AARRR (Pirate Metrics) | Glossaire

AARRR, also known as Pirate Metrics (referencing the 'Arr' pronunciation), is a metrics analysis framework developed by Dave McClure. It structures a digital product's growth funnel into five critical stages, enabling precise identification of improvement opportunities and friction points in the user journey.

Framework Fundamentals

Acquisition: how users discover your product (channels, traffic sources, cost per acquisition)
Activation: first successful experience demonstrating product value (onboarding, aha moments)
Retention: regular user return and sustained engagement (retention rate, cohorts, churn)
Revenue: monetization and customer lifetime value optimization (ARPU, LTV, freemium-premium conversion)
Referral: organic acquisition through user recommendations (virality, NPS, K-coefficient)

Strategic Benefits

Holistic view of user journey enabling identification of critical bottlenecks
Data-driven prioritization of product optimizations based on measurable impact at each stage
Alignment of product, marketing, and growth teams around common metrics
Standardized framework facilitating cross-industry comparison and benchmarking
Early identification of structural problems before they impact overall growth

Practical Application Example

For a B2B SaaS platform, here's how to structure an AARRR dashboard:

aarrr-metrics.ts

interface AARRRMetrics {
  acquisition: {
    weeklyVisitors: number;
    costPerVisit: number;
    topChannels: { channel: string; conversion: number }[];
  };
  activation: {
    signupRate: number;
    onboardingCompletion: number;
    timeToFirstValue: number; // in minutes
    activationCriteria: string; // e.g., "3 projects created"
  };
  retention: {
    day1: number;
    day7: number;
    day30: number;
    monthlyActiveUsers: number;
    churnRate: number;
  };
  revenue: {
    conversionToTrial: number;
    trialToPaid: number;
    averageRevenuePerUser: number;
    lifetimeValue: number;
  };
  referral: {
    npsScore: number;
    viralCoefficient: number;
    invitationsPerUser: number;
    inviteConversionRate: number;
  };
}

// Example dashboard
const currentMetrics: AARRRMetrics = {
  acquisition: {
    weeklyVisitors: 12500,
    costPerVisit: 2.3,
    topChannels: [
      { channel: "Organic Search", conversion: 0.034 },
      { channel: "LinkedIn Ads", conversion: 0.028 },
      { channel: "Content Marketing", conversion: 0.041 }
    ]
  },
  activation: {
    signupRate: 0.042,
    onboardingCompletion: 0.68,
    timeToFirstValue: 18,
    activationCriteria: "First project deployed"
  },
  retention: {
    day1: 0.72,
    day7: 0.45,
    day30: 0.31,
    monthlyActiveUsers: 3420,
    churnRate: 0.05
  },
  revenue: {
    conversionToTrial: 0.42,
    trialToPaid: 0.24,
    averageRevenuePerUser: 89,
    lifetimeValue: 1870
  },
  referral: {
    npsScore: 42,
    viralCoefficient: 0.35,
    invitationsPerUser: 2.1,
    inviteConversionRate: 0.17
  }
};

Operational Implementation

Define critical events for each stage (signup, activation action, retention threshold, payment, referral)
Instrument analytics tracking with appropriate tools (Amplitude, Mixpanel, Segment)
Establish industry benchmarks and set realistic goals per stage
Create dedicated dashboards per team with drill-down by cohort and segment
Set up automatic alerts on significant metric variations
Organize weekly reviews focused on the most problematic stage
Experiment iteratively with A/B tests targeted at each identified bottleneck

Pro Tip

Don't try to optimize all stages simultaneously. Identify your biggest leak in the funnel using the 10% rule: if a stage converts at less than 10% of the previous stage, it's your absolute priority. For example, if 1000 people sign up but only 50 activate (5%), activation should be your obsession before even thinking about acquisition.

Associated Tools and Platforms

Product analytics: Amplitude, Mixpanel, Heap, PostHog for event tracking
Visualization: Metabase, Redash, Looker for custom AARRR dashboards
Attribution: Segment, RudderStack to unify cross-channel data
Experimentation: Optimizely, VWO, GrowthBook to test optimizations
Cohort analysis: Retention.com, Baremetrics to analyze temporal behaviors
Referral: ReferralCandy, Viral Loops to systematize viral growth

Adopting the AARRR framework transforms the growth approach from qualitative intuition to rigorous quantitative discipline. By systematically structuring the measurement and optimization of each stage in the user journey, product teams can multiply their learning velocity and focus limited resources on the highest ROI levers. This method remains particularly relevant for SaaS products, marketplaces, and mobile applications where every conversion point counts.