Startup Idea Validation

Systematic validation for testing ideas before building: define hypotheses, collect evidence, score the opportunity, and make a decision you can defend.

Operating Principles (2026)

Prefer decisions over inventories: each dimension ends with GO / CONDITIONAL / PIVOT / NO-GO and a next action.
Separate evidence quality from confidence: weak evidence cannot justify a high score.
Pre-register thresholds and stop rules before running experiments (avoid moving goalposts).
Validate willingness-to-pay and time-to-value early (price is part of the product).
Calibrate thresholds to the target outcome (venture-scale vs cash-flow business) and business model (B2B SaaS, B2C, marketplace, services).
Stay safe and ethical: no misrepresentation, respect ToS, and handle customer data with minimization and retention limits.

Intake Checklist (Ask First)

One-sentence idea + target user + job-to-be-done
Business model: B2B/B2C, SaaS/usage-based/marketplace/services, ACV/ARPU range
Geography, constraints (regulated domain, procurement/security requirements, data access)
Target outcome: venture-scale, profitable small business, or thesis-driven R&D
Current evidence: interviews, pilots, pre-sales, traffic, competitor list, pricing assumptions

Choose the Right Output

| If the user asks… | Produce… | Use… | |---|---|---| | “Validate this idea” / “Is this worth building?” | 9-dimension scorecard + verdict | validation-scorecard.md, go-no-go-decision.md | | “What’s the riskiest assumption?” | RAT + test plan | riskiest-assumption-test.md, validation-experiment-planner.md | | “Test my hypothesis” | Hypothesis canvas + experiment design | hypothesis-canvas.md, hypothesis-testing-guide.md | | “Market size for X” | TAM/SAM/SOM sizing + assumptions table | market-sizing-worksheet.md, market-sizing-patterns.md | | “Can this be profitable / what’s my runway?” | Unit economics + runway + scenarios | financial-modeling-calculator.md | | “Should I build X or Y?” | Comparative scorecard + decision memo | validation-scorecard.md, go-no-go-decision.md |

Workflow

Clarify the target outcome and business model; set default thresholds accordingly.
Identify the RAT (the assumption that kills the business if wrong).
Plan the validation ladder: interviews -> smoke test -> concierge/WoZ -> paid pilot.
Run the cheapest falsifiable test first; pre-register PASS/FAIL thresholds and stop rules.
Score all 9 dimensions using evidence; downgrade scores when evidence is weak.
Produce a decision memo: verdict, why, what would change the decision, and the next smallest reversible step.

9-Dimension Scorecard

| Dimension | Weight | What it measures | |---|---:|---| | Problem severity | 15% | Urgency, cost of inaction, current workarounds | | Market size | 12% | Sufficient demand for the target outcome | | Market timing | 10% | Clear “why now” and tailwinds | | Competitive moat | 12% | Defensibility over time | | Unit economics | 15% | Profit path (incl. payback and margins) | | Founder-market fit | 8% | Access, expertise, and execution capability | | Technical feasibility | 10% | Buildability, dependencies, constraints | | GTM clarity | 10% | ICP, channels, motion, first customers | | Risk profile | 8% | What can kill it and likelihood |

Verdict thresholds (default):

80–100: GO
60–79: CONDITIONAL (validate RAT first)
40–59: PIVOT
<40: NO-GO

Deep scoring rubrics and calibration live in validation-methodology.md.

Evidence Rules

Strong evidence is behavioral commitment with cost (time, money, switching, access); weak evidence is opinions and hypotheticals.
Triangulate important claims across at least two sources (especially market sizing and competitor state).
Keep an evidence trail: link + capture month; separate “fact” vs “assumption”.

Validation Ladder (Default)

| Step | Goal | Strong signal | |---|---|---| | Interviews | Validate the problem and context | Repeated pain with real workarounds and spend | | Smoke test | Validate demand | Qualified conversion with price shown | | Concierge/WoZ | Validate workflow value | Users complete the job and return | | Paid pilot | Validate willingness-to-pay | Paid, renewed, or expanded |

AI / Automation Notes (2026)

If the idea depends on AI (agents, copilots, automation), validate these explicitly:

Data rights and access: can you legally and reliably access required data?
Reliability: define success metrics, failure modes, and human fallback; validate on real workflows.
Cost-to-serve: model inference + retrieval + human-in-the-loop costs in assets/financial-modeling-calculator.md.

See hypothesis-testing-guide.md for AI-specific experiment patterns.

Integration Points

Receives From

startup-review-mining - Pain point evidence
startup-trend-prediction - Market timing inputs
startup-competitive-analysis - Competitor landscape

Feeds Into

router-startup - Startup decision routing
product-management - Validated requirements and roadmap inputs
startup-business-models - Monetization and packaging decisions

Resources

| Resource | Purpose | |---|---| | validation-methodology.md | Scoring rubrics and calibration | | hypothesis-testing-guide.md | Experiment design and RAT workflows | | market-sizing-patterns.md | TAM/SAM/SOM methods and pitfalls | | moat-assessment-framework.md | Defensibility analysis |

Templates

| Template | Purpose | |---|---| | validation-scorecard.md | Full 9-dimension scoring | | go-no-go-decision.md | Decision memo format | | hypothesis-canvas.md | Hypothesis definition | | validation-experiment-planner.md | Experiment planning + thresholds | | riskiest-assumption-test.md | RAT identification and test design | | market-sizing-worksheet.md | Sizing worksheet | | financial-modeling-calculator.md | Runway + scenarios + unit economics |

Data

| File | Purpose | |---|---| | sources.json | Curated validation resources |