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Inspect the customer journey

AARRR

Review acquisition, activation, retention, revenue, and referral with explicit events, cohorts, observation windows, and denominators.

When to use it

Use AARRR to decide which part of a customer journey deserves investigation. This template lists revenue before referral to match the existing worksheet; neither is required to follow the other. The cards organize questions and do not encode customer counts or conversion rates.

What to bring

Counts or observations for a defined cohort, the events behind each measure, the relevant time windows, and known gaps in the data.

What you will have

A shared record of five diagnostic areas and the evidence needed for the next investigation or experiment.

How to use it

  1. Define the cohort and observation windows before entering stage counts.
  2. Specify acquisition and activation events in terms of meaningful customer behavior.
  3. Define repeat-use or return events and ensure the intended retention window is complete.
  4. Record payment and referral separately, including their own windows and attribution rules.
  5. Select a question to investigate; check logs or speak with customers before proposing a causal explanation.

Keep its limits in mind

A lower count does not identify a cause. Revenue and referral can occur independently. Compare rates only when cohort membership, event definitions, and observation windows support the denominator; do not infer a conversion rate from adjacent cards.

Fictional teaching example

Choose an investigation after a first collaboration

Fictional software example. Teams from one signup week are tracked through first use and later collaboration. Payment and referral are recorded separately.

Cohort and measurement rulesTeams from the same signup week. Activation window: 7 days;retention: collaboration in the following month. Payment andreferral windows and overlap need verification.Acquisition200 target teams signed up.Activation60 teams completed their first real collaboration.Retention24 of the activated teams collaborated again in thefollowing month.Revenue12 teams paid. Check revenue and refunds; amounts are notprovided.Referral6 teams brought in traceable new teams. Their overlap withpaying teams is not established.Stage cards do not encode counts, conversion rates, or a required sequence. Revenueand referral are recorded separately.

On a small screen, scroll across the diagram to read it.

Supported comparison: 24 of 60 activated teams is 40%, provided the following-month window is complete. The remaining teams have no recorded return in that window; this does not prove permanent churn.

Unknown relationship: The counts of 12 payers and 6 referrers do not establish a 50% payer-to-referrer conversion rate.

Next step: Investigate continued collaboration after activation. Confirm event tracking and observation completeness, then discuss obstacles with teams that did not return.

Check your work

  • Each count has a defined event and population.
  • Activation and retention windows are explicit and sufficiently observed.
  • The payment and referral groups are not assumed to be nested.
  • Unknown stages stay unknown rather than receiving invented zeros or rates.

Method references

Put the method to work

Use this framework in the English Workspace with early access. Local generation copies clearly labeled fields; you can edit the diagram afterwards.

Open in Workspace

Practice with an example

Compare signup cohorts, activation rates, and observation windows before deciding what to investigate.

When new users stop returning, check activation first →