prd-v03-moat-definition

# Moat Definition

Position in HORIZON workflow: v0.2 Competitive Landscape → **v0.3 Moat Definition** → v0.3 Pricing Model Selection

## Consumes

This skill requires prior work from v0.2:

- **Landscape map artifact** (from Competitive Landscape Mapping) — Current behavior documentation, feature matrix, competitor analysis
- **CFD-\* entries** (competitive intelligence, from Competitive Landscape Mapping) — Documented competitors with pricing, features, user feedback
- **BR-\* product type entry** (from Product Type Classification) — Classification constrains which competitors are relevant to analyze

This skill assumes v0.2 analysis is complete with documented competitors.

## Produces

This skill creates/updates:

- **CFD-\* entries** (competitor moat analysis) — Assessment of each competitor's defensibility by moat type
- **BR-\* entries** (targeting rules) — Constraints derived from moat analysis, defining where to compete vs. avoid
- **Moat strength inventory artifact** — Summary of competitor moats with vulnerability signals

All CFD moat analysis entries should include:
- `confidence: 2-3/5` (based on public evidence + user interviews about switching friction)
- Evidence source (pricing pages, reviews, customer interviews)
- Forward target: "Would move to 4/5 if we interview 5+ current/former customers about switching costs"

Example moat analysis entry:
```markdown
CFD-055: Competitor Moat Analysis — Notion

Competitor: Notion
Primary Moat Type: Switching Costs (data lock-in)
Moat Strength Tier: Strong
Confidence: 3/5 (source: public-research + 2-user-interviews)
Date: 2026-02-01

Switching Cost Quantification:
  - Financial: Multi-year contract, no early termination ($0 direct cost)
  - Time/Effort: 20+ hours migration, team retraining
  - Data Migration: Proprietary database format (complex export)
  - Workflow Retraining: Unique templates, team habits
  - Integration Rework: Deep Slack/GitHub dependencies

Total Switching Cost: $3K in labor + 20 hours = Material friction
Moat Verdict: Strong — switching costs >$3K + meaningful time investment

Vulnerability Signal: SMB segment with small teams; they use <20% of feature set (opportunity for simpler tool)
Targeting Decision: Avoid direct competition. Wedge in SMB with simplified, cheaper offering.

Evidence:
  - CFD-042 (landscape): Reviews show enterprise love; SMB complaints focus on cost + complexity
  - CFD-015 (value hypothesis): SMB would save $12,500/year with simpler tool
Next Target: "Would move to 4/5 if we interview 5+ SMB teams about exact switching cost dollars"
```

## Moat Type Taxonomy

Every moat falls into one of six types. Identify primary + secondary moats per competitor:

| Moat Type | Definition | Strong When | Weak When |
|-----------|------------|-------------|-----------|
| **Switching Costs** | Friction to leave (data, workflow, contracts) | Multi-year data, deep integrations | Easy export, monthly contracts |
| **Network Effects** | Value increases with users | Two-sided marketplace, content platform | Single-player tool, linear value |
| **Data/IP** | Proprietary data or algorithms | Unique training data, patents | Commodity ML, public datasets |
| **Brand/Trust** | Recognition, credibility | Regulated industry, high-risk decisions | Low-stakes, undifferentiated |
| **Scale/Cost** | Volume economics | Infrastructure-heavy, marginal cost near zero | Labor-intensive, linear cost |
| **Regulatory** | Compliance barriers | Certifications required, government contracts | No compliance requirements |

**For micro-SaaS**: Switching costs and brand/trust matter most. Network effects and scale rarely apply.

## Moat Strength Tiers

Rate each competitor's defensibility:

| Tier | Criteria | Evidence Signals | Targeting Implication |
|------|----------|------------------|----------------------|
| **Impenetrable** | Multi-layered moat, 10+ years data lock-in | "Would take years to switch" | Avoid direct competition |
| **Strong** | Significant switching friction, 1-2 year contracts | High NPS + low churn despite complaints | Target underserved segments only |
| **Moderate** | Some friction, workarounds exist | Churn 5-10%, export options | Wedge opportunity exists |
| **Weak** | Easy to replace, commodity offering | Monthly plans, high churn, price shopping | Direct competition viable |
| **Eroding** | Former strength declining | New alternatives gaining share | Aggressive targeting |

**Gate rule**: Don't compete where incumbent has Impenetrable or Strong moat unless targeting segment they explicitly ignore.

## Switching Cost Inventory

Quantify ALL switching costs — the sum determines moat strength:

| Cost Type | High Impact | Low Impact | How to Assess |
|-----------|-------------|------------|---------------|
| **Financial** | >6mo contract, early termination fees | Monthly billing, no penalty | Check pricing page terms |
| **Time/Effort** | 40+ hr migration, retraining | <4 hr setup, familiar UX | Trial the competitor |
| **Data Migration** | Proprietary format, no export | Standard export (CSV, API) | Test export function |
| **Workflow Retraining** | Unique methodology, team habits | Standard patterns | Read onboarding docs |
| **Integration Rework** | Deep API dependencies | Standalone tool | Map their integrations |

**Calculation**: Sum hours + dollars. >$5K or >40hr = material switching cost.

## Targeting Decision Framework

Use moat analysis to determine where to compete:

```
Moat Impenetrable/Strong → DON'T COMPETE HERE
                          ↓ unless
                          Target ignored segment (SMB, specific vertical)
                          
Moat Moderate → WEDGE STRATEGY
                ↓ identify
                Entry point that bypasses switching friction
                
Moat Weak/Eroding → DIRECT COMPETITION
                    ↓ execute
                    Feature + price attack on their core
```

### Wedge Opportunity Signals

A wedge exists when:
- Competitor moat doesn't a