Outcome Definition
Position in HORIZON workflow: v0.2 Product Type Classification → v0.3 Outcome Definition → v0.3 Pricing Model Selection
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 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
- Vanity metrics as primary: "50K users" means nothing if only 500 pay
- Traffic without quality: High volume + low engagement = quality problem
- Arbitrary targets: "10% improvement" without baseline or benchmark
- All lagging, no leading: Can't course-correct if you only see outcomes monthly
- Ignoring product type: Clone metrics ≠ Innovation metrics
- Unmeasurable outcomes: "Better experience" — how do you know?
Downstream Connections
KPI- entries feed into:
| Consumer |
What It Uses |
Example |
| v0.5 Red Team |
Kill thresholds |
"If KPI-001 not hit by Day 21, pivot" |
| v0.7 Build Execution |
EPIC acceptance criteria |
"EPIC complete when KPI-002 validated" |
| v0.9 GTM |
Launch dashboard |
Track KPI-001, KPI-003 post-launch |
| BR- Business Rules |
Derived constraints |
"BR-XXX: No launch if LTV:CAC <3:1" |
Detailed References
- Good/bad examples: See
references/examples.md
- Benchmark sources: See
references/benchmarks.md
- KPI template worksheet: See
assets/kpi.md
1---2name: prd-v03-outcome-definition3description: 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.4---5
6# Outcome Definition
7
8Position in HORIZON workflow: v0.2 Product Type Classification → **v0.3 Outcome Definition** → v0.3 Pricing Model Selection
9
10## Metric Quality Hierarchy
11
12Not all metrics are equal. Use this tier system:
13
14| Tier | Metric Types | Why It Matters |
15|------|--------------|----------------|
16| **Tier 1** | Revenue (MRR, first dollar, ACV), Churn (logo, NRR), LTV:CAC | Revenue validates market fit. "First dollar IS the proof." |
17| **Tier 2** | Conversion rates (trial→paid, lead→customer), Time to Value, Activation | Leading indicators that predict Tier 1 outcomes |
18| **Tier 3** | Engagement (DAU, sessions), Feature adoption, NPS | "Nice to know" — only track if tied to Tier 1/2 |
19
20**Rule**: Every product needs at least one Tier 1 metric. Tier 3 metrics without Tier 1/2 correlation are vanity metrics.
21
22## Product Type × Metric Selection
23
24Metrics must align with product type from v0.2 classification:
25
26| Product Type | Primary Metrics | Anti-Metrics (Avoid) |
27|--------------|-----------------|----------------------|
28| **Clone** | Feature parity score, Price delta vs. leader, TTFV vs. leader | Generic engagement (doesn't prove you beat leader) |
29| **Undercut** | Price per [unit] vs. leader, Niche conversion rate, CAC in target segment | Broad market share (you're niche by design) |
30| **Unbundle** | Category NPS vs. platform, Vertical retention, Feature depth usage | Platform-level metrics (irrelevant to your slice) |
31| **Slice** | Marketplace ranking, Install→activate rate, Platform retention lift | TAM metrics (platform owns the market) |
32| **Wrapper** | Time saved per workflow, API reliability, Integration adoption | Standalone usage (value is in connection) |
33| **Innovation** | Education→activation conversion, Behavioral change rate, Reference customers | User counts without activation (people try, don't convert) |
34
35## Leading vs. Lagging Framework
36
37Every product needs BOTH:
38
39**Leading Indicators** (actionable now, predict outcomes):
40- Sequences sent, open rates, trial starts
41- Time to first value, activation rate
42- Feature adoption in first 7 days
43
44**Lagging Indicators** (confirm strategy worked):
45- MRR, churn rate, LTV:CAC
46- Net Revenue Retention (NRR)
47- Customer count, logo churn
48
49**Pattern**: Track leading weekly, lagging monthly. If leading indicators fail, you can pivot before lagging indicators confirm disaster.
50
51## Target-Setting Rules
52
53Targets must be evidence-based, never arbitrary:
54
55**Good targets** (use these approaches):
56- Competitor benchmark × safety margin: "SMB churn benchmark 3-5% → use 5%"
57- Revenue gates: "First dollar by Day 14" (Signal → $1: 14 days)
58- Ratio thresholds: "LTV:CAC ≥ 3:1"
59- Time bounds: "TTFV < 5 minutes for self-serve"
60
61**Bad targets** (anti-patterns):
62- Round numbers without evidence: "10% improvement"
63- Engagement without revenue tie: "1000 DAU"
64- Aspirational without baseline: "Best in class retention"
65
66## Output Template
67
68Create KPI- entries in this format:
69
70```
71KPI-XXX: [Metric Name]
72Type: [Tier 1 | Tier 2 | Tier 3]
73Category: [Leading | Lagging]
74Definition: [Exact calculation formula]
75Target: [Specific threshold with evidence source]
76Evidence: [CFD-XXX or benchmark source]
77Downstream Gate: [Which decision uses this — e.g., "v0.5 Red Team kill criteria"]
78Measurement: [How/when measured — e.g., "Weekly via Mixpanel"]
79```
80
81**Example KPI- entry:**
82```
83KPI-001: Time to First Revenue
84Type: Tier 1
85Category: Lagging
86Definition: Days from market signal identification to first paying customer
87Target: ≤14 days (GearHeart standard: Signal → $1: 14 days)
88Evidence: BR-001 (GearHeart methodology)
89Downstream Gate: v0.5 Red Team — if not hit by Day 21, evaluate pivot
90Measurement: Manual tracking in PRD changelog
91```
92
93## Anti-Patterns to Avoid
94
951. **Vanity metrics as primary**: "50K users" means nothing if only 500 pay
962. **Traffic without quality**: High volume + low engagement = quality problem
973. **Arbitrary targets**: "10% improvement" without baseline or benchmark
984. **All lagging, no leading**: Can't course-correct if you only see outcomes monthly
995. **Ignoring product type**: Clone metrics ≠ Innovation metrics
1006. **Unmeasurable outcomes**: "Better experience" — how do you know?
101
102## Downstream Connections
103
104KPI- entries feed into:
105
106| Consumer | What It Uses | Example |
107|----------|--------------|---------|
108| **v0.5 Red Team** | Kill thresholds | "If KPI-001 not hit by Day 21, pivot" |
109| **v0.7 Build Execution** | EPIC acceptance criteria | "EPIC complete when KPI-002 validated" |
110| **v0.9 GTM** | Launch dashboard | Track KPI-001, KPI-003 post-launch |
111| **BR- Business Rules** | Derived constraints | "BR-XXX: No launch if LTV:CAC <3:1" |
112
113## Detailed References
114
115- **Good/bad examples**: See `references/examples.md`
116- **Benchmark sources**: See `references/benchmarks.md`
117- **KPI template worksheet**: See `assets/kpi.md`
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