Title, meta description, canonical URL, OG tags, Twitter cards, BreadcrumbList, FAQPage schema, and WebApplication schema are configured for this problem statement generator route.
This tool is for product discovery and design thinking problem statements, not academic research papers. It helps you produce decision-grade, evidence-aware problem statements you can use in discovery, prioritization, and product planning—with no fluff.
Turn research inputs into a clear problem framing: persona-style statement, user needs statement, how-might-we questions, evidence summary, and optional prioritization score. No login required.
No login. Runs in your browser. We do not store your inputs.
No login. Runs in your browser. We do not store your inputs.
Mode
Context type
Scoring (1–5) optional
Fix: Use a specific segment: role, context, or cohort (e.g. 'New workspace admins in teams of 10+').
Fix: Describe the concrete barrier: what exactly blocks them from the goal?
Fix: Add how this affects the user (feelings, outcomes) or a metric (e.g. activation 22% → 30%).
I am The user. I'm trying to accomplish their goal. But face a barrier.
The user needs a way to accomplish their goal because face a barrier.
ProblemScore = Frequency × Severity × Confidence = 3 × 3 × 3 = 27. Use this to compare with other problems; higher score suggests higher priority when evidence supports it.
A strong problem statement has a clear actor (who), a goal they are trying to accomplish, a concrete barrier or obstacle (what blocks them), a root cause hypothesis (why it happens), and impact (how it affects them—qualitative or metric). Avoid solution language; keep the statement in problem space until you validate it with evidence.
Solution leakage means your problem statement names a solution (e.g. app, feature, dashboard, AI, button) instead of describing the problem. The tool flags words like these so you can reframe. Rewrite by focusing on current behavior, the barrier, and the impact—not the product or feature you might build.
Example rewrite: instead of “Users need a better onboarding feature,” use “New users don’t complete setup because they don’t see progress or value in the first session.”
Persona-style (I am / I’m trying to / But / Because) works well for empathy and storytelling in workshops. User needs statement (“X needs a way to Y because Z”) is concise for backlogs and PRDs. HMW questions open ideation without presupposing a solution—use them after the problem is framed so they stay in possibility space. Use all three: persona for alignment, user needs for handoffs, HMW for ideation.
Add at least one evidence item: a quote from an interview, support ticket, or survey plus the source, or a metric with baseline, target, and timebox (e.g. activation 22% → 30% in 8 weeks). Evidence-based mode requires at least one. Paste a quote and tag the source; optional link and metric fields make the evidence summary and prioritization snapshot stronger for stakeholders.
Symptom: Stakeholders push back because the statement sounds like a feature request.
Cause: Solution leakage: the problem is written around an app, feature, or product instead of user behavior and barrier.
Fix: Remove solution words (app, feature, dashboard, AI, button). Reframe as: who, what they're trying to do, what blocks them, why, impact.
Symptom: The statement could apply to anyone; it doesn't guide prioritization.
Cause: Vague actor: segment is generic (e.g. 'users', 'customers') or missing.
Fix: Define a specific segment: role, context, or cohort. Use the quality check to flag vague actors.
Symptom: The obstacle is fuzzy ('it's hard', 'they can't') and doesn't point to root cause.
Cause: Vague obstacle: no concrete description of what actually blocks the user.
Fix: Describe the specific barrier: what step fails, what information is missing, what friction they hit.
Symptom: Team jumps to solutions before validating the problem.
Cause: No explicit guardrails; 'What this is NOT' is missing or ignored.
Fix: Always show the three non-goals and use them in reviews to keep the conversation in problem space.
Symptom: No way to compare this problem to others for roadmap.
Cause: Missing impact: no qualitative impact or metric (baseline/target/timebox).
Fix: Add user impact (feelings, outcomes) or at least one metric. In evidence-based mode, evidence is required.
Symptom: Root cause is missing or only restates the symptom.
Cause: Evidence-based mode requires a root cause hypothesis; often it's left blank or vague.
Fix: State your best hypothesis for why the obstacle exists. Differentiate cause from symptom.
Symptom: HMW questions presuppose a solution or sound like a feature list.
Cause: HMWs were written before the problem was clear or are phrased as solutions.
Fix: Generate HMWs after the problem statement. Keep them open (how might we help…?) and avoid naming features.
Symptom: Exports don't match what other tools or briefs expect.
Cause: CSV or JSON schema isn't used consistently for backlog or PRD intake.
Fix: Use the provided CSV columns and JSON structure so problem statements can be ingested by other workflows.
This tool is for product discovery and design thinking problem statements, not academic research papers. It produces decision-grade, evidence-aware problem framing for discovery, prioritization, and product planning. You can use it for customer problem statements, user needs statements, and how-might-we generation in a product context.
Quick mode is for 60-second framing with minimal fields. Standard mode requires segment, goal, and obstacle and supports optional evidence and scoring. Evidence-based mode requires root cause and at least one evidence item (quote or metric) and forces scoring (frequency, severity, confidence) so you get a ProblemScore for prioritization.
Solution leakage means your problem statement mentions a solution (e.g. app, feature, dashboard, AI, button) instead of staying in problem space. The quality check flags this. Fix it by reframing in terms of current behavior, barrier, and impact—avoid naming features or products until the problem is validated.
Persona-style (I am / I'm trying to / But / Because) is great for empathy and storytelling. User needs statement (X needs a way to Y because Z) is concise for backlogs and PRDs. HMW questions open ideation without presupposing a solution. Use all three: persona for alignment, user needs for handoffs, HMW for workshops.
Add at least one evidence item: a quote (from interview, support, or survey) and source, or a metric with baseline, target, and timebox. Evidence-based mode requires at least one. You can paste a quote and tag the source; optional link and metric fields make the evidence summary and prioritization snapshot stronger.
Yes. Use the Share action to generate a compressed URL that reconstructs inputs and outputs in a new session. Anyone with the link can open it and continue editing. No login required; the snapshot is encoded in the URL so you can paste it in Slack or email.
ProblemScore = Frequency × Severity × Confidence (each 1–5). It appears when you provide scoring (required in evidence-based mode). Use it to compare problems: higher score suggests higher priority when evidence supports it. The prioritization snapshot explains what drives the score.
Copy to clipboard (all outputs), Export Markdown (stakeholder-ready with all sections), Export CSV (columns for backlog or PRD intake: context_type, segment, goal, obstacle, root_cause, user_impact, evidence, metrics, problem_score, problem_statement, user_needs, hmws), and Export JSON (raw inputs plus computed outputs). Use CSV for backlog or PRD intake and Markdown for stakeholder briefs.
Use it after interviews (Interview Script Generator) or with clustered insights (Insight Clustering Helper) to turn evidence into a clear problem statement. Feed the output into JTBD Statement Generator, Opportunity Solution Tree, or prioritization tools like RICE and Kano for a full discovery-to-roadmap flow. Exports and share URL make handoffs easy.
Yes. The tool is free, runs in your browser, and requires no login. You can generate problem statements, load examples, export Markdown/CSV/JSON, and share URLs. Autosave uses local storage; we do not store your data on our servers. Use it as often as you need for discovery and roadmap work.
Courses, blog guides, and glossary entries to deepen your problem framing and discovery skills.
Use CraftUp’s discovery tools and courses to go from problem framing to validation and prioritization.
Last updated: 2026-03-05