Open ended qualitative questions: 30+ templates for user interviews

Open-ended questions invite expansive responses requiring explanation, storytelling, and detail rather than simple yes/no answers or single-word replies. These questions are designed to get detailed answers that provide a broad range of insights, helping researchers understand complex topics and personal experiences. Open-ended qualitative questions are essential for exploring complex topics and generating new theories. While closed-ended questions limit answers to set options, typically yes/no or ratings, they are useful for gathering quantitative data but do not elicit detailed responses. In contrast, open-ended questions give users the chance to share unexpected insights, hidden reasons, and explain behaviors in their own words.

A closed question asks: “Do you like our dashboard?” allowing only yes or no answers. While useful for quick, quantitative data, closed-ended questions can't reveal user motivations or detailed experiences. An open-ended alternative like “Describe your experience using our dashboard” invites richer, more helpful answers about how users interact with the product, their feelings, and ideas for improvement. Asking open-ended questions is key to gaining deeper insights into user behavior.

Airbnb user researchers found important problems in the booking process not by asking if users were satisfied but by asking hosts: “Walk me through the last time you had trouble managing a booking.” This open-ended question revealed issues like calendar syncing problems, unclear pricing, worries about guest communication, and cleaning coordination challenges that yes/no questions never showed. Open-ended questions allow many possible answers instead of limiting responses, making them key for getting detailed and complete feedback. User interviews provide direct access to the thoughts, feelings, and experiences that shape how people interact with a product or service, and collecting feedback through open-ended questions helps researchers gather data for deeper analysis.

Figma product teams test features not by asking “Would you use real-time collaboration?” but by asking: “Describe a recent time you needed to work with others on a design.” Users share how they collaborate, frustrations with switching tools, version control issues, and feedback problems. This helps define feature needs without leading users to certain answers.

Good open-ended questions have six key features: they start with words like “How,” “Why,” or “Describe”; focus on real experiences; avoid leading language; ask one thing at a time; encourage storytelling; and allow for unexpected insights. Building rapport with participants is essential to get honest, detailed responses. Manual coding is commonly used to analyze the rich feedback gathered from these questions.

Introduction to qualitative research

Qualitative research is a powerful approach for uncovering the deeper motivations, attitudes, and behaviors of your target audience. Unlike quantitative methods that focus on numbers and statistics, qualitative research gathers rich, nuanced data through methods like user interviews, observations, and open-ended questions. By encouraging participants to share their experiences in their own words, researchers can gain valuable insights that go beyond surface-level feedback.

User interviews are a cornerstone of qualitative research, allowing you to ask open-ended questions that prompt detailed responses and stories. This approach helps you understand not just what users do, but why they do it—revealing pain points, unmet needs, and unexpected opportunities. The detailed responses collected through qualitative research provide a foundation for drawing meaningful conclusions and making informed decisions about product development, marketing, and customer experience. By focusing on open-ended questions and encouraging participants to elaborate, you can gain valuable insights that drive innovation and customer satisfaction.

Discovery and problem exploration templates for user interviews

Discovery research identifies user problems, workflows, and unmet needs before defining product requirements. These open-ended templates focus on user research questions to explore needs and goals, helping teams gather actionable insights for product development and better user experience. User interview templates and user research questions help structure discovery research and ensure that the user journey and customer research objectives are addressed. User interview templates can save time for researchers by providing a solid foundation for crafting practical questions.

Current workflow and process templates

“Walk me through your current process for [specific task].” Captures steps, tools, decisions, time, and frustrations to identify improvement areas.

Slack asks: “Walk me through how your team shares project updates.” Users describe communication methods and pain points.

“Describe a typical day managing [responsibility].” Reveals routines and challenges using insights from qualitative research techniques.

Notion asks: “Describe a typical day managing your personal projects.” Users share usage patterns For those seeking to enhance their project outcomes, learning more about market understanding and research methods can provide valuable insights.

“Tell me about the last time you needed to [specific goal].” Grounds discussions in real experiences.

Calendly asks: “Tell me about the last time you scheduled a meeting outside your organization.” Users describe coordination challenges.

“How do you currently solve [problem your product addresses]?” Reveals competing solutions and highlights the importance of choosing the right UX research methods to better understand user needs.

Airtable asks: “How do you track projects and collaborate?” Users describe tools and expectations for digital product managers, and many businesses also benefit from using marketing analysis frameworks to guide their strategic decisions.

“What tools do you use for [task], and how do they work together?” Uncovers integration needs.

Zapier asks: “What tools manage customer data, and how do they integrate?” Users reveal manual processes and gaps.

Listen carefully to participants’ responses to uncover authentic insights and build trust for richer qualitative data. Gathering feedback—especially specific feedback—during these interviews is essential for informing customer research and understanding the user journey.

Pain point and challenge templates

“Describe the biggest challenge you face when trying to [goal].” Surfaces critical problems and impacts.

Linear asks: “Describe the biggest challenge managing engineering work.” Users reveal priorities.

“What frustrates you most about [tool]?” Uncovers emotional pain points.

Superhuman asks: “What frustrates you most about email?” Users describe overload.

“Tell me about a time when [solution] let you down.” Reveals reliability issues. Evaluative research is designed to uncover such problems by assessing solutions in real-world scenarios.

Miro asks: “Tell me about a time remote collaboration tools failed your team.” Users share difficulties.

“What takes longer than it should in your workflow?” Identifies inefficiencies.

Webflow asks: “What takes longer than it should when building websites?” Users reveal bottlenecks.

“Describe a recent situation where you couldn’t accomplish what you needed.” Highlights unmet needs.

Figma asks: “Describe a recent situation where Figma couldn’t meet your needs.” Users reveal limitations.

User research experience and perception templates

Experience research explores user emotions, satisfaction, and frustrations with products. These templates uncover emotional responses and perception patterns.

Product experience templates

“Describe your first impression when you started using [product].” Captures initial reactions, expectation matches or mismatches, and early adoption barriers. Capturing initial impressions is crucial for understanding how customers perceive the product and identifying factors that influence their early experiences.

Notion researchers ask this to understand feelings like “powerful but overwhelming” or “beautifully designed but confusing.” Collecting feedback and especially detailed feedback on these user experiences helps teams understand emotional responses and perception patterns, which can guide product improvements.

“What words would you use to describe [product]?” Reveals emotional associations, perceived positioning, and communication gaps.

Superhuman users describe their email app as “fast,” “keyboard-focused,” or “intimidating,” highlighting brand perception.

“Tell me about a time when [product] exceeded your expectations.” Identifies delight factors and unexpected benefits.

Slack users share moments like discovering integrations that solved problems, guiding onboarding and marketing.

“Walk me through a recent experience using [product] that frustrated you.” Highlights usability issues and missing features.

Zoom users report audio or screen-sharing problems, informing improvements.

“How has [product] changed how you work?” Measures workflow impact and value realization.

Airtable users describe replacing spreadsheets and improving collaboration, ultimately contributing to improved customer satisfaction.

Understanding expectation matches or mismatches helps identify gaps and improve customer experience.

When conducting user interviews, keep in mind that cultural differences can impact how users express their perceptions and experiences. Consider these differences when comparing data across regions to ensure more accurate and unbiased insights.

Comparative perception templates

“How does [product] compare to [alternative] you’ve used?” Reveals competitive positioning and feature priorities.

Linear users compare to Jira noting “faster,” “cleaner interface,” and missing customization.

“What would you lose if [product] disappeared tomorrow?” Tests product dependency and unique value.

Figma users cite collaboration challenges without the product.

“Describe the difference between [your product] and how you worked before.” Shows workflow improvements and value created.

Calendly users highlight eliminating scheduling conflicts.

“What surprised you most about using [product]?” Uncovers unexpected benefits and perception shifts.

Notion users mention powerful databases and templates.

“Tell me about how others on your team perceive [product].” Reveals adoption barriers and organizational dynamics.

Miro users note complexity and remote team support, guiding segment targeting.

Note: Questions anchored to real, recent experiences yield more reliable data than hypotheticals.

Usability and feature templates

Usability research assesses product ease of use, feature clarity, and task success. User testing uncovers friction and improvement areas by collecting specific user feedback. User interview templates and user interview script templates provide a structured approach to gather feedback, ensuring you capture both specific feedback and detailed feedback on usability and features. These templates help gather insights on usability and feature understanding for ongoing enhancement.

Task and navigation templates

“Walk me through what you’re trying to do right now.” Clarifies goals, reveals task interpretation, and surfaces confusion. Gathering specific feedback and detailed feedback during this step helps identify usability issues and areas for improvement.

Dropbox found users vary between collaboration, distribution, and backup needs, highlighting feature distinctions.

“Describe how you would find [specific feature or information].” Tests navigation and search effectiveness without direct prompts. Gathering specific feedback here uncovers navigation pain points.

Gmail users search settings in various places depending on feature type.

“What do you expect to happen when you [take specific action]?” Reveals mental models and interface clarity gaps. Detailed feedback from users helps clarify where expectations and reality diverge.

Spotify users expect different privacy, sharing, or editing behaviors than provided.

“Tell me what’s confusing or unclear on this screen.” Identifies terminology, layout, or information overload issues. Gathering detailed feedback here pinpoints confusion and guides improvements.

Zoom users report confusion around meeting controls and screen sharing, guiding improvements.

“Describe your thought process as you complete this task.” Captures real-time decisions and hesitation points, revealing usability issues. Specific feedback during this process highlights friction points.

Airbnb users question pricing and cancellation details, indicating friction before abandonment.

Learning and onboarding templates

“Walk me through your first experience using [feature].” Captures discovery, confusion, and first impressions to inform onboarding and leverage insights from customer personas.

Figma users struggle with variants and properties, requiring better education.

“What help or guidance did you need when getting started?” Identifies knowledge gaps and tutorial needs.

Webflow users need support with responsive design and interactions.

“Describe when you felt you understood how to use [product or feature] effectively.” Pinpoints aha moments and learning patterns.

Notion users grasp databases and templates but may struggle without guidance.

“Tell me about mistakes you made when learning [product].” Reveals common pitfalls and recovery needs.

Zapier users note trigger confusion and testing failures requiring clearer messaging.

“How did you figure out how to accomplish [specific task]?” Highlights learning methods like experimentation and peer support.

Slack users mainly learn through trial and colleague observation, suggesting in-app guidance.

Feature validation and prioritization templates for user interviews

Feature validation research tests concepts, prioritizes development, and validates market fit before engineering investment. These templates assess feature value, adoption likelihood, and competitive necessity. Responses to these open ended qualitative questions provide valuable data for product decisions, as they help collect qualitative data that informs deeper understanding of user needs. Gathering data and feedback from user interviews enables teams to draw meaningful conclusions about feature priorities and customer needs, ensuring product development aligns with real user expectations.

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.

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.

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.

After collecting responses, teams can use them to inform feature priorities and product direction. Applying qualitative analysis to these qualitative data sets helps extract themes and actionable insights, ensuring that teams gain valuable insights into user needs and feature priorities. Additionally, understanding user needs and improving customer experience through user interviews can lead to increased customer loyalty, fostering long-term relationships and trust.

Crafting the right questions and guiding the conversation during user interviews can be daunting, but it is essential for gathering actionable insights that help teams make informed product decisions.

Customer development and buying templates

Customer development research validates market opportunities, understands buying processes, and informs go-to-market strategies. Gathering customer feedback through user interviews helps identify patterns, improve products, and make data-driven decisions to meet customer expectations. Customer research through user interviews also enables businesses to understand how customers perceive their products and what drives customer loyalty, which is essential for building long-term relationships and trust. These templates explore decision-making and competitive dynamics.

Purchase decision templates

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

Superhuman users mention “heard from founders,” “saw Twitter buzz,” “tried waitlist,” and “invited by friend,” highlighting community-driven acquisition.

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

Notion buyers emphasize “flexibility,” “collaboration,” and “ease of use” versus competitors’ complexity.

“Tell me about other products you considered and why you chose this one.” This reveals evaluation criteria and choice drivers.

Linear users cite “speed,” “keyboard shortcuts,” and clean interface as differentiators.

“What almost prevented you from choosing [product]?” This surfaces barriers like price, features, integration, or competitor advantages.

Webflow prospects express concerns about “learning curve,” “scalability,” and “team adoption,” needing support.

“Describe how you justify [product] cost to yourself or stakeholders.” This uncovers value articulation and budget concerns.

Zapier customers report “saved 10 hours weekly,” “enabled workflows,” and “reduced errors,” supporting expansion.

Adoption and impact templates

“Tell me how [product] has changed your work or workflow.” This measures benefits, behavior changes, and value delivery.

Slack users mention “faster decisions,” “reduced email,” and “improved transparency,” confirming value. However, it’s important to recognize that such feedback can sometimes be influenced by types of bias in user research, such as selection or confirmation bias, which researchers should consider.

Understanding customer loyalty and how customers perceive your product is crucial in this stage, as these insights help improve customer satisfaction and retention. By focusing on customer research, businesses can better address the factors that influence loyalty and long-term engagement.

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

Figma designers note “couldn’t collaborate” and “version control chaos,” showing strong product-market fit.

“Describe features you use most and why they matter.” This identifies core value drivers and potential expansion.

Notion power users highlight databases and templates, guiding marketing and development.

“What’s missing that would make [product] indispensable?” This surfaces unmet needs and competitive gaps.

Airtable users request “offline access,” “advanced permissions,” and “enterprise SSO,” showing enterprise progression.

“Tell me about how you would describe [product] to colleagues.” This reveals positioning and referral messaging.

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

Creating an interview script

A well-designed interview script is essential for conducting effective user interviews and gathering meaningful feedback from your target audience. The interview script serves as a roadmap, ensuring that you cover all relevant topics and stay aligned with your research objectives. When creating your script, start by defining what you want to learn—whether it’s understanding user pain points, validating new features, or exploring customer expectations.

Your script should prioritize open-ended questions that encourage detailed responses, allowing participants to share their experiences and perspectives freely. Include thoughtful follow-up questions to probe deeper and clarify responses, helping you gain deeper insights into user needs and behaviors. It’s important to avoid leading or biased language, as this can influence participants and limit the authenticity of their feedback. Instead, use neutral phrasing that invites honest and expansive answers.

By preparing a clear and focused interview script, you can ensure that your user interviews yield valuable feedback, uncover deeper insights, and provide the qualitative data needed to inform your product or service decisions.

Conducting user interviews

The way you conduct user interviews has a significant impact on the quality of insights you gather. During the interview process, it’s crucial to create a welcoming and non-judgmental environment where participants feel comfortable sharing their honest feedback. Use active listening techniques—such as maintaining eye contact, nodding, and giving verbal affirmations—to show genuine interest in the participant’s responses.

Ask open-ended questions and avoid leading questions that might steer participants toward a particular answer. Encourage users to respond in their own words, providing detailed and expansive answers that reveal their true thoughts, feelings, and pain points. Give participants time to think and elaborate, and use follow-up questions to dig deeper into their experiences.

By conducting user interviews with empathy and careful attention, you can gather nuanced data about your target audience. These valuable insights can help you identify customer pain points, improve the customer experience, and inform strategic decisions across your organization.

Analyzing open-ended responses

Once you’ve collected open-ended responses from user interviews, the next step is to analyze the data to uncover meaningful insights. Start by systematically reviewing participants’ responses, looking for common themes, patterns, and trends that relate to your research objectives. Coding and categorizing the data can help you organize open-ended responses and identify recurring ideas or issues.

Careful consideration of the context, tone, and specific language used by participants is essential for drawing meaningful conclusions. Pay attention to both what is said and how it is said, as this can reveal underlying attitudes and motivations. By thoroughly analyzing open-ended responses, you can gain a deeper understanding of your target audience, identify areas for improvement, and develop strategies to meet customer expectations and enhance customer satisfaction.

A rigorous approach to qualitative research analysis ensures that you extract the most valuable insights from your data, enabling you to make informed decisions and drive positive outcomes for your business.

User interview reporting

Reporting on user interviews is a vital step in the qualitative research process, as it translates raw data into actionable insights for your team and stakeholders. A strong user interview report should clearly summarize your research objectives, methodology, and the key findings that emerged from your interviews. Use direct quotes, anecdotes, and real examples from participants to bring your findings to life and make them relatable.

Keep your language simple and avoid jargon, ensuring that your report is accessible to a wide audience. Focus on presenting insights in a way that informs decision-making and drives action—highlighting recommendations for product improvements, customer experience enhancements, or strategic initiatives. By connecting your findings to business goals and customer needs, you demonstrate the value of qualitative research and the impact of user-centered design.

Effective user interview reporting not only communicates what you learned, but also inspires your team to act on those insights, ultimately leading to better products and improved customer experiences.

Common open-ended question mistakes

Even experienced researchers make mistakes reducing question effectiveness and insight quality. Avoid these pitfalls when crafting open-ended questions for user interviews, and remember that well-designed interview questions are essential for gathering authentic insights. Building rapport with participants is crucial for encouraging honest responses and minimizing bias—when participants feel comfortable and trust the interviewer, they are more likely to share genuine feedback. Each question should align with your overall research question to ensure relevance and focus.

Leading questions that bias responses

Leading questions suggest expected answers through language choices, tone, or framing pressuring participants toward particular responses rather than authentic perspectives. To ensure unbiased responses, it’s important to craft questions that encourage honesty and objectivity, allowing participants to share their genuine thoughts.

Poor example: “How much do you love our new feature that makes work so much easier?” This assumes positive sentiment and benefit realization biasing users toward praise.

Better approach: “How has the new feature affected your workflow?” This neutral framing allows both positive and negative experiences without pressure or assumptions.

Compound questions asking multiple things

Compound questions combine several queries confusing participants about which element to address first and typically generating incomplete answers.

Poor 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?” This overwhelming question covers four distinct topics.

Better approach: Ask four separate questions about usage patterns, favorite features, desired improvements, and frequency allowing focused responses to each element.

Hypothetical questions about future behavior

Hypothetical questions ask what users would do in imaginary situations generating unreliable speculation rather than actual behavior patterns.

Poor example: “Would you pay $50/month for premium features?” Users poorly predict future purchasing behavior, social desirability biases responses, and features remain abstract.

Better approach: “Tell me about the last time you paid for software. What made it worth the investment?” This reveals actual purchasing drivers and willingness to pay.

Vague questions lacking specificity

Vague questions use abstract language generating general platitudes rather than concrete, actionable insights rooted in actual experiences.

Poor example: “What do you think about our product?” This invites abstract opinions rather than specific experiences revealing actual usage patterns and problems.

Better approach: “Walk me through the last time you used our product.” This grounds discussion in concrete experience revealing real workflows and friction points.

Yes/no questions closed to elaboration

Questions beginning with “Do you,” “Can you,” “Would you,” or “Have you” are examples of closed-ended questions. These invite brief confirmations rather than rich narratives, limiting insight depth and not encouraging detailed feedback.

Poor example: “Do you find our interface confusing?” This generates a yes/no response without explaining what’s confusing or why it matters.

Better approach: “Describe your experience navigating our interface.” This invites specific examples, context, and explanation revealing usability issues.

Questions assuming facts not established — For more information on conducting surveys and best practices, see

Presumptuous questions assume experiences, opinions, or facts not yet confirmed frustrating participants and generating unreliable responses under pressure.

Poor example: “When did you stop having problems with our product?” This assumes problems existed, have stopped, and users recall timing.

Better approach: “Are you currently experiencing any challenges with our product? If so, describe them.” This doesn’t assume problem existence or history.

Best practices for open-ended questions

Creating effective open-ended qualitative questions requires attention to structure, language, and context, ensuring questions elicit rich, authentic, and actionable user insights. Using an interview script or interview guide helps ensure consistency and thoroughness throughout the research process. A user interview script helps maintain consistency across interviews, enabling comparison of responses and identification of common themes.

Start with open words and phrases

Begin questions with “How,” “Why,” “What,” “Describe,” “Tell me about,” “Walk me through,” or “Explain” naturally inviting expansive responses rather than brief answers.

These question starters create space for storytelling, encourage detail and context, signal interest in user perspective, and generate unexpected insights researchers couldn’t anticipate.

Focus on specific behaviors and experiences

Ground questions in concrete actions, recent events, and real situations rather than abstract opinions or general impressions generating actionable insights.

Ask “Tell me about the last time you used our product” rather than “What’s your opinion of our product?” The specific behavioral focus reveals actual usage patterns.

Use neutral, unbiased language

Avoid words or phrases suggesting desired answers, expected emotions, or researcher opinions maintaining neutrality enabling authentic user perspectives.

Choose “How has feature X affected your workflow?” over “How has feature X improved your workflow?” The neutral version allows both positive and negative impacts.

Ask one clear thing at a time

Single-focus questions generate complete, focused responses while compound questions create confusion and incomplete answers covering multiple topics superficially.

Separate “How do you use our product?” and “What features matter most?” and “What would you change?” rather than combining into overwhelming compound question.

Sequence questions strategically

Progress from broad context to specific details, from easy comfortable topics to more complex or sensitive areas, and from present to past to future building rapport and understanding. A user interview guide can be a valuable tool for planning and conducting interviews, helping you organize and sequence your questions effectively. A well-prepared user interview script boosts the interviewer's confidence and helps them elicit more detailed responses.

Begin with “Describe your current workflow” establishing context before asking “What’s your biggest challenge?” or “How would you solve this problem differently?”

Prepare thoughtful follow-up probes

Plan follow-up user research questions deepening initial responses, including “Can you give me a specific example?”, “Tell me more about that,” “What happened next?”, and “How did you feel?” These techniques should be designed to elicit detailed responses and more detailed responses about the user journey, encouraging participants to share comprehensive stories and experiences.

These probes extract maximum insight value from user responses revealing details, context, emotions, and causal factors behind initial answers.

Test questions before research

Pilot questions with colleagues or friendly users identifying confusing language, leading bias, or unclear intent before conducting formal research sessions. Testing also helps ensure your questions elicit nuanced responses that reveal deeper insights.

Testing reveals whether questions generate expected insight types, surface misunderstandings requiring clarification, and identify improvements enhancing question effectiveness.

Focus on actionable insights

Well-crafted open-ended questions help gather valuable feedback from users, leading to insights that can drive meaningful improvements in your product or service. User interview scripts typically include a clear introduction and conclusion to set the stage and wrap up the interview smoothly.

Frequently asked questions about open-ended questions

How many open-ended questions should I ask in user interviews?
Plan 8-12 primary open-ended questions for 45-60 minute interviews, allowing 4-5 minutes per question including follow-ups for deeper insights.

What’s the difference between open-ended and closed questions?
Open-ended questions invite detailed, expansive responses in the participant’s own words, while closed questions limit answers to fixed options like yes/no or ratings.

Should open-ended questions have right answers?
Open-ended questions seek authentic user perspectives and behaviors, with no right or wrong answers.

Can I combine open-ended and closed questions in interviews?
Yes, combining both types strategically collects quantitative data and explores motivations and experiences.

How do I encourage detailed responses to open-ended questions?
Use follow-up probes, silence after responses, specific examples, positive body language, and build rapport for richer answers.

What if users give short answers to open-ended questions?
Follow up with prompts like “Can you give a specific example?” or “Tell me more about that” to elicit fuller responses.

Ready to act on your research goals?