aarrr-metrics
Über
Diese Fähigkeit unterstützt Entwickler dabei, das Produktwachstum zu messen und zu optimieren, indem sie den AARRR-Rahmen (Pirate Metrics) anwendet. Sie definiert phasespezifische KPIs, analysiert Konversionen im Trichter und bietet Anleitungen zur Priorisierung von Wachstumsexperimenten. Nutzen Sie sie, um Dashboards zu erstellen, Engpässe zu identifizieren und Wachstumsprobleme in Ihrer Anwendung zu diagnostizieren.
Schnellinstallation
Claude Code
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Dokumentation
AARRR Pirate Metrics
Apply Dave McClure's AARRR framework to measure and optimize growth through the five stages: Acquisition, Activation, Retention, Revenue, and Referral.
When to Use This Skill
- Building growth dashboards
- Identifying funnel bottlenecks
- Prioritizing growth experiments
- Reporting to investors
- Diagnosing growth problems
Methodology Foundation
Based on Dave McClure's AARRR framework (500 Startups), providing:
- Stage-specific metrics definition
- Funnel conversion analysis
- Prioritization framework
- Experiment design guidance
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Defines metrics per stage | Specific definitions for your product |
| Identifies bottlenecks | Experiment priorities |
| Suggests experiments | Resource allocation |
| Creates dashboards | Tool selection |
| Benchmarks performance | Acceptable thresholds |
Instructions
Step 1: Define Each Stage
AARRR Stages:
| Stage | Question | Focus |
|---|---|---|
| Acquisition | How do users find you? | Traffic, channels |
| Activation | Do they have a great first experience? | Onboarding, aha moment |
| Retention | Do they come back? | Engagement, habit |
| Revenue | Do they pay? | Conversion, monetization |
| Referral | Do they tell others? | Virality, NPS |
Step 2: Set Stage-Specific Metrics
Metrics Framework:
| Stage | Primary Metric | Supporting Metrics |
|---|---|---|
| Acquisition | CAC, Unique visitors | Channel mix, CTR, CPM |
| Activation | Activation rate | Time to activate, drop-off points |
| Retention | D7/D30 retention | DAU/MAU, churn rate |
| Revenue | LTV, ARPU | Conversion rate, ACV |
| Referral | Viral coefficient | NPS, referral rate |
Step 3: Map Your Funnel
Funnel Template:
Acquisition → Activation → Retention → Revenue → Referral
100% → 30% → 15% → 5% → 1%
Calculate conversion rates between each stage.
Step 4: Identify Bottlenecks
Bottleneck Analysis:
| Drop-off | Diagnosis |
|---|---|
| Acquisition → Activation | Poor onboarding or wrong traffic |
| Activation → Retention | Not finding core value |
| Retention → Revenue | Pricing or value misalignment |
| Revenue → Referral | Not delighting paying users |
Step 5: Prioritize Experiments
ICE Framework:
- Impact: How much will it move the metric?
- Confidence: How sure are we?
- Ease: How easy to implement?
Examples
Example 1: Complete AARRR Dashboard
Input:
Build an AARRR dashboard for a B2B SaaS product.
Monthly visitors: 50,000
Signups: 3,000
Activated users: 900
Paying customers: 150
Referrals generating signups: 45
Output:
## AARRR Dashboard: B2B SaaS
### Funnel Overview
┌──────────────────────────────────────────────────────────────┐ │ AARRR FUNNEL │ ├──────────────────────────────────────────────────────────────┤ │ │ │ ACQUISITION ACTIVATION RETENTION REVENUE REF │ │ 50,000 3,000 900 150 45 │ │ 100% 6% 30% 17% 30% │ │ │ │ ████████████ ████████ ████ ██ █ │ │ │ │ Visitors → Signups → Activated → Paid → Referral │ │ (-94%) (-70%) (-83%) (-70%) │ │ ⚠️ ⚠️ ✅ ⚠️ │ │ │ └──────────────────────────────────────────────────────────────┘
---
### Stage-by-Stage Analysis
#### 1. ACQUISITION
**Metrics:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Monthly visitors | 50,000 | - | Baseline |
| Visitor → Signup | 6% | 2-5% | ✅ Good |
| CAC | $45 | <$50 | ✅ Good |
| Signups | 3,000 | - | - |
**Channel Breakdown:**
| Channel | Visitors | Signups | Conv % | CAC |
|---------|----------|---------|--------|-----|
| Organic | 20,000 | 1,500 | 7.5% | $0 |
| Paid Search | 15,000 | 900 | 6% | $60 |
| Content | 10,000 | 450 | 4.5% | $20 |
| Social | 5,000 | 150 | 3% | $80 |
**Analysis:** Acquisition is healthy. Organic performing best.
Paid social has high CAC—consider reallocating.
---
#### 2. ACTIVATION ⚠️ BOTTLENECK
**Metrics:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Signup → Activated | 30% | 40-60% | ⚠️ Below |
| Time to activate | 3.2 days | <1 day | ⚠️ Slow |
| Activation rate | 900/3,000 | - | - |
**Activation Definition:**
"Activated" = Created first project + invited 1 team member
**Drop-off Analysis:**
| Step | Users | Drop-off |
|------|-------|----------|
| Signup complete | 3,000 | - |
| Email verified | 2,400 | -20% |
| Created project | 1,500 | -38% |
| Invited team | 900 | -40% ⚠️ |
**Primary Bottleneck:** "Invite team member" step losing 40%
**Experiment Ideas:**
| Experiment | Hypothesis | ICE |
|------------|------------|-----|
| Skip team invite in onboarding | Removes friction, activate solo first | 8/8/9 = 8.3 |
| In-app invite prompt (day 2) | Right timing, after value seen | 7/7/8 = 7.3 |
| Email team invite reminder | Low effort, catches drop-offs | 5/6/9 = 6.7 |
---
#### 3. RETENTION
**Metrics:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Week 1 retention | 65% | 60%+ | ✅ Good |
| Month 1 retention | 45% | 40%+ | ✅ Good |
| DAU/MAU ratio | 28% | 20%+ | ✅ Good |
| Churn rate | 5%/month | <5% | ✅ OK |
**Retention Curve:**
Day 1: 100% ████████████████████ Day 7: 65% █████████████ Day 14: 52% ██████████ Day 30: 45% █████████ Day 60: 38% ████████ Day 90: 32% ██████
**Analysis:** Retention is solid. Users who activate tend to stick.
This confirms activation is the primary bottleneck.
---
#### 4. REVENUE
**Metrics:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Activated → Paid | 17% | 5-15% | ✅ Strong |
| Trial → Paid | 17% | 10-25% | ✅ Good |
| ARPU | $89/mo | - | Baseline |
| LTV | $1,068 | - | 12mo × ARPU |
| LTV:CAC | 24:1 | >3:1 | ✅ Excellent |
**Revenue Breakdown:**
| Plan | Customers | % | MRR |
|------|-----------|---|-----|
| Starter ($29) | 60 | 40% | $1,740 |
| Pro ($89) | 75 | 50% | $6,675 |
| Enterprise ($249) | 15 | 10% | $3,735 |
| **Total** | **150** | - | **$12,150** |
**Analysis:** Strong conversion and healthy LTV:CAC.
Not a bottleneck—maintain current approach.
---
#### 5. REFERRAL ⚠️ OPPORTUNITY
**Metrics:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Referral rate | 30% | 20%+ | ✅ Good |
| Viral coefficient | 0.45 | >1 = viral | ⚠️ Below |
| NPS | +32 | >30 | ✅ Good |
| Referral signups | 45 | - | - |
**Calculation:**
- 150 paying customers
- 30% refer (45 referrals)
- Each referral generates 1 signup
- Viral coefficient = 45/150 × (6% activation) = 0.018
- Not organic virality, but healthy referral base
**Experiment Ideas:**
| Experiment | Hypothesis | ICE |
|------------|------------|-----|
| Referral incentive (2-way) | Motivation for both parties | 7/8/7 = 7.3 |
| In-app share prompts | Right moment capture | 6/7/8 = 7.0 |
| Case study program | Social proof + referral | 5/6/6 = 5.7 |
---
### Priority Recommendations
| Priority | Focus | Current | Target | Impact |
|----------|-------|---------|--------|--------|
| 1 | Activation | 30% | 45% | +450 activated/mo |
| 2 | Referral | 30% | 50% | +30 referral signups |
| 3 | Paid channel mix | 6% conv | 8% conv | -$10 CAC |
**90-Day Goal:**
If activation improves 30% → 45%:
- +450 more activated users
- At 17% conversion = +76 new customers
- At $89 ARPU = +$6,800 MRR
---
### Dashboard Template
┌────────────────────────────────────────────────────────────┐ │ AARRR MONTHLY DASHBOARD January 2026 │ ├────────────────────────────────────────────────────────────┤ │ │ │ ACQUISITION ACTIVATION RETENTION │ │ Visitors: 50K Activated: 900 D30: 45% │ │ Signups: 3K Rate: 30% ⚠️ Churn: 5% │ │ CAC: $45 Time: 3.2d DAU/MAU: 28% │ │ │ │ REVENUE REFERRAL OVERALL │ │ Customers: 150 Referrals: 45 MRR: $12.2K │ │ Conv: 17% Rate: 30% LTV:CAC: 24:1 │ │ ARPU: $89 NPS: +32 Health: 🟢 │ │ │ │ BOTTLENECK: Activation (30% vs 45% target) │ │ EXPERIMENT: Skip team invite onboarding │ │ │ └────────────────────────────────────────────────────────────┘
Example 2: Quick Bottleneck Diagnosis
Input:
Diagnose this funnel:
- 100K visitors, 5K signups (5%)
- 4K activated (80%)
- 1K retained at D30 (25%)
- 200 paid (20%)
Output:
## Quick AARRR Diagnosis
### Funnel
| Stage | Users | Conv | Benchmark | Status |
|-------|-------|------|-----------|--------|
| Acquisition | 100K → 5K | 5% | 2-5% | ✅ Good |
| Activation | 5K → 4K | 80% | 40-60% | ✅ Excellent |
| Retention | 4K → 1K | 25% | 40%+ | ❌ Problem |
| Revenue | 1K → 200 | 20% | 5-15% | ✅ Strong |
### Bottleneck: RETENTION
**Problem:** Only 25% retained at D30 (should be 40%+)
**What this means:**
- Great at attracting and activating
- Users try it, find value initially
- But don't form a habit / come back
- Losing 3,000 activated users monthly
**Likely Causes:**
1. Single-use case (solved problem, left)
2. Not enough ongoing value
3. Poor re-engagement
4. Competitor switching
**Recommended Experiments:**
1. User interviews with churned users
2. Email re-engagement sequence
3. Weekly value summary email
4. Add recurring use case
**Impact if fixed:**
If retention → 40%: 1,600 retained → 320 paid
That's +120 customers/month (+60%)
Skill Boundaries
What This Skill Does Well
- Structuring growth metrics
- Identifying funnel bottlenecks
- Prioritizing experiments
- Creating dashboards
What This Skill Cannot Do
- Access your actual data
- Know your specific definitions
- Run experiments
- Guarantee results
Iteration Guide
Follow-up Prompts:
- "Design activation experiments for [problem]"
- "What metrics matter for [stage]?"
- "Create a retention analysis framework"
- "How do we improve [specific conversion]?"
References
- Dave McClure - Pirate Metrics (500 Startups)
- Reforge Growth Series
- Amplitude Product Analytics
- Mixpanel Growth Framework
Related Skills
product-led-growth- PLG motionsgrowth-loops- Sustainable growthstartup-metrics- Investor metrics
Skill Metadata
- Domain: Growth
- Complexity: Intermediate
- Mode: cyborg
- Time to Value: 2-3 hours for full setup
- Prerequisites: Analytics access, metric definitions
GitHub Repository
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