Rebundle
/pirate-metrics
Skill

Pirate Metrics

Mapea tu producto en AARRR (Acquisition, Activation, Retention, Referral, Revenue) y diagnostica el embudo.

SKILL.md
---
name: pirate-metrics
description: Use Dave McClure's AARRR funnel to diagnose where a product is leaking. For each stage (Acquisition, Activation, Retention, Referral, Revenue) define the canonical event, the current rate, the target rate, and the next experiment to run. Output a one-page funnel with the weakest stage flagged.
---

Pirate Metrics (AARRR)

Coined by Dave McClure at 500 Startups. Five stages every product goes through. Most teams obsess over Acquisition and ignore Retention — which is where the real money lives.

When to use this skill

  • New product, no analytics culture yet.
  • Existing product where the team can't agree what's broken.
  • Investor due diligence prep.
  • Quarterly health check.

The five stages

Acquisition

The user lands and shows interest. Canonical event: landed_homepage or signed_up_for_newsletter. Healthy rate: depends on channel. SEO 1-3% click-to-signup; paid 0.5-2%; referral 8-15%.

Activation

The user has their first valuable experience. Canonical event varies — for Slack it's "sent 2000 messages in a team of 3+", for Dropbox "uploaded 1 file from 2 devices". Healthy rate: 30-50% of signups for B2B SaaS, 15-25% for consumer. This is the biggest leak in most products. Optimize here before paying for more traffic.

Retention

The user comes back. Canonical event: weekly or monthly active user, where active = the activation event repeated. Healthy rate: D1 60%+, D7 40%+, D30 25%+ for consumer SaaS. B2B varies but should be flat or rising at month 3+. Retention shape matters more than absolute number. Flat = product market fit. Decaying = leaks.

Referral

The user invites others. Canonical event: invited_a_friend and the friend signed up. Healthy rate: viral coefficient (k-factor) > 0.5 sustained. Most B2B products have k < 0.1; that's fine if Acquisition + Retention are strong.

Revenue

The user pays. Canonical event: first paid charge. Healthy rate: free → paid 2-5% for self-serve B2B; LTV/CAC > 3 sustained.

Process

  1. For each stage, define the canonical event in plain language.
  2. Pull current rate from analytics.
  3. Set a target rate based on benchmark or hypothesis.
  4. Identify the weakest stage — where the multiplicative gap is biggest.
  5. Propose 2-3 experiments to fix the weakest stage. Don't optimize the others until the leak is fixed.

Output format

| Stage         | Event                                | Current | Target | Gap    |
|---------------|--------------------------------------|---------|--------|--------|
| Acquisition   | Visit landing                         | 12,400  | 12,400 | —      |
|               | → Signed up                           | 4.1%    | 6.0%   | -1.9pp |
| Activation    | First report generated within 7d      | 31%     | 50%    | -19pp  |  ← weakest
| Retention     | Active 4+ weeks after activation      | 64%     | 70%    | -6pp   |
| Referral      | Invited 1+ user                       | 8%      | 15%    | -7pp   |
| Revenue       | Free → paid within 30d                | 3.1%    | 4.5%   | -1.4pp |

WEAKEST: Activation. Fix this first.

EXPERIMENTS:
1. Sample data on day 1 (most users have nothing to report on)
2. Onboarding email sequence with 3 sample reports as templates
3. In-app prompt at minute 5 if no report created

Anti-patterns to reject

  • Optimizing Acquisition while Activation is below 25%. (More traffic = more churn.)
  • Counting "MAU" as Activation. Activation is one-time, MAU is Retention.
  • Vanity totals without rates ("we have 50K users"). Rates show health, totals show effort.
  • Skipping Referral because "we're B2B". Referral works in B2B too — it's just called "intros".

Constraints

  • Always show rates, not just totals.
  • Always identify ONE weakest stage. Don't fix three at once.
  • Use placeholders if the user hasn't shared real numbers.