What makes a good research question: evaluation guide for product teams

Research is a systematic and structured process designed to generate new knowledge or validate existing understanding. In the context of UX research and product development, this process begins with formulating clear research questions that guide every subsequent step, from data collection to analysis and interpretation. The ultimate goal is to uncover actionable insights about user behavior, preferences, and pain points, ensuring that product decisions are grounded in real user needs.

A well-defined research process helps teams focus their efforts, avoid wasted resources, and produce findings that are both relevant and feasible to act upon. One widely used framework for evaluating the quality of research questions is the FINER criteria: questions should be Feasible, Interesting, Novel, Ethical, and Relevant. Applying these criteria ensures that research questions are not only answerable within the available resources and timeframe, but also contribute meaningful knowledge to the team and organization. By starting with strong research questions, product teams can maximize the value of their UX research and drive continuous product improvement.

Types of research questions

Research questions come in several forms, each serving a different purpose within the research process. The three main types are exploratory, descriptive, and causal questions:

• Exploratory research questions are used when little is known about a topic. They help teams explore new areas, uncover variables, and identify potential pain points or opportunities. For example, “What challenges do users face when onboarding to our platform?” is an exploratory question that can reveal unexpected user needs.

• Descriptive research questions aim to detail the characteristics or behaviors of a user group or phenomenon. These questions might ask, “How do users interact with our dashboard on mobile devices?” or “What are the most common pain points reported during user interviews?” Descriptive questions help teams understand the current state of user experience.

• Causal research questions investigate relationships between variables, such as, “Does simplifying the checkout process reduce cart abandonment rates?” These questions are often tested through experiments or A/B testing to determine cause and effect.

In UX research, the type of research question you choose will influence your research design, methods, and analysis. For instance, qualitative research questions are ideal for exploring how users perceive a new feature or why certain pain points exist, while quantitative questions are better suited for testing hypotheses or measuring the impact of design changes. Selecting the right type of research question ensures your study is focused, actionable, and aligned with your research goals.

User insights and pain points

Gaining deep user insights and identifying pain points are at the heart of effective UX research. User insights are the valuable understandings you gain about user needs, motivations, and behaviors—often uncovered through methods like user interviews, usability testing, and surveys. These insights help product teams see beyond surface-level feedback and understand the “why” behind user actions.

Pain points, on the other hand, are the specific problems or frustrations users encounter during their journey with your product. Research questions targeting pain points might include, “What obstacles do users face when completing their first task?” or “Where do users get stuck during the onboarding process?” By mapping the user journey and employing tools such as cognitive walkthroughs, teams can systematically uncover and prioritize these pain points.

Addressing user pain points not only improves product usability but also drives higher satisfaction and adoption. Crafting research questions that focus on user insights and pain points ensures that your research delivers actionable findings, guiding design decisions and product enhancements that truly matter to your users.

Research questions define what teams need to learn, guiding method selection, participant recruitment, data collection, and analysis focus. This article serves as a resource for writing and evaluating research questions, helping researchers create effective and impactful studies. Well-crafted research questions produce focused insights informing specific product decisions. Poorly crafted questions waste resources generating vague findings or answers to questions nobody needed.

When Notion researchers ask “What do users think about our product?” they face vague scope making method selection difficult, analysis unfocused, and findings disconnected from decisions. Asking instead “What prevents new users from successfully creating their first database within the first week?” provides clear focus enabling targeted research revealing specific onboarding barriers informing concrete improvements.

The quality of research questions determines research effectiveness regardless of budget, sample size, or methodology sophistication. Strong questions with modest execution typically outperform weak questions with excellent execution because focus and relevance matter more than research polish. Product teams recognizing this truth invest significant effort crafting and refining questions before launching research. Many researchers start with a question that is either too narrow or too broad, and this article provides guidance on refining them.

Good research questions share five fundamental characteristics: clarity enabling shared understanding, appropriate scope balancing breadth and depth, actionability connecting to product decisions, answerability through feasible methods, and alignment with team capacity and timeline. According to the FINER criteria, a good research question should be Feasible (can be answered with available resources), Interesting (significant to the researcher and the wider community), Novel (fills an existing gap in knowledge), Ethical (ensures safety and confidentiality for participants), and Relevant (addresses important issues and increases the likelihood of discussion and recognition within the scientific community). Evaluating questions against these characteristics before research prevents common mistakes and ensures investigation addresses actual information needs. Writing research questions that are novel and fill an existing gap in knowledge is essential for contributing new information to the field.

This guide provides a comprehensive evaluation framework including clarity assessment checking for precision and shared understanding, scope evaluation ensuring appropriate focus, actionability verification connecting findings to decisions, answerability testing examining method feasibility, and practical application guidance showing framework usage with real product research examples. Discussion among researchers is important to refine questions and ensure their relevance. A strong research question should engage the broader scientific community, capturing interest for long-term research.

Characteristic 1 of a good research question: clarity and precision

Good research questions demonstrate clarity through precise language, unambiguous meaning, and shared understanding among stakeholders ensuring everyone comprehends what the research will investigate.

What clarity means

Clear questions use specific terminology avoiding vague concepts, define boundaries explicitly showing what’s included and excluded, and communicate intent transparently so stakeholders understand research focus without interpretation gaps. Framing questions thoughtfully is essential to encourage honest answers and avoid introducing bias, ensuring participants feel comfortable sharing genuine insights.

How to evaluate clarity

Test questions by asking five people to explain what the research will explore. If explanations vary significantly, clarity is insufficient. Check whether questions use terms everyone defines identically. Identify words with multiple interpretations requiring definition. When responses are ambiguous, use follow-up questions to clarify intent and gather deeper understanding.

Examples showing clarity differences

Poor clarity: “How can we improve user experience?”
Improved clarity: “What obstacles prevent users from completing project setup within their first session?”

The vague version allows countless interpretations of “improve,” “user experience,” and scope. The clear version specifies exact experience phase (setup), timeframe (first session), and focus (obstacles preventing completion).

Poor clarity: “Why do people abandon our product?”
Improved clarity: “What factors cause trial users to stop using our product within 14 days without converting to paid plans?”

The vague version doesn’t specify which users (trial, paid, all), what abandonment means (permanent, temporary), or relevant timeframe. The clear version defines user segment (trial), abandonment criteria (stop using within 14 days), and conversion context.

Poor clarity: “What features do users want?”
Improved clarity: “Which current workflow pain points could new features address for enterprise teams managing 50+ projects simultaneously?”

The vague version invites wish lists disconnected from real needs. The clear version grounds inquiry in specific user segment (enterprise teams), context (managing 50+ projects), and connection to actual problems (workflow pain points).

Open-ended questions like those above allow participants to expand on their answers and provide more detailed insights, while closed-ended questions limit responses to predefined options and are better suited for quantifying data rather than exploring nuanced experiences. For more on defining and structuring research problems, see this methodology guide.

Practical application tips

Define ambiguous terms before finalizing questions. Specify user segments, timeframes, and contexts explicitly. Test questions with colleagues checking whether everyone understands identically. Whether you're developing surveys or conducting market research, replace vague verbs (improve, enhance, optimize) with precise actions (complete, accomplish, achieve). Avoid leading and closed-ended questions to reduce bias and encourage honest, detailed answers from participants.

Figma researchers initially drafted: “Why don’t teams collaborate effectively?” After stakeholders interpreted this differently (some thought about real-time editing, others about feedback workflows, others about file organization), they refined to: “What prevents design teams from providing and incorporating feedback during design reviews?” This precision aligned team understanding and focused research productively.

Characteristic 2: appropriate scope

Good research questions define appropriate scope balancing breadth enabling comprehensive understanding with depth enabling actionable specificity avoiding both overwhelming complexity and unhelpful narrowness.

What appropriate scope means

Well-scoped questions address important topics comprehensively without attempting to answer everything about everything. Scope appropriateness depends on available resources, timeline constraints, and decision needs with larger questions requiring more resources and longer timelines. Research questions should be aligned with clear research objectives to ensure the inquiry yields valuable and actionable insights.

How to evaluate scope

Estimate participant count and interview duration needed to answer question adequately. If estimate exceeds available resources by 2x or more, scope is too broad. If question seems answerable with 2-3 interviews, scope may be too narrow missing important context. Check whether question contains multiple sub-questions each deserving separate investigation. Using frameworks like the PICO framework can help define scope by ensuring all relevant components—Patient/population, Intervention, Comparison, and Outcome—are addressed. The ECLIPSE framework (Expectation, Client group, Location, Impact, Professionals, Service) is also useful, especially for evaluating policies or services, and emphasizes the importance of clearly defining the client group. For qualitative and mixed-methods research, the SPIDER framework is helpful for developing primary research questions, while the SPICE framework is valuable for public health researchers evaluating projects, services, or policies. For those interested in user research for product managers: a complete guide, practical methods and insights are available to define, conduct, and leverage user-centered research.

Examples showing scope differences

Too broad: “How do people work?” Too narrow: “Do users prefer blue or green buttons?” Appropriate scope: “How do remote teams coordinate asynchronous project work across time zones?”

The broad version encompasses everything from tools to culture to psychology making focused research impossible. The narrow version addresses trivial detail insufficient for meaningful decisions. The appropriately scoped version focuses on specific challenge (remote coordination), context (asynchronous work, time zones), and user segment (teams) enabling focused valuable research.

Too broad: “What improves productivity?” Too narrow: “How many clicks does saving require?” Appropriate scope: “What workflow interruptions prevent engineers from maintaining focus during feature development?”

The broad version tackles enormous topic requiring years of research. The narrow version focuses on metric without understanding underlying experience. The appropriately scoped version targets specific user segment (engineers), activity (feature development), and phenomenon (workflow interruptions affecting focus).

Practical application tips

Break broad questions into focused sub-questions each manageable within resource constraints. Expand narrow questions adding context about why the detail matters and what larger pattern it reveals. Match scope to decision importance with strategic decisions justifying broader research and tactical decisions requiring narrow focus.

Linear researchers initially asked: “How do teams manage software development?” Recognizing overwhelming scope, they refined to: “How do engineering managers communicate status updates to non-technical stakeholders in weekly cycles?” This scope reduction enabled thorough investigation within 15 interviews informing specific status communication features.

Characteristic 3: actionability and relevance

Good research questions connect directly to product decisions enabling teams to act on findings rather than generating interesting but unusable information.

What actionability means

Actionable questions inform specific decisions teams face whether building features, improving experiences, prioritizing roadmaps, or refining strategies. Research findings from actionable questions directly influence what teams do differently versus confirming what teams already know or revealing information teams can’t act upon. For example, actionable research questions can inform strategies for product adoption by uncovering how users accept and integrate a product into their routines, which is critical for successful product development.

How to evaluate actionability

Ask “What would we do differently if we learned X versus Y?” for potential findings. If answers are “nothing” or “unclear,” question lacks actionability. Check whether stakeholders can articulate how findings will influence decisions. Identify whether question explores topics team controls versus external factors teams cannot influence. A relevant research question is one that has the potential to impact current ideas or practices, making it significant to the healthcare community. Relevance in a research question increases the likelihood of discussion and recognition within the scientific community.

Examples showing actionability differences

Poor actionability: “What do users think about current economic conditions?” Good actionability: “How do budget constraints affect users’ willingness to pay for premium features during economic uncertainty?”

The poor version explores macro economics beyond product control. The good version connects economic context to specific product decision (premium pricing strategy) teams can address.

Poor actionability: “Do users prefer working from home or offices?” Good actionability: “How do remote work patterns affect the collaboration features users need from our product?”

The poor version investigates preferences teams don’t control. The good version explores how work patterns influence product requirements teams can address through features.

Poor actionability: “What makes people happy?” Good actionability: “What product experience moments create satisfaction versus frustration during onboarding?”

The poor version tackles philosophical topic disconnected from product. The good version identifies specific experience moments teams can improve through design changes.

Another example: Poor actionability: “What colors do users like?” Good actionability: “How do user preferences for interface colors influence product adoption and engagement rates?”

This actionable version shows how understanding user preferences can lead to product decisions that directly impact adoption and user satisfaction.

Practical application tips

Connect questions to upcoming decisions or roadmap discussions explicitly. Frame questions around factors teams control through product changes. Test actionability by asking stakeholders what they’d do with different potential findings. Avoid curiosity-driven questions lacking decision connection however interesting intellectually.

Calendly researchers considered asking: “What scheduling tools do competitors offer?” Recognizing this competitive analysis doesn’t directly inform product decisions, they reframed to: “What scheduling problems do users solve with workarounds because our product lacks needed capabilities?” This actionable version identifies feature gaps teams can address directly.

Characteristic 4: answerability through methods

Good research questions are answerable through feasible research methods given team capabilities, budget constraints, timeline requirements, and participant accessibility.

What answerability means

Answerable questions match available research methods and resources. Questions requiring methods teams don’t have expertise using, budgets teams can’t afford, or participants teams can’t access should be refined to become feasible within constraints or explicitly resourced appropriately. Involving research participants and using empirical research methods are essential for generating valid and actionable insights.

How to evaluate answerability

Identify specific research methods that could answer the question. Estimate costs, timeline, and participant requirements for those methods. Compare estimates against available resources. If methods required are unavailable, unaffordable, or infeasible within timeline, question needs refinement or resources need adjustment. For questions exploring experiences or perceptions, consider whether a qualitative study is appropriate, as it can provide nuanced insights that quantitative methods may not capture.

Designing clinical research requires careful formulation of research questions to ensure studies are feasible, ethical, and relevant. Clinical research plays a critical role in generating new medical knowledge and informing healthcare practices.

Examples showing answerability differences

Hard to answer: “What will users want in five years?” Answerable alternative: “What unmet needs do users currently address through workarounds suggesting future feature opportunities?”

The hard version requires prediction beyond research capability. The answerable version explores current behaviors revealing needs teams can address now with future potential. Note: Complex research questions require synthesis and analysis, not just a basic factual search, allowing for detailed arguments over longer works.

Hard to answer: “Why do 10 million users choose our product?” Answerable alternative: “What factors influence product choice decisions among users who recently evaluated alternatives?”

The hard version requires massive scale beyond typical research budgets. The answerable version focuses on subset (recent choosers) manageable through 15-20 interviews revealing decision factors.

Hard to answer: “What do all users think about everything?” Answerable alternative: “What aspects of the checkout experience create friction for first-time purchasers?”

The hard version lacks focus making comprehensive answer impossible. The answerable version targets specific experience (checkout), user segment (first-time), and dimension (friction) enabling focused investigation.

Practical application tips

Match question scope to available methods and budget. If qualitative methods are available, frame questions appropriately for interviews or observation. If only analytics exist, craft questions those metrics can address. Validate early whether needed participants are accessible before finalizing questions.

Notion researchers wanted to understand: “How does Notion affect organizational culture?” Recognizing this requires longitudinal ethnography beyond their capability, they refined to: “How do teams adapt their collaboration practices during first 90 days using Notion?” This version remains longitudinal but becomes feasible through diary studies and periodic check-ins within team capacity.

Characteristic 5: strategic alignment

Good research questions align with organizational strategy, product roadmap priorities, and team focus areas ensuring research investment advances strategic objectives versus addressing tangential curiosities.

What strategic alignment means

Strategically aligned questions connect to company goals, product vision, or roadmap priorities helping teams make decisions advancing strategy. Alignment ensures research resources support important objectives rather than interesting digressions. Research questions should also align with areas of interest for both the organization and the broader scientific community, ensuring the topic captures attention and engagement for long-term research.

How to evaluate alignment

Map questions to strategic priorities or roadmap themes. Check whether findings would influence decisions leadership cares about. Verify questions address problems within current focus areas versus completely new directions. Ask stakeholders whether question topics matter to organizational success. User research and well-crafted user research questions can help generate and refine ideas that align with strategic priorities, ensuring research efforts are focused and actionable.

A strong research question should capture interest for long-term research, engaging not only internal stakeholders but also the broader research community.

Examples showing alignment differences

Poor alignment (for B2B SaaS): “What games do users play on mobile?” Good alignment: “What collaboration patterns distinguish high-performing teams using our platform?”

The poor version explores unrelated topic for B2B productivity tool. The good version investigates usage patterns directly relevant to product value and expansion opportunities.

Poor alignment (for project management tool): “What do users think about cryptocurrency?” Good alignment: “How do project managers track and communicate status to executives?”

The poor version investigates irrelevant topic, potentially falling victim to bias in user research. The good version explores workflow directly related to product use case and feature opportunities.

Practical application tips

Review questions against company OKRs and product roadmap priorities. Eliminate questions unrelated to strategic focus however personally interesting. Prioritize questions informing decisions leadership cares about. Frame even exploratory research connecting to strategic themes.

Slack researchers considered investigating: “How do people make friends at work?” While interesting, this didn’t align with product strategy focused on team productivity. Reframed to: “How do team communication patterns affect project delivery speed and quality?” aligning with productivity strategy while maintaining social dynamics exploration.

Usability testing and research questions

Usability testing is a cornerstone of UX research, providing direct evidence of how users interact with your product in real-world scenarios. The effectiveness of usability testing hinges on the quality of your research questions, which should be designed to uncover how users approach specific tasks, where they encounter friction, and how intuitive the product feels.

For example, research questions for usability testing might include: “How easily can users locate and use the new reporting feature?” or “What steps cause confusion when users attempt to complete a purchase?” By observing participants as they perform these tasks, teams can identify usability issues and gather honest feedback.

Successful usability testing requires careful planning: selecting representative participants, defining clear tasks, and choosing appropriate methods such as think-aloud protocols or eye-tracking. Well-crafted research questions keep the focus on user behavior and experience, ensuring that the findings directly inform design improvements and product decisions.

Common research question mistakes

Product teams repeatedly make predictable mistakes crafting research questions. Recognizing patterns enables prevention. It is important to avoid questions that are closed-ended or do not allow for follow-up questions, as these limit the depth and quality of insights you can gather.

Mistake 1: asking opinion instead of behavior questions

Teams ask “Do you like our feature?” instead of “How do you use our feature in your workflow?” Opinions are unreliable; behaviors reveal actual usage and value.

Mistake 2: seeking validation instead of learning

Questions like “Don’t you think our solution is great?” seek confirmation rather than discovery. Frame questions enabling genuine learning including negative findings.

Mistake 3: conflating multiple questions

Questions combining multiple topics like “How do users evaluate, purchase, and implement our product?” require separation into focused investigations each answerable independently.

Mistake 4: asking impossible questions

Questions like “What will users want in 10 years?” or “Why do people behave this way?” exceed research capability. Refine to answerable present-focused investigations.

Mistake 5: ignoring resource constraints

Questions requiring 100 interviews when budget allows 10 need scope reduction or resource adjustment. Match ambition to capability.

When designing research, remember that user research questions generally fall into three categories: behavioral, attitudinal, and demographic. Using more examples for each category helps clarify intent and improves research outcomes. Balance closed ended questions for quantitative data with open-ended questions to encourage richer responses, and always allow space for follow up questions to explore motivations and clarify answers for deeper insights.

Evaluation framework checklist

Use this checklist evaluating research questions before launching studies. Writing clear user research questions is essential for gathering reliable insights and improving research outcomes:

Clarity check:☐ Terms are defined precisely
☐ Five colleagues explain question identically
☐ Boundaries are explicit
☐ Ambiguous words are eliminated or defined

Scope check:☐ Answerable within resource constraints
☐ Focused enough for depth
☐ Broad enough for comprehensive understanding
☐ Single coherent topic versus multiple questions

Actionability check:☐ Connects to specific upcoming decision
☐ Findings will change team actions
☐ Addresses factors team can control
☐ Stakeholders articulate how findings matter

Answerability check:☐ Feasible methods exist
☐ Budget accommodates needed approach
☐ Timeline realistic for chosen methods
☐ Participants are accessible

Alignment check:☐ Supports strategic priorities
☐ Relates to roadmap themes
☐ Matters to organizational success
☐ Leadership cares about findings

Questions passing all checks merit research investment. Questions failing multiple checks need refinement before proceeding.

Note: Iterating on user research questions through feedback can improve their clarity and effectiveness.

Best practices for conducting research

To ensure your research delivers meaningful and actionable results, it’s essential to follow best practices throughout the research process. Start by formulating clear, focused research questions that align with your research goals and are feasible to answer within your resources. Use open-ended questions to encourage rich, detailed responses, and avoid leading questions that might bias participants’ answers.

Select market research methods that best fit your questions—combining qualitative and quantitative approaches can provide a more comprehensive view. Ensure your participant recruitment is representative of your target user group, and maintain high ethical standards, including informed consent and data privacy.

Be transparent about your methods, limitations, and findings, and remain open to feedback and iteration. Regularly review your research questions to ensure they remain relevant and aligned with your project objectives. By adhering to these best practices, researchers can generate high-quality data, avoid common pitfalls, and ultimately drive better product design and user experiences.

Practical application process

Follow this process refining research questions before studies:

Step 1: draft initial questions
Write questions capturing information needs without self-editing. Generate 10-15 potential user research questions exploring different angles on the topic. Use following questions to dig deeper into user pain points, decision-making, and areas for product improvement as part of your user research.

Step 2: evaluate against framework
Apply checklist to each question identifying which pass criteria and which need refinement. Eliminate questions failing multiple checks.

Step 3: refine promising questions
For questions showing promise but failing some checks, revise addressing specific weaknesses. Improve clarity, adjust scope, strengthen actionability, ensure answerability, or refine alignment. Refine user research questions based on feedback and ensure they align with your research objectives for more effective user research.

Step 4: prioritize revised questions
Rank refined questions by importance to decisions and strategic alignment. Select top 3-5 for investigation based on available resources.

Step 5: validate with stakeholders
Share refined prioritized questions with stakeholders confirming alignment with needs and decisions. Adjust based on feedback before proceeding.

Step 6: develop sub-questions
For selected questions, develop specific interview questions or research protocols addressing different aspects comprehensively.

This systematic process prevents rushing into research with poorly crafted questions ensuring investigation focuses on questions truly worth answering.

Frequently asked questions

How many research questions should one study address?
Focus on 1-3 primary questions per study to maintain clarity and depth.

Can research questions evolve during studies?
Yes, especially in exploratory research, but keep core questions focused to avoid scope creep.

Should research questions differ for qualitative versus quantitative research?
Yes; qualitative questions explore “how” and “why,” quantitative questions measure “how many” and “how much.”

How do I convince stakeholders that my research question is good?
Show how it meets evaluation criteria and links clearly to decisions stakeholders care about.

What if my question fails multiple criteria?
Refine it step-by-step or reconsider its suitability for current research.

How much time should I spend crafting questions?
Spend about 10-20% of the research timeline on developing and refining questions.

How should I recruit participants for my research?
Select participants matching your target audience using screening criteria to ensure relevant, honest insights.

Ready to act on your research goals?