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<!-- Module: 027 | Title: Unit Economics and Cohort Thinking -->

## PART VI - BUSINESS QUALITY | MODULE 027

# Unit Economics and Cohort Thinking

> Mission. Translate growth into acquisition economics, retention, payback, contribution margin, and lifetime value.

## Decision output

Objective: Translate growth into acquisition economics, retention, payback, contribution margin, and lifetime value. The completed work product must be reproducible from evidence, show the downstream financial or decision effect when material, state the strongest contrary case, and define a dated update rule.

## Explicit operating procedure

1. Define the economic unit first: customer, location, device, seat, transaction, MW, policy, account, route, well, project, or another unit that maps to value creation.

1. Build acquisition/onboarding cost from the resources required to acquire the unit, then calculate contribution or gross profit after directly attributable servicing costs.

1. Measure retention/churn by cohort and age, including contraction, expansion, reactivation, and reacquisition. Avoid mixing mature and immature cohorts in a single average.

1. Calculate CAC payback and LTV using observed cohort cash/gross-profit curves and discounting; do not rely on perpetual 1/churn shortcuts when retention is nonlinear.

1. Segment cohorts by channel, geography, customer size, product, vintage, or other economically meaningful dimension to detect deteriorating new-customer quality.

1. Translate unit economics into a company growth model: number of new units, acquisition capacity/cost, mature contribution, reinvestment needs, and incremental ROIC.

## Required evidence and model bridge

- Primary-source set: KPI history, customer cohorts, pricing evidence, cost structure, capital requirements. Preserve exact document/version, date, period, and source location for every material factual input used in unit economics and cohort thinking.

- For each key concept - cohort definition, CAC, payback, gross retention, net retention, contribution margin - state whether it is a reported fact, analyst calculation, management claim, external estimate, or judgment. Quantitative concepts must retain raw components and units; qualitative concepts must retain the specific evidence and counterevidence.

- Map only economically relevant findings into the model or decision record. Process-control modules such as unit economics and cohort thinking may have no direct valuation line; in that case document the downstream error or governance risk the control prevents.

## Metrics and calculation controls

| Metric / concept | Construction | Required validation |
| --- | --- | --- |
| CAC payback | CAC payback months = customer acquisition cost / monthly gross profit from new customer | CAC payback: Recalculate CAC payback from cited inputs; reconcile definition, period, units, signs, and source version; investigate and document any variance before use. |
| gross retention | GRR = beginning-cohort recurring revenue retained before expansion / beginning-cohort recurring revenue | gross retention: Recalculate gross retention from cited inputs; reconcile definition, period, units, signs, and source version; investigate and document any variance before use. |
| net retention | Recurring revenue from the opening customer cohort after churn, contraction, and expansion divided by that cohort's opening recurring revenue. | net retention: Recalculate independently from cited source data; verify definition, period, units, scope, signs, and any reconciliation to reported financial or operating totals. |
| LTV/CAC with explicit assumptions | LTV should be constructed from cohort gross profit, retention curve, servicing cost, and discounting rather than a perpetual shortcut | LTV/CAC with explicit assumptions: Recalculate LTV/CAC with explicit assumptions from cited inputs; reconcile definition, period, units, signs, and source version; investigate and document any variance before use. |



## Worked application

> Case: new cohorts weaken while mature cohorts hide the deterioration.

- Reconstruct the relevant reported fact from primary evidence before interpreting the case. For unit economics and cohort thinking, show the raw components rather than only the resulting ratio or narrative.

- Build the causal chain through cohort definition, CAC, payback, gross retention, then identify which link is directly observed and which link remains an assumption.

- Calculate CAC payback, gross retention, net retention, LTV/CAC with explicit assumptions from sourced components under the reported/base interpretation and at least one skeptical alternative interpretation.

- Translate the difference between cases into the variable that matters for unit economics and cohort thinking: evidence quality, revenue, operating profit/NOPAT, free cash flow, invested capital, financing/dilution, risk, or valuation. Mark non-applicable links instead of inventing them.

- Expert consistency test: use cohort and survival analysis to find aggregate metrics that are masking deterioration.

- Precommit the specific future filing, KPI, customer/supplier observation, regulator action, or market input that would materially invalidate the unit economics and cohort thinking conclusion.

## Failure tests

- FAIL if cohort definition cannot be defined and reproduced from the source pack.

- FAIL if LTV, CAC, payback, retention, or contribution margin is calculated from mismatched cohorts, periods, or cost definitions, or if acquisition growth hides deteriorating cohorts.

- FAIL if the unit economics and cohort thinking conclusion depends on an unstated assumption, unreconciled definition, or evidence that cannot be traced to its source/version.

- FAIL if evidence materially inconsistent with the unit economics and cohort thinking conclusion is omitted, reclassified, or dismissed without a documented definition, materiality, causal, timing, and source-quality analysis.

## Completion test

A senior reviewer must be able to reproduce the unit economics and cohort thinking conclusion, vary the most sensitive assumption independently, trace the change through the model, understand the strongest opposing case, and identify the next evidence that would force an update. If any link is missing, the module remains open.

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