prd-v03-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:

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 apply to specific segment
• One feature has LOW switching cost (can start there)
• Integration allows coexistence (not replacement)
• Price sensitivity > switching friction

Analysis Workflow

Step 1: Pull Competitor Data

Retrieve CFD- entries from v0.2 Competitive Landscape. For each competitor, you need: pricing, complaints, feature set.

Step 2: Identify Moat Type

For each competitor, determine primary moat type. Use evidence from reviews, pricing structure, integration depth.

Step 3: Rate Moat Strength

Apply tier criteria. Flag if insufficient evidence (Tier 4-5 confidence).

Step 4: Inventory Switching Costs

Complete the 5-category switching cost assessment. Quantify hours + dollars.

Step 5: Identify Vulnerabilities

Where is their moat weakest? Which segments do they ignore? What's eroding?

Step 6: Generate IDs

CFD entries (customer_feedback.md): Template: assets/cfd-moat-analysis.md

CFD-MOT-###: [Competitor] Moat Analysis — [Moat Type], [Strength Tier]

BR entries (BUSINESS_RULES.md): Template: assets/br-targeting.md

BR-TGT-###: [Targeting Rule] — based on [Competitor] moat weakness

Anti-Patterns to Avoid

| Don't | Do Instead | |-------|------------| | "They're big" | Specify which moat type + evidence | | Assume low switching cost | Quantify: hours + dollars | | Only analyze direct competitors | Include Type 4-5 (workarounds, inertia) | | Underestimate integration moat | Map actual dependency depth | | Ignore eroding moats | Track signals: new entrants, complaints | | Target where moat is strong | Find the segment where moat doesn't apply |

Output Requirements

Before advancing to Our Moat Articulation:

• [ ] ≥3 competitors with moat type identified
• [ ] ≥2 competitors with switching costs quantified
• [ ] Moat strength tier assigned (with evidence)
• [ ] Targeting decision per competitor (compete/avoid/wedge)
• [ ] CFD-MOT entries created (≥3)
• [ ] BR-TGT entries created (≥2)

Downstream Connections

| Consumer | What It Needs | Format | |----------|---------------|--------| | v0.3 Our Moat Articulation | Where competitors are weak, what moats work | CFD-MOT entries | | v0.3 Pricing Model | What price points bypass switching friction | BR-TGT entries | | v0.5 Red Team | Risks of competitor response | Moat strength tiers | | v0.9 GTM | Positioning against competitor moats | Targeting rules |

Detailed References

• Good/bad examples: See references/examples.md
• CFD-MOT template: See assets/cfd-moat-analysis.md
• BR-TGT template: See assets/br-targeting.md