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

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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:

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:

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 this — e.g., "v0.5 Red Team kill criteria"]
Measurement: [How/when measured — e.g., "Weekly via Mixpanel"]

Example KPI- entry:

KPI-001: Time to First Revenue
Type: Tier 1
Category: Lagging
Definition: Days from market signal identification to first paying customer
Target: ≤14 days (GearHeart standard: Signal → $1: 14 days)
Evidence: BR-001 (GearHeart methodology)
Downstream Gate: v0.5 Red Team — if not hit by Day 21, evaluate pivot
Measurement: Manual tracking in PRD changelog

Anti-Patterns to Avoid

1. Vanity metrics as primary: "50K users" means nothing if only 500 pay
2. Traffic without quality: High volume + low engagement = quality problem
3. Arbitrary targets: "10% improvement" without baseline or benchmark
4. All lagging, no leading: Can't course-correct if you only see outcomes monthly
5. Ignoring product type: Clone metrics ≠ Innovation metrics
6. Unmeasurable outcomes: "Better experience" — how do you know?

Downstream Connections

KPI- entries feed into:

Detailed References

• Good/bad examples: See references/examples.md
• Benchmark sources: See references/benchmarks.md
• KPI template worksheet: See assets/kpi.md