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Diagnoses growth health through AARRR pirate metrics, North Star alignment, API developer adoption funnel analysis, and KPI dashboards. Use when setting up analytics, diagnosing growth bottlenecks, preparing quarterly OKRs, building investor narratives, or when someone asks "how are we growing?"
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Builds brand positioning, messaging, and content strategy through Dunford Positioning, StoryBrand narrative, and distribution-first content architecture. Use when defining positioning, writing brand messaging, planning content strategy, creating editorial calendars, or when someone asks "how should we talk about [YOUR_COMPANY]?"
Manages the full client lifecycle from founder-led sales through partnerships and client success, using structured qualification, provider management, and expansion frameworks. Use when preparing for a sales call, qualifying a deal, managing provider relationships, onboarding a new client, or tracking client health.
Designs and validates business models through Business Model Canvas, positioning analysis, willingness-to-pay research, and unit economics modeling. Use when launching a new product line, entering a new market, redesigning pricing, or when someone asks "how do we make money from X?"
Builds and maintains competitive intelligence through Wardley Mapping, 7 Powers analysis, battlecards, and JTBD competitive mapping. Use when a new competitor emerges, preparing for investor meetings, building sales enablement materials, or quarterly strategy reviews.
Designs go-to-market strategy using Crossing the Chasm sequencing, Racecar growth diagnostics, developer-first PLG playbook, and land-and-expand motions. Use when entering a new market segment, launching a new product, redesigning channel strategy, or when someone asks "how do we get our first [N] clients?"
Builds and maintains financial models including revenue forecasts, burn rate analysis, unit economics, cash flow projections, and scenario planning. Use when updating financial projections, preparing for investor conversations, analyzing pricing changes, running scenario analysis, or when someone asks "how much runway do we have?"
| name | measuring-growth |
| description | Diagnoses growth health through AARRR pirate metrics, North Star alignment, API developer adoption funnel analysis, and KPI dashboards. Use when setting up analytics, diagnosing growth bottlenecks, preparing quarterly OKRs, building investor narratives, or when someone asks "how are we growing?" |
| version | 1.0.0 |
| created | "2026-02-20T00:00:00.000Z" |
| tags | ["growth","analytics","metrics","kpis","aarrr","okrs","developer-funnel"] |
| triggers | ["how are we growing?","set up analytics","growth bottleneck","KPI dashboard","quarterly OKRs","investor metrics","developer adoption","retention analysis","cohort analysis","growth narrative"] |
Diagnose, measure, and accelerate your company's growth engine -- from developer sign-up to production volume, across all funnel stages.
Purpose: Structure the entire growth funnel into five measurable stages.
ACQUISITION --> ACTIVATION --> RETENTION --> REVENUE --> REFERRAL
"They find us" "Aha moment" "They stay" "They pay" "They tell others"
B2B API Platform Interpretation:
| Stage | Definition | Key Question | Primary Metric |
|---|---|---|---|
| Acquisition | Developer discovers your platform (docs, referral, event) | How do devs find us? | New sign-ups / month |
| Activation | Developer makes first successful API call | Did they hit the aha moment? | TTFHW (Time to First Hello World) |
| Retention | Client stays active month-over-month | Are they still transacting? | Monthly Active API Clients |
| Revenue | Client generates meaningful volume | Are they scaling? | Monthly Processed Volume ($) |
| Referral | Client refers another company | Do they advocate? | Referral-sourced pipeline % |
How to run an AARRR diagnostic:
Purpose: One metric that best captures the value your platform delivers to customers.
| Context | North Star Metric | Why |
|---|---|---|
| B2B (primary) | Monthly Processed Volume ($) | Directly measures value flowing through the platform; correlates with revenue, client health, and product breadth |
| B2C (experimental) | Monthly Active Users | Measures end-user engagement with products |
North Star rules:
North Star decomposition for B2B:
Monthly Processed Volume ($)
= # Active API Clients
x Avg Transactions per Client
x Avg Transaction Size
x Product Mix Factor
Purpose: A product-specific growth engine for API-first platforms. Maps the developer journey from discovery to expansion.
DISCOVER --> SIGN UP --> FIRST API CALL --> FIRST TXN --> PRODUCTION --> EXPANSION
| Stage | Definition | Target Conversion | Target Time |
|---|---|---|---|
| Discover | Dev finds your docs, landing page, or referral | -- | -- |
| Sign Up | Creates account, gets API keys | >40% of visitors | <5 min |
| First API Call | Hits sandbox endpoint successfully | >60% of sign-ups | <30 min (TTFHW) |
| First Transaction | Executes a real transaction (testnet or mainnet) | >40% of first-callers | <7 days |
| Production | Goes live with real users and volume | >30% of first-txn | <30 days |
| Expansion | Adds products, increases volume, or upgrades tier | >50% of production | <90 days |
TTFHW (Time to First Hello World) -- a critical developer experience metric:
Developer funnel diagnostics checklist:
Purpose: 10-12 KPIs with definitions, targets, data sources, and owners. Two variants: B2B (primary) and B2C (experimental).
See full templates in Deliverable 2: KPI Dashboard Specification below.
Purpose: Quarterly objectives aligned to growth metrics. This skill provides the metric foundation; the OKR process, scoring, and review cadence live in the "steering-strategy" skill.
How this skill connects to OKRs:
Example OKR using this skill's output:
Objective: Accelerate developer activation
KR1: Reduce median TTFHW from 45 min to <30 min
KR2: Increase sign-up-to-first-API-call conversion from 35% to 55%
KR3: Ship quickstart guides for 3 programming languages (Python, Node, Go)
When to produce: Monthly, or ad-hoc when growth stalls.
# Growth Diagnostic Report -- [Month Year]
## North Star Status
- **Current:** $[X]M monthly processed volume
- **Target:** $[Y]M (from quarterly OKR)
- **Trend:** [Up/Down/Flat] -- [X]% MoM change
- **Assessment:** [On Track / Warning / Off Track]
## AARRR Funnel Analysis
| Stage | Metric | Current | Prior Month | MoM Change | Target | Status |
|-------|--------|---------|-------------|------------|--------|--------|
| Acquisition | New sign-ups | | | | | |
| Activation | TTFHW (median) | | | | <30 min | |
| Activation | Sign-up to first call % | | | | >60% | |
| Retention | Monthly active clients | | | | | |
| Retention | Logo churn rate | | | | <3% | |
| Revenue | Monthly processed volume | | | | | |
| Revenue | NRR | | | | >120% | |
| Referral | Referral-sourced pipeline % | | | | >20% | |
## Developer Funnel Metrics
| Stage | Count | Conversion from Prior | Target Conv. | Gap |
|-------|-------|----------------------|--------------|-----|
| Discover (unique visitors) | | -- | -- | |
| Sign Up | | % | >40% | |
| First API Call | | % | >60% | |
| First Transaction | | % | >40% | |
| Production | | % | >30% | |
| Expansion | | % | >50% | |
## Bottleneck Identification
- **Primary bottleneck:** [Stage] -- [describe the drop-off and evidence]
- **Root cause hypothesis:** [Why is this stage underperforming?]
- **Secondary bottleneck:** [Stage] -- [describe]
## Recommendations
1. [Action] -- Expected impact: [X]% improvement in [metric]
2. [Action] -- Expected impact: [X]% improvement in [metric]
3. [Action] -- Expected impact: [X]% improvement in [metric]
## Provider / Dependency Reliability (affects retention + revenue)
| Provider | Uptime | Avg Latency | Incidents | Status |
|----------|--------|-------------|-----------|--------|
| [Provider A] | | | | |
| [Provider B] | | | | |
| [Provider C] | | | | |
| # | KPI | Definition | Formula / Source | Target (Y1) | Frequency | Owner |
|---|---|---|---|---|---|---|
| 1 | Monthly Processed Volume | Total $ value of transactions processed | Sum of all txn values | [Set based on financial model] | Weekly | CEO |
| 2 | Active API Clients | Clients with >=1 API call in trailing 30 days | Count distinct client_id where last_call < 30d | [Set based on sales targets] | Monthly | CEO |
| 3 | TTFHW | Median time from sign-up to first successful API call | Median(first_200_response_ts - account_created_ts) | <30 min | Weekly | CTO |
| 4 | API Uptime | Percentage of time API returns successful responses | (1 - error_minutes / total_minutes) x 100 | >99.9% | Daily | CTO |
| 5 | NRR (Net Revenue Retention) | Revenue retained + expanded from existing clients | (Starting MRR + expansion - contraction - churn) / Starting MRR | >120% | Monthly | CEO |
| 6 | ARPA (Avg Revenue Per Account) | Average monthly revenue per active client | Total MRR / Active Clients | [Set based on pricing model] | Monthly | CEO |
| 7 | CAC Payback | Months to recover customer acquisition cost | CAC / (ARPA x Gross Margin) | <12 months | Quarterly | CEO |
| 8 | Logo Churn Rate | % of clients lost in period | Churned clients / Starting clients | <3% monthly | Monthly | CPO |
| 9 | Developer Funnel Conversion | Sign-up to production conversion rate | Production clients / Total sign-ups (trailing 90d) | >7% | Monthly | CTO |
| 10 | Product Breadth per Client | Avg number of products used per active client | Sum(products_used) / Active Clients | >2.0 | Monthly | CPO |
| 11 | Provider Uptime (weighted) | Weighted avg uptime across upstream providers [Provider A/B/C] | Weighted by volume share | >99.5% | Daily | CTO |
| 12 | MRR Growth Rate | Month-over-month MRR growth | (MRR_current - MRR_prior) / MRR_prior | >15% MoM | Monthly | CEO |
Only activate this if your company pursues a B2C product (via DIBB bet in "steering-strategy").
| # | KPI | Definition | Target | Frequency |
|---|---|---|---|---|
| 1 | MAU | Monthly Active Users (>=1 session) | TBD | Monthly |
| 2 | DAU/MAU Ratio | Daily stickiness | >20% | Weekly |
| 3 | First Transaction Rate | % of sign-ups who complete first transaction within 7 days | >30% | Weekly |
| 4 | Account Value Growth | Avg account value growth per user per month | Positive | Monthly |
| 5 | Retention D1/D7/D30 | % of users returning after 1, 7, 30 days | D1>40%, D7>25%, D30>15% | Weekly |
| 6 | NPS | Net Promoter Score | >50 | Quarterly |
Rule: Do not blend B2B and B2C dashboards. They serve different business models with different unit economics. If both exist, present them as separate tabs/views.
Source: ICE-scored experiment ideas originate in "shaping-product-strategy" skill. This skill consumes the top items and plans execution sprints.
# Growth Experiment Backlog -- [Quarter]
## Active Sprint ([Date Range])
| Rank | Experiment | Hypothesis | ICE Score | Metric Targeted | Status |
|------|-----------|-----------|-----------|----------------|--------|
| 1 | [Name] | If we [change], then [metric] will [improve by X%] because [reason] | I:_ C:_ E:_ = _ | [KPI #] | [Running/Complete/Killed] |
| 2 | [Name] | If we... | | | |
| 3 | [Name] | If we... | | | |
## Sprint Results
| Experiment | Result | Statistical Significance | Decision | Learning |
|-----------|--------|------------------------|----------|----------|
| | | | Ship / Iterate / Kill | |
## Backlog (Prioritized)
| # | Experiment | ICE | Metric | Notes |
|---|-----------|-----|--------|-------|
| 4 | | | | |
| 5 | | | | |
| ... | | | | |
## Velocity
- Experiments run this quarter: [X]
- Win rate: [X]%
- Avg impact of wins: [X]% improvement
Sprint cadence: Run 3 experiments per 2-week sprint. Review results at sprint end. Top-of-backlog items graduate to next sprint.
Note (Month 3+ addition): When experiment velocity reaches 4+ per sprint, consider adopting Sean Ellis's Growth Machine framework for more structured experiment pipelines with dedicated growth meetings and cross-functional growth squads.
# Retention & Cohort Analysis -- [Period]
## Monthly Cohort Retention Heatmap (B2B)
Cohort = month client went to production. Cell = % of cohort still active.
| Cohort | M0 | M1 | M2 | M3 | M4 | M5 | M6 | M7 | M8 | M9 | M10 | M11 | M12 |
|--------|----|----|----|----|----|----|----|----|----|----|-----|-----|-----|
| [Month 1] | 100% | | | | | | | | | | | | |
| [Month 2] | 100% | | | | | | | | | | | | |
| ... | | | | | | | | | | | | | |
## NRR by Cohort
| Cohort | Starting MRR | Current MRR | NRR | Expansion $ | Contraction $ | Churn $ |
|--------|-------------|-------------|-----|-------------|---------------|---------|
| | | | | | | |
## Segmented Retention Curves
Break retention by:
- **Client tier:** SMB vs. Mid-Market vs. Enterprise
- **Product used:** Single-product vs. multi-product
- **Geography:** [Primary market] vs. [Secondary market] vs. other
- **Acquisition channel:** Referral vs. outbound vs. inbound
## Key Findings
1. [Finding] -- e.g., "Multi-product clients retain 2x better than single-product"
2. [Finding]
3. [Finding]
## Actions
1. [Action to improve retention based on findings]
2. [Action]
Source: Brian Balfour's Four Fits framework. Evaluates whether your growth model is internally consistent.
# Four Fits Assessment -- [Date]
## 1. Market-Product Fit
- **Market:** [Describe your target market]
- **Product:** [Your product / platform]
- **Fit assessment:** Does the product solve a real, urgent, frequent problem?
- **Evidence:** [Customer quotes, pipeline size, competitive wins]
- **Score:** [1-5] -- [Strong Fit / Emerging / Weak / Untested]
## 2. Product-Channel Fit
- **Product:** [Your product and its onboarding model]
- **Channel:** [Primary distribution channels]
- **Fit assessment:** Does the product naturally spread through the chosen channels?
- **Evidence:** [Sign-up sources, referral rate, content engagement]
- **Score:** [1-5]
## 3. Channel-Model Fit
- **Channel:** [Your acquisition channels]
- **Model:** [Revenue model -- transaction fees, subscriptions, etc.]
- **Fit assessment:** Can the channel economically acquire customers at the target LTV:CAC?
- **Evidence:** [CAC by channel, payback period, channel capacity]
- **Score:** [1-5]
## 4. Model-Market Fit
- **Model:** [Business model summary]
- **Market:** [TAM $X, growth rate Y%]
- **Fit assessment:** Does the business model support the market's buying patterns?
- **Evidence:** [Market willingness to pay, contract sizes, procurement cycles]
- **Score:** [1-5]
## Overall Assessment
- **Strongest fit:** [Which one and why]
- **Weakest fit:** [Which one -- this is where growth will stall]
- **Priority action:** [What to fix to strengthen the weakest fit]
When to produce: Before fundraising rounds. Cross-references "raising-capital" skill for deck integration.
# [YOUR_COMPANY] Growth Narrative -- [Date]
## The Headline
[One sentence: "[YOUR_COMPANY] has grown from [X] to [Y] in [Z] months, demonstrating [key insight]."]
## Key Metrics (Benchmarked)
| Metric | Current | 3mo Ago | Top Quartile B2B SaaS/Fintech | Status |
|--------|---------|---------|-------------------------------|--------|
| MRR | | | | |
| MRR Growth (MoM) | | | >20% | |
| NRR | | | >130% | |
| # Active Clients | | | | |
| Monthly Volume | | | | |
| TTFHW | | | <15 min (Stripe benchmark) | |
| Logo Churn | | | <2% monthly | |
| CAC Payback | | | <12 months | |
## Growth Story (3 chapters)
### Chapter 1: Product-Market Fit Signal
[Evidence that your market wants this -- pipeline, LOIs, design partners, pilot conversions]
### Chapter 2: Efficient Growth Engine
[Evidence of repeatable acquisition -- developer funnel metrics, conversion rates,
low-CAC channels, referral momentum]
### Chapter 3: Expansion & Retention
[Evidence of land-and-expand -- NRR, product breadth per client, volume ramps,
multi-product adoption curves]
## The Ask
[How this growth trajectory justifies the raise amount and valuation]
## Benchmarks & Comps
| Company | At Similar Stage | Key Metric | Your Comparison |
|---------|-----------------|------------|-----------------|
| [Comp 1] | | | |
| [Comp 2] | | | |
| [Comp 3] | | | |
| [Comp 4] | | | |
These decisions were resolved during skill creation (from framework synthesis):
| Decision | Resolution | Rationale |
|---|---|---|
| OKRs primary home | "steering-strategy" skill | OKRs are a strategic cadence tool; this skill provides metric baselines that feed OKR target-setting |
| Sean Ellis Growth Machine | Month 3+ addition note | Requires experiment velocity (4+/sprint) that a small early-stage team will not have initially |
| Viral coefficient analysis | Deferred | B2C-only metric; include when/if B2C bet is activated via DIBB |
| Skill | Relationship |
|---|---|
| steering-strategy | OKRs live there; this skill provides metric baselines and growth diagnostics that feed quarterly OKR setting |
| modeling-finances | Unit economics (LTV, CAC, ARPA, NRR) calculated there feed into this skill's KPI dashboard |
| shaping-product-strategy | ICE-scored experiment backlog originates there; this skill consumes top experiments into sprint plans |
| raising-capital | Growth narrative (Deliverable 6) feeds directly into investor updates and pitch deck metrics slide |
Customize this section with your company's specifics before using the skill.
Growth metrics must account for upstream provider reliability. If a critical provider has downtime, your platform's volume drops regardless of client demand. Track provider uptime as a growth input, not just an ops metric.
With a small early-stage team, do not over-instrument. Start with the 12 B2B KPIs above. Add complexity only when you have someone dedicated to analyzing the data.
"Set up our first dashboard" -- Use Deliverable 2. Implement the 12 B2B KPIs. Weekly on KPIs 1-4 (volume, clients, TTFHW, uptime). Monthly on the full dashboard. Skip B2C unless that bet is active.
"Growth is stalling" -- Run Deliverable 1 (Growth Diagnostic). Identify the AARRR bottleneck and developer funnel drop-off. Generate 5-10 hypotheses. ICE-score them (from "shaping-product-strategy"). Load top 3 into Deliverable 3. Run a 2-week sprint.
"Prepare for fundraising" -- Run Deliverables 1 (diagnostic) + 4 (cohorts) + 5 (Four Fits). Compile into Deliverable 6 (Growth Narrative). Hand off to "raising-capital" for deck integration.
"Set quarterly growth OKRs" -- Run Deliverable 1 for bottleneck. Review Deliverable 2 for baselines. Set 3-5 OKRs targeting bottleneck metrics. Hand to "steering-strategy" for OKR process and scoring.