Retention Cohort Review

Critically test the quality, consistency and readiness of Retention Cohort Review. The objective is to remove ambiguity around relative cohort progress, evidence quality and programme interventions, give the founder a decision-ready output, and make it clear whether the venture should progress, repeat the task with stronger evidence, escalate to expert support, or move into a linked stage.

Bertie or a programme manager assigns Retention Cohort Review when the venture needs a decision-ready output for this group. Typical triggers include group-gate reviews, evidence gaps identified by the co-pilot or founder request.

ICP hypothesis; product/MVP status; customer evidence; pricing assumptions; early traction or pipeline data; existing artefact to review; specific context for relative cohort progress, evidence quality and programme interventions.

1. 1Assemble Retention Cohort Data and Artefactsexpand_more

   Extract, clean and format user usage, subscription renewal and churn data grouped by acquisition timeframes into clear cohort tables. Consolidate supporting qualitative evidence, including exit survey responses, customer success logs and feature adoption records for each distinct cohort. Organise these data points into a centralised repository ready for comparative analysis.

   Objective

   Completing this action establishes a single source of truth for historical customer retention across distinct signup windows. It prevents selective bias during evaluation and ensures the subsequent review rests upon verifiable, complete dataset foundations.

   What's expected

   The founder must present a comprehensive cohort matrix detailing user retention percentages, net revenue retention (NRR) and churn rates over consistent weekly or monthly intervals. This must be accompanied by raw export files, data definition notes and mapped qualitative feedback tied directly to specific cohort identifiers.

   Consultant stress-test · 5 questions

   1. 1.What data sources were integrated to build this cohort matrix, and how did you verify that user identifiers match across usage and billing systems?
   2. 2.How have you accounted for anomalies or one-off marketing spikes when defining the boundaries of these specific cohorts?
   3. 3.What proportion of the logged cohort data relies on manual data entry versus automated telemetry, and what is the error margin?
   4. 4.Why were these specific time intervals selected for cohort grouping, and do they align with your venture's actual sales and onboarding cycles?
   5. 5.How does this dataset distinguish between voluntary customer churn and involuntary churn caused by payment processing failures?

   Open action arrow_forward
2. 2Evaluate Relative Cohort Progress and Interventionsexpand_more
3. 3Test Cohort Metrics Against Venture DNA Criteriaexpand_more
4. 4Uncover Contradictions Missing Evidence and Material Risksexpand_more
5. 5Prioritise Targeted Retention Corrections and Experimentsexpand_more
6. 6Record Formal Governance Verdict and Next Stepsexpand_more

• A data-room asset titled Retention Cohort Review
• A review note with a verdict, evidence gaps, risks, recommended corrections and a clear continue / repeat / escalate decision
• It should update the venture DNA with specific evidence or decisions about relative cohort progress, evidence quality and programme interventions, create a visible milestone in the founder journey, and generate one or more recommended next tasks

A mentor or evaluator can review the output at the group gate. Programme managers can require an advisor checkpoint before Bertie moves the venture forward.

Draft your output and let Bertie review it