/prd-v03-moat-definition

name: prd-v03-moat-definition
description: Assess competitor defensibility and define our own moat strategy during PRD v0.3 Commercial Model. Triggers on requests to analyze competitor moats, define our defensibility, assess switching costs, identify vulnerabilities, find wedge opportunities, or when user asks "what's our moat?", "how defensible are they?", "where can we compete?", "switching costs?", "defensibility", "who to target". Consumes Competitive Landscape (v0.2) CFD- entries. Outputs CFD- entries for competitor moats and BR- entries for targeting rules and our defensibility strategy.
context: fork
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - WebSearch
  - WebFetch

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