Acquisition Cohort Comparison Brief
Compare acquisition groups with aligned entry rules, return outcomes and observation windows while preserving audience-mix and incomplete-follow-up limits.
Read this resource as Markdown
When to use this template
Use this when a founder wants to compare people arriving through different periods or channels. Specify who enters each group, how long they can be observed and what later behavior means.
Choose another approach when: You plan to compare a mature group with yesterday’s signups as if both had equal opportunity, or intend to claim channel causality from self-selected audiences.
Gather these inputs
- A clear acquisition grouping rule and stable unit.
- A relevant later-use or task outcome with validated measurement.
- Entry dates, follow-up availability and known differences in audience or access.
Copy and adapt the template
Edit the text below and copy it into your own document. Edits stay in this browser field and are not submitted or saved by this page.
Worked example
Illustrative example, not a Crany customer result. Replace every example detail with facts you can verify.
Fictional example: a founder wants to compare pilot applicants from a tutorial with people who joined after a community discussion. The tutorial group has had time to receive access, while recent discussion signups are still waiting. The brief aligns the entry and follow-up rules before examining later checklist use. People without access are not counted as failed product users. The founder also records that the tutorial explained the task in detail, so the groups may differ before signup. If the mature groups remain small, the conclusion stays descriptive. No retention percentage is fabricated, and the comparison is not called a controlled test just because both groups appear in the same table.
How to use it
- Define group membership, outcomes and overlap before selecting favorable dates.
- Align follow-up maturity and document product-access and audience differences.
- Report bounded comparisons with uncertainty and the next evidence needed.
Check before using it
- Incomplete follow-up is not recorded as a failed outcome.
- The counting unit and outcome definition match across groups.
- Self-selection and different product exposure remain interpretation limits.
What to measure
Track how much of each cohort has a complete eligible observation window, then compare the stated outcome under a stable definition. Preserve uncertainty from sparse samples and missing data. A descriptive cohort contrast does not by itself justify a causal channel-return claim.
Research and sources
Google explains cohort entry and return criteria and provider-specific device-based limitations. Microsoft discusses trustworthy experiment measurement. This original comparison brief remains descriptive and does not import GA4 behavior into every provider or imply random assignment.
- Google Analytics: Cohort exploration — checked 2026-10-24. Cohort inclusion and return criteria, time granularity and GA4 device-based limits. Provider-specific behavior does not imply cross-device identity completeness.
- Microsoft Research: Patterns of Trustworthy Experimentation, Pre-Experiment Stage — checked 2026-10-24. Clear hypotheses, appropriate measurement, assignment units and data-quality checks before a controlled experiment.
About Crany
Crany is an AI marketing co-founder in development for software founders and vibe coders, designed to strategize, execute approved marketing and improve based on results. This free resource is usable independently of the product. Join the public waitlist.