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:

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