/prd-v03-outcome-definition

name: prd-v03-outcome-definition
description: Define measurable success metrics (KPIs) tied to product type during PRD v0.3 Commercial Model. Triggers on requests to define success metrics, set KPI targets, determine what to measure, establish go/no-go thresholds, or when user asks "how do we measure success?", "what metrics matter?", "what's our target?", "how do we know if this works?", "define KPIs", "success criteria". Consumes Product Type Classification (BR-) from v0.2. Outputs KPI- entries with thresholds, evidence sources, and downstream gate linkages.
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Outcome Definition

Position in HORIZON workflow: v0.2 Product Type Classification → **v0.3 Outcome Definition** → v0.3 Pricing Model Selection

Consumes

This skill requires prior work from v0.2:

• **BR-\* product type entry** (from Product Type Classification) — Classification determines which metrics are relevant
• **CFD-\* entries** (from Problem Framing and Competitive Landscape) — Customer evidence about desired outcomes
• **Market benchmarks and competitor metrics** — Reference data for Tier 1/2 targets

This skill assumes v0.2 classification is complete.

Produces

This skill creates/updates:

• **KPI-\* entries** (outcome definitions) — Measurable success metrics tied to product type
• **BR-\* outcome rules** (optional) — Constraints derived from KPI thresholds (e.g., "Launch blocked if LTV:CAC < 3:1")
• **Success criteria artifact** — Dashboard of leading + lagging indicators that define product-market fit

All KPI entries should include:

• `confidence: 2-3/5` (based on benchmark evidence, not just assumptions)
• Evidence source (competitor benchmarks, CFD validation, industry reports)
• Forward target: "Would move to 4/5 if we observe real customer data"

Example KPI entry with confidence:

KPI-001: Time to First Revenue

Type: Tier 1 (Revenue)
Category: Lagging
Definition: Days from market signal identification to first paying customer
Target: ≤14 days
Confidence: 2/5 (source: GearHeart-methodology + 0-customer-validation)
Evidence: BR-001 (GearHeart standard); No pre-customer validation yet
Next Target: "Would move to 4/5 if actual customer reaches paying status in ≤14 days"
Downstream Gate: v0.5 Red Team — if not hit by Day 21, evaluate pivot

---

KPI-002: Conversion Rate (Trial → Paid)

Type: Tier 2 (Leading Indicator)
Category: Leading
Definition: (Paid customers / Trial signups) × 100, measured over 60-day trial period
Target: ≥15% (benchmark: SaaS median 10-15%)
Confidence: 3/5 (source: SaaS-benchmarks + 1-SMB-validation-conversation)
Evidence: CFD-042 (competitive landscape shows SMB conversion patterns)
Next Target: "Would move to 4/5 if we see actual cohort conversion in our product"
Downstream Gate: v0.7 Build Execution — EPIC complete when KPI-002 validated

Metric Quality Hierarchy

Not all metrics are equal. Use this tier system:

| Tier | Metric Types | Why It Matters | |------|--------------|----------------| | **Tier 1** | Revenue (MRR, first dollar, ACV), Churn (logo, NRR), LTV:CAC | Revenue validates market fit. "First dollar IS the proof." | | **Tier 2** | Conversion rates (trial→paid, lead→customer), Time to Value, Activation | Leading indicators that predict Tier 1 outcomes | | **Tier 3** | Engagement (DAU, sessions), Feature adoption, NPS | "Nice to know" — only track if tied to Tier 1/2 |

**Rule**: Every product needs at least one Tier 1 metric. Tier 3 metrics without Tier 1/2 correlation are vanity metrics.

Product Type × Metric Selection

Metrics must align with product type from v0.2 classification:

| Product Type | Primary Metrics | Anti-Metrics (Avoid) | |--------------|-----------------|----------------------| | **Clone** | Feature parity score, Price delta vs. leader, TTFV vs. leader | Generic engagement (doesn't prove you beat leader) | | **Undercut** | Price per [unit] vs. leader, Niche conversion rate, CAC in target segment | Broad market share (you're niche by design) | | **Unbundle** | Category NPS vs. platform, Vertical retention, Feature depth usage | Platform-level metrics (irrelevant to your slice) | | **Slice** | Marketplace ranking, Install→activate rate, Platform retention lift | TAM metrics (platform owns the market) | | **Wrapper** | Time saved per workflow, API reliability, Integration adoption | Standalone usage (value is in connection) | | **Innovation** | Education→activation conversion, Behavioral change rate, Reference customers | User counts without activation (people try, don't convert) |

Leading vs. Lagging Framework

Every product needs BOTH:

**Leading Indicators** (actionable now, predict outcomes):

• Sequences sent, open rates, trial starts
• Time to first value, activation rate
• Feature adoption in first 7 days

**Lagging Indicators** (confirm strategy worked):

• MRR, churn rate, LTV:CAC
• Net Revenue Retention (NRR)
• Customer count, logo churn

**Pattern**: Track leading weekly, lagging monthly. If leading indicators fail, you can pivot before lagging indicators confirm disaster.

Target-Setting Rules

Targets must be evidence-based, never arbitrary:

**Good targets** (use these approaches):

• Competitor benchmark × safety margin: "SMB churn benchmark 3-5% → use 5%"
• Revenue gates: "First dollar by Day 14" (Signal → $1: 14 days)
• Ratio thresholds: "LTV:CAC ≥ 3:1"
• Time bounds: "TTFV < 5 minutes for self-serve"

**Bad targets** (anti-patterns):

• Round numbers without evidence: "10% improvement"
• Engagement without revenue tie: "1000 DAU"
• Aspirational without baseline: "Best in class retention"

Output Template

Create KPI- entries in this format:

KPI-XXX: [Metric Name]
Type: [Tier 1 | Tier 2 | Tier 3]
Category: [Leading | Lagging]
Definition: [Exact calculation formula]
Target: [Specific threshold with evidence source]
Evidence: [CFD-XXX or benchmark source]
Downstream Gate: [Which decision uses t