “Describe your experience using our dashboard” inviting specific examples, context about usage patterns, emotional reactions, pain points, and improvement ideas. The open-ended version generates 100x more actionable insight despite requiring only slightly different wording.

Airbnb user researchers discovered critical booking flow issues not through satisfaction ratings but by asking hosts: “Walk me through the last time you struggled to manage a booking.” The open-ended format revealed calendar synchronization confusion, pricing uncertainty, guest communication anxiety, and cleaning coordination challenges that closed questions about “calendar satisfaction” never surfaced.

Figma product teams validate features not by asking “Would you use real-time collaboration?” but instead: “Describe a recent situation where you needed to work with others on a design.” Users reveal specific collaboration patterns, tool switching frustration, version control problems, and feedback workflow inefficiencies informing feature requirements without leading users toward predetermined answers. It's important to avoid leading questions that suggest or push respondents toward a certain answer, as this can introduce bias and reduce the accuracy of your findings.

Effective open-ended questions share six characteristics. First, they begin with words like “How,” “Why,” “What,” “Describe,” or “Tell me about” rather than “Do you,” “Can you,” or “Would you.” Second, they focus on specific experiences and behaviors rather than abstract opinions. Third, they avoid suggesting expected answers through neutral language. Fourth, they ask one thing at a time avoiding compound constructions. Fifth, they invite storytelling through prompts encouraging narrative responses. Sixth, they generate insights researchers couldn’t anticipate by creating space for unexpected revelations. Additionally, concise questions help participants clearly understand the information you're seeking, preventing confusion and ensuring relevant insights.

Discovery and problem exploration templates

Recruiting participants and engaging research participants is essential to ensure a diverse and representative sample for discovery research. Crafting user research questions should align with your research goals and the specific information you need to gather. Discovery research uncovers user problems, current workflows, and unmet needs before defining product requirements. These open-ended templates reveal opportunities through understanding existing user behaviors and challenges.

Current workflow and process templates

“Walk me through your current process for [specific task].” This workflow mapping template captures step-by-step approaches, tools used, decision points, time investments, and frustration moments revealing improvement opportunities.

Slack researchers use: “Walk me through how your team currently shares project updates.” Users describe email threads, scattered Slack messages, status meetings, shared documents, and information loss revealing communication tool requirements.

“Describe a typical day managing [relevant responsibility].” This day-in-the-life template reveals routine behaviors, recurring challenges, tool switching patterns, and context providing comprehensive understanding of user reality.

Notion asks: “Describe a typical day managing your personal projects and notes.” Users reveal morning planning, throughout-day capture, evening review, weekend organization showing usage pattern opportunities.

“Tell me about the last time you needed to [accomplish specific goal].” This recent example template grounds abstract discussions in concrete experiences revealing real triggers, actual approaches, genuine obstacles, and emotional responses.

Calendly researchers ask: “Tell me about the last time you needed to schedule a meeting with someone outside your organization.” Users describe email back-and-forth, timezone confusion, calendar conflicts, and coordination friction—demonstrating the importance of understanding user needs through methods like buyer persona development.

“How do you currently solve [problem your product addresses]?” This alternatives exploration template reveals competing solutions including other products, manual processes, spreadsheets, or workarounds showing competitive context and switching drivers.

Airtable asks: “How do you currently track projects and collaborate with your team?” Users describe Trello boards, Google Sheets, Asana projects, email threads, or whiteboards revealing expectations and feature requirements.

“What tools do you use for [specific task], and how do they work together?” This tool stack template uncovers integration needs, context switching pain, feature gaps, and workflow continuity revealing platform and partnership opportunities.

Zapier uses: “What tools do you use for managing customer data, and how do they work together?” Users reveal CRM, email, spreadsheets, forms, analytics requiring manual data transfer and synchronization.

Collecting data from research participants using these templates helps gain insights into user pain points and unmet needs, which can guide product development and prioritization. For best results, consider recruiting participants for product research using proven strategies.

Pain point and challenge templates

“Describe the biggest challenge you face when trying to [accomplish goal].” This primary pain point template surfaces critical problems worth solving, their frequency and severity, current coping mechanisms, and impact on success.

Linear researchers ask: “Describe the biggest challenge you face when managing engineering work.” Users reveal unclear priorities, context switching, status reporting burden, and stakeholder alignment issues.

“What frustrates you most about [current approach or tool]?” This frustration template uncovers emotional pain points, usability barriers, missing capabilities, and breaking points triggering tool switching or abandonment.

Superhuman asks: “What frustrates you most about email?” Users describe inbox overload, finding old messages, maintaining context, following up, and achieving inbox zero.

“Tell me about a time when [current solution] let you down.” This failure story template reveals breaking points, edge cases, reliability issues, and critical moments when existing solutions fail users most severely.

Miro researchers probe: “Tell me about a time when remote collaboration tools let your team down.” Users describe workshop failures, idea loss, participant confusion, and technical difficulties.

“What takes longer than it should in your current workflow?” This inefficiency template identifies time sinks, manual processes, repetitive tasks, and automation opportunities representing high-value improvements.

Webflow asks: “What takes longer than it should when building and updating websites?” Users reveal design-to-code translation, responsive adjustments, content updates, and deployment processes.

“Describe a recent situation where you couldn’t accomplish what you needed.” This limitation template surfaces feature gaps, capability boundaries, workaround attempts, and unmet needs revealing expansion opportunities.

Figma researchers ask: “Describe a recent situation where Figma couldn’t handle what you needed.” Users reveal prototyping limitations, handoff challenges, version control needs, or developer collaboration gaps.

User research questions in this context can be used to understand user needs, preferences, and willingness to pay, helping to identify and address user pain points more effectively.

Experience and perception templates

Experience research explores how users feel about products, what creates positive or negative impressions, and what drives satisfaction or frustration. Descriptive questions help researchers understand how users perceive products and their user expectations. These templates uncover emotional responses and perception patterns.

Product experience templates

“Describe your first impression when you started using [product].” This initial reaction template captures immediate emotional responses, expectation matches or mismatches, interface clarity, and early adoption barriers.

Notion researchers use: “Describe your first impression when you started using Notion.” Users recall feeling “powerful but overwhelming,” “beautifully designed but confusing,” or “blank page intimidating.”

“What words would you use to describe [product]?” This perception language template reveals how users naturally characterize products, their emotional associations, perceived positioning, and communication gaps between intention and perception.

Superhuman asks users to describe their email app hearing “fast,” “keyboard-focused,” “expensive,” “exclusive,” “intimidating” revealing brand perception and positioning opportunities.

“Tell me about a time when [product] exceeded your expectations.” This positive moment template identifies delight factors, unexpected benefits, aha moments, and experience elements creating strong advocacy worth amplifying. Understanding user satisfaction and mental models in these moments can help improve product experience by aligning features with user expectations and how users perceive value.

Slack users describe discovering channels, integrations, or search capabilities unexpectedly solving problems revealing features worth emphasizing in onboarding and marketing.

“Walk me through a recent experience using [product] that frustrated you.” This negative moment template surfaces friction points, usability issues, missing features, or reliability problems creating dissatisfaction requiring resolution.

Zoom users describe audio issues, screen sharing confusion, meeting controls complexity, or recording challenges informing improvement priorities.

“How has [product] changed how you work?” This impact template measures workflow transformation, behavior changes, capability gains, and realized value versus expectations.

Airtable users describe replacing spreadsheets, improving collaboration, automating processes, or centralizing information showing value realization and expansion opportunities.

Qualitative user research questions are used to gather detailed, narrative feedback about user satisfaction and mental models, helping teams understand how users think, what they expect, and how they interact with products.

Comparative perception templates

“How does [product] compare to [alternative] you’ve used?” This comparative template reveals competitive positioning, relative strengths and weaknesses, differentiation perception, and switching motivations.

Linear users compare to Jira describing “faster,” “cleaner interface,” “better keyboard shortcuts,” “missing some customization” showing positioning and feature priorities.

“What would you lose if [product] disappeared tomorrow?” This essentiality template tests product dependency, unique value proposition, switching costs, and competitive moats through hypothetical loss.

Figma designers say “couldn’t collaborate remotely,” “back to version control chaos,” “need multiple tools,” showing strong product-market fit and defensibility.

“Describe the difference between [your product] and how you worked before.” This transformation template reveals value created, workflow improvements, capability gains, and problems solved validating product impact.

Calendly users describe eliminating “email back-and-forth,” “timezone math,” “double bookings,” “calendar conflicts” showing clear value proposition.

“What surprised you most about using [product]?” This unexpected insight template uncovers unanticipated benefits, hidden features, capability discoveries, or perception shifts revealing messaging and positioning opportunities.

Notion users discover “databases are powerful,” “templates save time,” “everything connects,” “it’s a wiki and task manager” revealing education needs.

“Tell me about how others on your team or in your organization perceive [product].” This indirect perception template reveals adoption barriers, stakeholder concerns, organizational dynamics, and expansion challenges through others’ viewpoints.

Miro users describe colleagues finding it “too complex,” “great for workshops,” “doesn’t replace docs,” “helps remote teams” informing segment targeting.

Usability and feature templates

Usability research evaluates product ease of use, feature clarity, and task completion effectiveness. Crafting effective usability testing questions is essential to evaluate the user journey and understand how participants interact with the product at each stage. These templates identify friction, confusion, and improvement opportunities during product interaction.

Task and navigation templates

“Walk me through what you’re trying to do right now.” This task clarification template confirms user goals, reveals task interpretation, identifies expectation mismatches, and surfaces confusion during usability testing.

Dropbox researchers use this during sharing tasks discovering users sometimes want collaboration, sometimes distribution, sometimes backup revealing feature distinction needs.

“Describe how you would find [specific feature or information].” This findability template tests information architecture, navigation clarity, menu labeling, and search effectiveness without directly showing locations.

Gmail testing reveals users search settings in account preferences, individual message menus, or help documentation depending on feature type.

“What do you expect to happen when you [take specific action]?” This expectation template surfaces mental model assumptions before interaction revealing interface clarity, predictability, and user understanding gaps.

Spotify researchers ask about playlist actions discovering users expect different privacy settings, sharing behaviors, or collaborative editing than provided.

“Tell me what’s confusing or unclear on this screen.” This comprehension template identifies terminology issues, information overload, layout problems, or missing context creating user confusion during interfaces evaluation.

Zoom testing reveals meeting controls, audio/video settings, and screen sharing options create initial confusion requiring interface or onboarding improvements.

“Describe your thought process as you complete this task.” This think-aloud template captures real-time cognitive processes, decision-making, hesitation points, and understanding revealing usability issues during observation.

Airbnb booking flow testing hears users question pricing breakdowns, wonder about cancellation policies, compare options revealing friction before abandonment.

Qualitative data collected from these open-ended usability testing questions provides deeper insights into user behavior, motivations, and pain points throughout the user journey, rather than just quantitative metrics.

Learning and onboarding templates

“Walk me through your first experience using [feature].” This initial usage template captures discovery processes, learning approaches, early confusion, and first impressions informing onboarding design.

Figma tracks component usage discovering users struggle with variants, properties, and instances requiring extensive education and clearer affordances.

“What help or guidance did you need when getting started?” This support need template identifies knowledge gaps, documentation requirements, tutorial opportunities, and confusion points during early adoption.

Webflow users need help with responsive design, CSS properties, interactions, and CMS setup revealing onboarding content priorities.

“Describe when you felt you understood how to use [product or feature] effectively.” This competency milestone template identifies aha moments, learning patterns, time-to-value, and expertise development informing progressive disclosure strategies.

Notion users achieve understanding when grasping databases, templates, and relations but may struggle for weeks without proper guidance.

“Tell me about mistakes you made when learning [product].” This error template reveals common pitfalls, conceptual misunderstandings, interface traps, and failure recovery needs during learning curves.

Zapier users describe trigger/action confusion, data field mapping errors, testing failures, and unexpected results requiring better error messaging and education.

“How did you figure out how to accomplish [specific task]?” This discovery template reveals learning methods including experimentation, documentation, support, colleagues, or external resources informing support strategy.

Slack users primarily learn through experimentation and colleague observation rather than documentation suggesting in-app guidance and social learning.

Open-ended qualitative research questions in these templates encourage participants to share detailed narratives during data collection methods such as interviews or focus groups, resulting in rich, descriptive data about their onboarding and learning experiences.

Feature validation and prioritization templates

Feature validation research tests concepts, prioritizes development, and validates market fit before engineering investment. These templates assess feature value, adoption likelihood, and competitive necessity.

Concept testing templates

“Describe how you would use [proposed feature] in your workflow.” This usage scenario template validates feature utility, uncovers application patterns, identifies integration needs, and exposes adoption barriers. Focusing on a particular feature during concept testing can provide valuable insights for user-centered product development, ensuring that the feature aligns with real user needs and enhances the overall experience.

Asana tests features asking: “Describe how you would use timeline dependencies.” Users reveal understanding, value perception, and specific use cases or struggle to articulate applications.

“What problem would [feature] solve for you?” This problem-solution fit template confirms value proposition, reveals primary benefits, identifies unexpected applications, and validates problem severity.

Monday.com asks: “What problem would recurring task automation solve?” Hearing “eliminate weekly setup,” “ensure consistency,” “save hours” validates investment.

“Tell me about situations when you would use [feature].” This context template identifies trigger conditions, usage frequency, specific scenarios, and feature necessity revealing adoption likelihood.

Linear probes their tool versus Jira, Notion, or spreadsheets discovering specific project types and team characteristics favoring each approach.

“What concerns do you have about [proposed feature]?” This barrier template surfaces adoption obstacles including learning curve, workflow disruption, complexity, cost, or integration worries.

Notion users express database concerns like “seems complicated,” “team adoption worries,” “migration fears” revealing onboarding needs.

“How would you explain [feature] value to teammates or management?” This value articulation template tests whether users understand benefits, can communicate advantages, and perceive clear ROI supporting adoption.

Miro users articulating “faster workshops,” “better alignment,” “reduced meetings” demonstrate understanding versus those struggling to explain value.

Prioritization templates

“If you could change one thing about [current approach], what would it be?” This priority template identifies highest-impact opportunities from user perspective without biasing toward specific features. User research questions can be categorized into descriptive, comparative, and causal types. Comparative questions help evaluate the differences or similarities between two or more design variations, while causal questions seek to uncover the reasons behind user behavior—both approaches provide valuable insights for prioritizing user-centered features.

Figma regularly hears requests for component management, collaboration improvements, version control, and mobile support revealing roadmap priorities.

“Describe which of these capabilities matters most to you and why.” This forced ranking template prioritizes competing features, reveals decision criteria, and exposes segment differences.

Airtable testing gantt charts, forms, automations, and integrations discovers enterprise customers prioritize integrations while SMBs emphasize forms.

“Tell me about the last time you wanted to [do something your product doesn’t support].” This gap identification template surfaces unmet needs, workarounds, frustration points, and expansion opportunities through actual missed capabilities.

Webflow users describe wanting better CMS features, easier responsive design, advanced interactions, or team collaboration revealing development priorities.

“What would prevent you from adopting [proposed feature]?” This blocker template identifies barriers including complexity, cost, workflow fit, technical limitations, or competing priorities.

Zapier AI feature research reveals “trust concerns,” “need control,” “unclear value” requiring education, positioning, and gradual rollout strategies.

“Walk me through when you would choose [feature] versus [alternative approach].” This context template validates feature necessity, reveals selection criteria, and confirms clear decision logic exists.

Notion users explain when they’d use databases versus simple lists, when templates help versus starting fresh revealing feature positioning.

Customer development and buying templates

Customer development research validates market opportunities, understands buying processes, and informs go-to-market strategy. Regularly conducting user research helps track changing customer needs and preferences, ensuring your product remains competitive. These templates explore decision-making and competitive dynamics.

Purchase decision templates

“Walk me through how you decided to try [product].” This acquisition journey template captures discovery, evaluation, decision, and onboarding revealing marketing channels, decision factors, and conversion barriers.

Superhuman users describe “heard from founders,” “saw Twitter buzz,” “tried waitlist,” “invited by friend” revealing community-driven acquisition strategy.

“Describe what factors mattered most when evaluating solutions.” This criteria template identifies decision priorities including features, price, ease, integration, support, brand guiding positioning and messaging.

Notion buyers emphasize “flexibility,” “collaboration,” “ease of use,” “affordable pricing” versus competitors highlighting “powerful but complex.”

“Tell me about other products you considered and why you chose this one.” This competitive template reveals consideration sets, evaluation criteria, differentiation perception, and final choice drivers.

Linear users compared Jira, Asana, ClickUp citing “speed,” “keyboard shortcuts,” “clean interface” as differentiators showing positioning opportunities.

“What almost prevented you from choosing [product]?” This objection template surfaces barriers including price, features, integration, implementation, or competitor advantages requiring response.

Webflow prospects express “learning curve concern,” “scalability worries,” “team adoption risk” requiring case studies, training, and migration support.

“Describe how you justify [product] cost to yourself or stakeholders.” This ROI template uncovers value articulation, benefit quantification, budget processes, and organizational concerns informing pricing strategy.

Zapier customers calculate “saved 10 hours weekly,” “enabled workflows,” “reduced errors,” “avoided hiring” supporting expansion and enterprise sales.

Adoption and impact templates

“Tell me how [product] has changed your work or workflow.” This transformation template measures realized benefits, unexpected consequences, behavior changes, and actual value delivery. User research questions in this area can help measure customer satisfaction and track how perceptions and needs change over time.

Slack users describe “faster decisions,” “reduced email,” “improved transparency,” “better remote work” confirming value and generating testimonials.

“What would you lose if [product] disappeared tomorrow?” This dependency template reveals switching costs, unique value, competitive advantage, and product essentiality.

Figma designers say “couldn’t collaborate,” “need multiple tools,” “version control chaos” showing strong product-market fit and retention drivers.

“Describe features you use most and why they matter.” This usage template identifies core value drivers, workflow integration, priorities, and potential expansion opportunities.

Notion power users emphasize databases, templates, sharing revealing marketing, onboarding, and development emphasis areas.

“What’s missing that would make [product] indispensable?” This gap template surfaces unmet needs, competitive vulnerabilities, and completion opportunities for product-market fit.

Airtable users request “offline access,” “advanced permissions,” “enterprise SSO” showing progression from current to enterprise positioning.

“Tell me about how you would describe [product] to colleagues.” This word-of-mouth template reveals positioning perception, value articulation, and referral messaging in users’ own language.

Superhuman users say “email for power users,” “keyboard-first inbox,” “helps achieve inbox zero” showing clear positioning and target audience.

Common open-ended question mistakes

Even experienced researchers can reduce insight quality by making these mistakes when crafting open-ended questions for user interviews. Writing questions carefully is essential to encourage honest answers from participants, ensuring you gather genuine and unbiased insights.

Leading questions bias responses
Example: “How much do you love our new feature?” assumes positivity.
Better: “How has the new feature affected your workflow?” invites honest feedback.
Testing your questions for bias by having someone review them can ensure they are understandable and neutral. Avoiding leading questions is crucial to ensure unbiased responses in both user research and qualitative research.

Compound questions confuse participants
Example: “How do you use our product and what features do you like and what would you change and how often do you use it?”
Better: Ask separate questions about usage, favorites, improvements, and frequency.

Hypothetical questions yield unreliable answers
Example: “Would you pay $50/month for premium features?”
Better: “Tell me about the last time you paid for software. What made it worth it?”

Vague questions lack specificity
Example: “What do you think about our product?”
Better: “Walk me through the last time you used our product.”

Yes/no questions limit depth
Example: “Do you find our interface confusing?”
Better: “Describe your experience navigating our interface.”

Assuming facts frustrates participants
Example: “When did you stop having problems with our product?”
Better: “Are you currently experiencing any challenges? If so, describe them.”

Best practices for open-ended questions

To create effective open-ended questions that elicit rich and actionable user insights, follow these key practices:

Start with open wordsUse starters like “How,” “Why,” “What,” “Describe,” or “Tell me about” to invite detailed responses and storytelling.

Focus on specific behaviorsAsk about concrete actions or recent experiences rather than general opinions to gain actionable insights.

Use neutral languageAvoid words that suggest desired answers to maintain neutrality and encourage honest feedback.

Ask one question at a timeKeep questions clear, concise, and specific to avoid confusion and incomplete answers.

Sequence questions thoughtfully
Begin broadly and move to specifics, building rapport and understanding progressively. Preparing an interview guide or script helps process researchers prioritize the right user research questions and maintain focus throughout the session.

Prepare follow-up probes
Use prompts like “Can you give an example?” or “Tell me more about that” to deepen responses. It's important to ask follow-up questions during user interviews to gather deeper insights and clarify participant responses.

Test questions beforehandPilot your questions to identify and fix any confusing or biased wording before research sessions.

Process researchers use systematic approaches, such as interviews and focus groups, to determine the best questions to ask at each stage of user research. Crafting the right user research questions and asking effective follow-up questions are essential for gathering meaningful insights and improving the quality of your research.

Conclusion

In summary, qualitative research is an invaluable tool for understanding user preferences, behaviors, and pain points. By crafting effective qualitative research questions and employing the right research methods, researchers can collect valuable insights that drive product development and enhance user experience. A well-designed research project starts with clear research goals, a focus on the target user, and a commitment to open-ended, unbiased questions that allow participants to share their thoughts in their own words.

Remember, the success of your qualitative research depends on thoughtful research design, the use of user interviews and usability testing, and a deep understanding of your research objectives. By following these best practices, you can ensure your research project provides actionable insights that truly reflect user needs and preferences, helping your team build better products and deliver exceptional user experiences.

Ready to act on your research goals?