Opportunity Solution Tree Builder (Lite)
Map outcomes, opportunities, and candidate solutions into a clear OST draft.
Discovery
Use Opportunity Solution Tree Builder (Lite)Free Discovery Tools
Discovery tools help product managers and founders make sharper decisions with less overhead. Instead of rebuilding spreadsheets, prompts, and checklists every week, you can use focused workflows that standardize your process and keep teams aligned. CraftUp's free tools section is designed for real operating cadence: discovery calls, prioritization reviews, roadmap syncs, and execution handoffs. Each tool is built to reduce ambiguity, speed up decisions, and produce outputs you can reuse in docs, standups, and stakeholder updates. Use this category as a practical starting point when you need a repeatable method, not another theory-heavy framework. The goal is to help you move from analysis to clear next actions without adding process bloat.
Tools in this category
JTBD Statement Generator
Translate evidence into an editable JTBD Job Story with provenance, assumptions, contradictions, Four Forces and...
Discovery
Use JTBD Statement GeneratorPersona Generator
Build evidence-backed personas with claim-level evidence, contradictions, unknowns, and traceable Product implications.
Discovery
Use Persona GeneratorInterview Script Generator
Generate a user interview script for product discovery with opening, non-leading core questions, probes, and wrap-up.
Discovery
Use Interview Script GeneratorProblem Statement Generator
Turn research inputs into a clear, decision-ready product problem statement.
Discovery
Use Problem Statement GeneratorExperiment Hypothesis Generator
Turn a product decision into a falsifiable experiment contract with mechanism, threshold and guardrails.
Discovery
Use Experiment Hypothesis GeneratorInsight Clustering Helper (Tagging + Themes)
Cluster interview notes into evidence-backed patterns with provenance, contradictions, and segment splits.
Discovery
Use Insight Clustering Helper (Tagging + Themes)Value Proposition Canvas Helper
Build the canonical Value Proposition Canvas (Customer Profile + Value Map), link pains and gains, check fit, and...
Discovery
Use Value Proposition Canvas HelperLean Canvas Helper
Turn the 9-block Lean Canvas into claims with evidence, an explainable riskiest-assumption queue, and a learning loop.
Discovery
Use Lean Canvas HelperPRD Generator
Build an evidence-safe PRD decision contract with requirement truth states, provenance/source authority, open...
Discovery
Use PRD GeneratorUser Story Generator
Build delivery-sized user stories from confirmed context, expose unknowns, review candidate splits, and hand confirmed behavior into acceptance criteria.
Discovery
Use User Story GeneratorIdeal Customer Profile Builder
Build an evidence-backed ICP hypothesis: compare customer segments, keep unknowns explicit, record disqualifiers...
Discovery
Use Ideal Customer Profile BuilderHow to use these tools
Start with one clear outcome before opening any Discovery tool. Define the decision you need to make in one sentence, then collect only the inputs that materially influence that decision. Teams lose most time when they over-collect context and under-define the decision boundary. Keep your first pass small: one target user, one timeframe, and one measurable objective. After the first run, review the output with one cross-functional partner and stress test assumptions before socializing broadly. Use the output as a draft artifact, not as final truth. The fastest teams treat tool output as a structured first version they can debate, improve, and operationalize. Add qualitative evidence from interviews, support tickets, or sales calls to avoid purely numeric decisions. If the output creates tension, that tension is useful: it highlights where assumptions, constraints, or risk tolerance differ across stakeholders. Document those differences early so roadmap conversations become evidence-led instead of opinion-led. Build a weekly cadence around these tools. In most product teams, decisions degrade when workflows are ad hoc. Use one short session to refresh inputs, rerun the tool, and compare deltas against last week. Keep a changelog of what changed and why, then tie those changes to outcome metrics. Over time, this gives you a lightweight decision log that improves consistency and onboarding for new teammates. Finally, connect tool output to execution artifacts. Turn your final output into acceptance criteria, experiment briefs, or stakeholder updates within 24 hours. If an output does not translate into action, the tool run had low leverage. The practical rule is simple: every run should produce one reusable artifact and one concrete next step. As your team matures, standardize input definitions so people score and describe work in the same way. Shared definitions reduce debate time and improve comparability across cycles. Keep one short quality checklist near the tool: clear problem statement, measurable outcome, explicit constraints, and next decision owner. This small discipline is usually enough to keep quality high without slowing velocity.