startup-idea-validation

name	startup-idea-validation
description	Systematic 9-dimension validation machine for testing ideas before building. Covers problem severity, market sizing, timing, competitive moats, unit economics, founder-market fit, technical feasibility, GTM clarity, and risk profile. Makes GO/NO-GO decisions based on evidence, not assumptions.
metadata	{"globs":"**/*.md\n**/validation/**\n**/ideas/**\n**/hypothesis/**\n"}

Startup Idea Validation

Systematic validation machine for testing ideas BEFORE building. Validate hypotheses, score opportunities, and make evidence-based GO/NO-GO decisions.

Modern Best Practices (Dec 2025):

• Run a validation ladder (interviews → smoke test → concierge/MVP → paid pilots) before building.
• Pre-register decision thresholds (avoid “moving goalposts” after seeing data).
• Separate evidence quality (strong/medium/weak) from confidence and excitement.
• Test willingness-to-pay early (pricing pages, pilots, LOIs) and treat time-to-value as a constraint.
• Handle customer/market data with purpose limitation, retention, and access controls.

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When to Use This Skill

Trigger	Action
"Validate this idea"	Run full 9-dimension validation
"Is this worth building?"	Run validation scorecard
"Test my hypothesis"	Run hypothesis canvas
"Market size for X"	Run market sizing
"Should I build X or Y?"	Run comparative validation
"What's the riskiest assumption?"	Run RAT analysis

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Validation Ladder (Dec 2025)

Step	Goal	Strong signal	Weak signal	Output
Customer interviews	Validate problem + context	Repeated pain + real workarounds	Hypothetical enthusiasm	Notes + quotes + JTBD
Smoke test	Validate demand	Clicks/signups with clear intent	Survey-only interest	Landing page metrics
Concierge / Wizard-of-Oz	Validate workflow value	Users complete job and return	One-off curiosity	Learning report
Paid pilot	Validate willingness-to-pay	Paid, renewed, or expanded	“Will pay later”	Pilot results + pricing

Use templates/validation-experiment-planner.md for experiment design and decision thresholds.

9-Dimension Validation Framework

Quick Reference

Dimension	Weight	Key Question	Score Range
Problem Severity	15%	Hair on fire or nice to have?	0-10
Market Size	12%	Big enough to matter?	0-10
Market Timing	10%	Why now?	0-10
Competitive Moat	12%	Defensible advantage?	0-10
Unit Economics	15%	Can this be profitable?	0-10
Founder-Market Fit	8%	Right team for this?	0-10
Technical Feasibility	10%	Can we actually build it?	0-10
GTM Clarity	10%	Know how to reach customers?	0-10
Risk Profile	8%	Manageable risk level?	0-10

Verdict Thresholds

Score	Verdict	Action
80-100	Strong GO	Proceed to build
60-79	Conditional GO	Validate riskiest assumptions first
40-59	PIVOT	Core hypothesis needs rework
<40	NO-GO	Fundamental issues, don't build

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Dimension Deep Dives

1. Problem Severity (15%)

Question: Is this a "hair on fire" problem or a "nice to have"?

Signal Strength Indicators:

Score	Description	Evidence
9-10	Hair on fire	Customers actively seeking solutions, willing to pay premium
7-8	Significant pain	Multiple workarounds in use, clear cost of problem
5-6	Real but manageable	Occasional complaints, spreadsheet solutions exist
3-4	Nice to have	Would be good but not urgent
1-2	No real pain	Solution looking for a problem

Evidence Sources:

• Review mining (G2, Capterra, Reddit) → startup-review-mining
• Customer interviews (5-10 minimum)
• Support ticket analysis
• Search volume for solutions

2. Market Size (12%)

Question: Is this market big enough to build a venture-scale business?

TAM/SAM/SOM Framework:

Metric	Definition	Minimum Threshold
TAM	Total Addressable Market	$1B+
SAM	Serviceable Addressable Market	$100M+
SOM	Serviceable Obtainable Market (3yr)	$10M+

Sizing Methods:

• Top-down: Industry reports, analyst estimates
• Bottom-up: Customer count × ACV
• Comparable: Similar company revenue extrapolation

3. Market Timing (10%)

Question: Why now? What's changed that makes this possible/necessary?

Timing Signal Matrix:

Signal	Strong	Weak
Technology enabler	Just became viable	Has existed for years
Regulatory change	New opportunity	No change
Behavior shift	COVID/platform shifts changed habits	Status quo
Cost curve	10x cheaper now	Same cost
Competition	Market forming	Saturated

Integration: Use startup-trend-prediction for timing analysis.

4. Competitive Moat (12%)

Question: What will make this defensible over time?

Moat Type Assessment:

Moat Type	Strength	Build Time	Example
Network Effects	Very Strong	18-24mo	Marketplace, social
Switching Costs	Strong	12-18mo	Workflow integration
Data Moats	Medium	6-12mo	Proprietary datasets
Brand	Medium	24mo+	Trust, reputation
Regulatory	Strong	Variable	Licenses, compliance
Technology	Weak	<6mo	Can be copied

5. Unit Economics (15%)

Question: Can this be a profitable business?

Key Metrics:

Metric	Target	Red Flag
LTV:CAC	>3:1	<2:1
Payback Period	<12 months	>24 months
Gross Margin	>70% (SaaS)	<50%
NRR	>100%	<80%

Formula Basics:

LTV = (ARPU × Gross Margin) / Monthly Churn
CAC = Total Sales & Marketing / New Customers

6. Founder-Market Fit (8%)

Question: Are you the right person/team to solve this?

Assessment Criteria:

Factor	Strong	Weak
Domain Expertise	5+ years in space	No experience
Network	Direct access to buyers	Cold outreach only
Insight	Unique perspective	Generic understanding
Passion	Personal connection	Pure opportunity
Ability to Execute	Built similar before	First attempt

7. Technical Feasibility (10%)

Question: Can we actually build this?

Feasibility Matrix:

Factor	Score
Core technology exists	+3
Similar products exist	+2
Team has built similar	+2
<6 month MVP possible	+2
No regulatory blockers	+1

8. GTM Clarity (10%)

Question: Do we know how to reach and convert customers?

GTM Readiness:

Element	Clear	Unclear
ICP definition	Specific persona	"Everyone"
Acquisition channel	Tested, CAC known	Guessing
Sales motion	PLG/Sales/Hybrid decided	TBD
Pricing	Market-validated	Assumed
First 10 customers	Identified	Unknown

9. Risk Profile (8%)

Question: What could kill this and how likely?

Risk Categories:

Risk Type	Example	Mitigation
Market	Demand doesn't materialize	Validate with pre-sales
Technical	Can't build at scale	Prototype early
Execution	Team can't deliver	Start small
Regulatory	Law changes	Legal review
Funding	Can't raise	Bootstrap path
Competition	Incumbent pivots	Speed, niche

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Validation Workflow

START
  │
  ▼
┌─────────────────────────────────────┐
│ 1. PROBLEM VALIDATION               │
│    - Review mining (10+ sources)    │
│    - Customer interviews (5-10)     │
│    - Pain severity scoring          │
└─────────────────────────────────────┘
  │
  ▼
┌─────────────────────────────────────┐
│ 2. MARKET VALIDATION                │
│    - TAM/SAM/SOM calculation        │
│    - Timing analysis (trends)       │
│    - Competitive landscape          │
└─────────────────────────────────────┘
  │
  ▼
┌─────────────────────────────────────┐
│ 3. SOLUTION VALIDATION              │
│    - Technical feasibility          │
│    - Moat assessment                │
│    - Unit economics modeling        │
└─────────────────────────────────────┘
  │
  ▼
┌─────────────────────────────────────┐
│ 4. EXECUTION VALIDATION             │
│    - Founder-market fit             │
│    - GTM clarity                    │
│    - Risk assessment                │
└─────────────────────────────────────┘
  │
  ▼
┌─────────────────────────────────────┐
│ 5. SCORECARD & DECISION             │
│    - 9-dimension scoring            │
│    - GO/NO-GO verdict               │
│    - RAT identification             │
└─────────────────────────────────────┘
  │
  ▼
GO / CONDITIONAL GO / PIVOT / NO-GO

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Navigation

Resources (Deep Dives)

Resource	Purpose
validation-methodology.md	9-dimension scoring system details
hypothesis-testing-guide.md	How to run validation experiments
market-sizing-patterns.md	TAM/SAM/SOM calculation methods
moat-assessment-framework.md	Competitive barrier analysis

Templates (Outputs)

Template	Use For
validation-scorecard.md	Full 9-dimension scoring
hypothesis-canvas.md	Hypothesis testing template
validation-experiment-planner.md	Hypothesis → method → metric → decision
riskiest-assumption-test.md	RAT experiment design
market-sizing-worksheet.md	TAM/SAM/SOM calculation
go-no-go-decision.md	Final decision template

Data

File	Contents
sources.json	Validation resources (YC, a16z, SVPG, etc.)

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Integration Points

Receives From

• startup-review-mining - Pain point evidence
• startup-trend-prediction - Market timing data
• startup-competitive-analysis - Competitor data

Feeds Into

• router-startup - Validation results
• product-management - Validated requirements
• startup-business-models - Monetization decisions

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Quick Start

Minimum Viable Validation

For rapid first-pass validation:

1. Pain Check (15 min)

   • Search G2/Capterra for competitor complaints
   • Search Reddit for problem discussions
   • Score: Is this severe enough to trigger action (not “nice to have”)?

2. Size Check (15 min)

   • How many potential customers?
   • What would they pay?
   • Is the market plausibly large enough for your target outcome? [Inference]

3. Timing Check (10 min)

   • Why now vs 2 years ago?
   • What changed?

4. Competition Check (15 min)

   • Who else is doing this?
   • What's wrong with existing solutions?

If all 4 checks pass: Proceed to full validation scorecard. If any fail: Pivot or abandon.

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Key Principles

Evidence Over Opinion

Every score must have evidence:

• GOOD: "Pain score 8/10: 47 reviews mention this specific complaint (sources linked)"
• BAD: "Pain score 8/10: I think this is a real problem"

Invalidate Fast

Goal is to find reasons NOT to build:

• Cheap to kill ideas, expensive to build
• Seek disconfirming evidence
• Run the riskiest assumption test first

Iterate the Idea, Not Just the Validation

If validation reveals issues:

• Don't just re-score, adjust the idea
• Pivot to stronger position
• Find the version that scores 80+

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Do / Avoid (Dec 2025)

Do

• Validate the riskiest assumption first (RAT), not the easiest to test.
• Use the ladder: interviews → smoke → concierge → paid pilots.
• Treat willingness-to-pay as a primary signal, not an afterthought.
• Write decision thresholds before running experiments.

Avoid

• Survey-only validation and hypothetical questions (“Would you use this?”).
• Sampling bias (friends, one subreddit, one review site) without triangulation.
• Building an MVP as “validation” without falsifiable hypotheses.

What Good Looks Like

• ICP: one narrow segment with a clear job, pain severity, and buying trigger.
• Evidence: 10+ direct conversations in the ICP with repeatable pain patterns (not one-off anecdotes).
• WTP: explicit pricing tests and at least one “paid” signal (deposit, pilot fee, LOI with price).
• Experiments: hypotheses + success metrics + stop rules written before execution.
• Decision: a documented go/no-go with the next smallest reversible step.

Optional: AI / Automation

Use only when explicitly requested and policy-compliant.

• Summarization/clustering: speed up synthesis, but keep raw notes + spot-checks.
• Copy drafting: generate landing page variants; humans verify claims and compliance.