AARRR Pirate Metrics

• Recite the five AARRR stages and what each measures
• Map product events and metrics onto the framework
• Diagnose a product's weakest stage from its AARRR shape

• It converts 'are we growing?' into five specific questions, each with an owner and a fix.
• It forces teams to look past acquisition — many 'growth' problems are actually activation or retention problems.
• The framework is tool-agnostic and applies to B2B, B2C and marketplace products.
• It gives the team a shared lifecycle language in planning meetings.

Pour users in at the top (acquisition) and they flow through activation, retention and revenue. The business grows fastest when you patch the biggest hole — the framework tells you where that hole is.

• Acquisition: count new visitors/users by channel, with the funnel starting where you can affect it (impression → signup).
• Activation: define the aha moment (e.g. first report created) and measure the share of new users achieving it within a window.
• Retention: measure the share of Day-N users still using the product at Day 1, 7, 30.
• Revenue: measure paying behavior — conversion to paid, MRR/ARR, LTV.
• Referral: measure invitations and their conversion (K-factor = invite rate × invitee conversion).

• A SaaS found activation at 12% while acquisition was healthy — doubling down on onboarding raised activated users more than any ad spend.
• A marketplace measures K-factor weekly; a referral incentive lift in K-factor predicted signup growth a month later.
• A subscription app watches Day-7 retention as its north-star-effective input metric, since churn correlates with the 60-day mark.

• Pick ONE metric per stage so the framework stays readable, with diagnostics underneath.
• Define the activation event with an experiment: test candidate aha moments and pick the one that predicts retention.
• Keep AARRR numbers consistent with cohort dates — reporting them per end-date hides timing effects.
• Pair AARRR with funnel/cohort drill-downs; the framework is a pointer, not the whole story.

• Calling DAU 'acquisition' — acquisition counts new users arriving, not total active count.
• Defining activation as 'signed up', which is really the end of acquisition.
• Ignoring retention because acquisition is growing — the leak just gets bigger.
• Comparing AARRR across un-normalized user bases (all users vs new users).

• If activation is low, drop the aha-moment event into a funnel to find the step users fail at.
• If retention looks flat, segment it by acquisition cohort — recent cohorts may be masking an earlier leak.
• If revenue is low but activation is high, check pricing-page events for confusion paths.
• For referral, track invite clicks separately from completed invites to find the friction.