On bad output, see guides/skill-recovery.md

Business-Plan Unit-Economics Critique

Review a business-plan-shaped draft for one question: do the per-customer economics compound, and at what scale? Plans that survive moat and market scrutiny still fail on the unit math — CAC rising faster than assumed, LTV propped by optimistic churn, contribution margins eaten by costs treated as fixed but aren't, payback periods consuming more working capital than the company can raise, gross-margin trajectories that never reach steady state. Apply five lenses scoped to that question.

Scope (and what's deferred)

Covers unit economics only. Two adjacent dimensions are out of scope, handled by sibling skills:

• Moat-and-distribution critique (moat type, distribution channel, switching cost, network effect, competitive response) — business-plan-critique-moat.
• Market-sizing critique (TAM/SAM/SOM realism, segment definition, addressable customer count) — future business-plan-critique-market-sizing.

If the draft's biggest weakness is in one of those, name it briefly under "Out of scope" in your Goal-Alignment Note and let the orchestrator route it. Do not attempt those critiques here — keeping this skill narrow lands sharp findings without blurring into a generic business review.

Pre-flight: Skip Obvious Stubs

If the draft is under ~500 words AND contains TODO markers or structurally incomplete signals (empty sections, missing thesis/intro, placeholder text), output the single line draft incomplete; unit-economics critique skipped and stop. Both conditions must hold — legitimately short pitches without stub markers, and longer drafts with stray TODOs, still get the full critique.

Using the Fact-Check Report

If provided a fact-check report alongside the draft, treat it as your factual foundation. Do not independently verify quoted CAC figures, churn benchmarks, gross-margin comps, pricing claims, or competitor unit economics the report already assessed.

Instead:

• Reference the fact-check findings where they bear on the math. A churn benchmark rated Inaccurate directly affects the LTV lens.
• Build on the fact-check where it surfaces ambiguity. A "Mostly Accurate" finding on a comp's contribution margin can still affect the gross-margin trajectory lens.
• Focus energy on the lenses below — this skill uniquely provides the structural assessment of whether the per-customer math compounds.

If no fact-check report is provided, emit this warning at the top of your output before the critique begins:

⚠️ No fact-check report provided. This critique does not include independent factual
verification. Checkable numerical claims in the draft (quoted CAC, churn rates, gross-margin
benchmarks, pricing comps) have not been assessed. For full verification, run the
fact-check skill first or use the draft-review orchestrator.

Then proceed focusing on internal consistency and structural argument. Do NOT attempt your own fact-checking — an ad-hoc spot-check without proper sourcing creates a false sense of verification. When discussing unverifiable numerical claims, flag actual confidence: "this 4% monthly churn figure is doing a lot of work and I haven't verified it against the SaaS comp set" beats false confidence or vague hedging.

The Five Lenses

1. CAC (Customer Acquisition Cost)

CAC is rarely a single number — it's a function of channel, segment, and scale. Common failure: reporting a blended CAC concealing a healthy seed-channel CAC mixed with an unhealthy paid-channel CAC, then assuming the blended figure holds as the seed channel runs out.

Moves:

• Decompose by channel. What is CAC per channel (organic, paid, sales-led, partnership, referral)? Blended-only reporting hides the marginal cost of the next customer, which is what matters for scaling.
• CAC at scale, not CAC today. Early CAC is almost always the cheapest CAC the business will see. Auctions get more competitive, low-hanging keywords saturate, referral loops decay, the founder stops closing every deal. Does the plan model CAC expansion as channels scale, or project today's number flat?
• Fully-loaded vs. ad-spend-only. "CAC of $200" can mean ad spend per customer (excluding sales salaries, content, free-trial costs, onboarding), or include those. The plan should be explicit; if not, assume the figure is understated.
• Payback timing relative to CAC. A $5K CAC is fine for a $50K ACV product and ruinous for a $50/month one — but this lens is whether CAC is what the plan says it is. CAC-to-payback is lens #4.

If the plan's CAC depends on a channel that won't scale (founder network, single viral moment, one-off enterprise reference), flag that sustainable CAC is materially higher than reported.

2. LTV (Lifetime Value)

LTV is the most aggressively engineered number in early-stage plans: it stacks three assumptions (retention, expansion, gross margin) and small changes in each produce large changes in LTV. Most reported LTVs are upper bounds, not expected values.

Pressure-test the inputs:

• Churn rate basis. Is quoted churn monthly, annual, gross, or net? Customer churn or revenue churn? 5% monthly customer churn implies 46% annual gross retention — a 2-year average lifetime, not the 10-year lifetime the model may assume.
• Cohort age. Has the cohort lived long enough to observe its actual churn curve? Many "low churn" claims come from cohorts under 12 months old, before the post-honeymoon churn step. Annualizing a 6-month figure is doing a lot of work.
• Expansion assumptions. Net-revenue retention >100% (NRR via upsell, seat expansion, usage growth) is real but earned. If LTV bakes in 120% NRR before a track record, ask what structural mechanism drives expansion — usage scaling with customer growth, seats tied to adoption. "We'll upsell them" is a hope, not a structure.
• Gross-margin input. LTV is gross-margin-weighted lifetime revenue, not revenue. Computing LTV on top-line revenue overstates it by 1/GM. If the plan reports an LTV/CAC ratio, confirm the LTV is margin-weighted (lens #3 feeds this).

If LTV is a single number, ask for implied retention and expansion. If implied numbers exceed the comp set's best performers, that's the headline finding — the plan implicitly claims top-decile retention without saying so.

3. Contribution margin

Contribution margin per customer (revenue minus variable cost per customer, before fixed overhead) is what the business keeps from each unit of growth. Many plans conflate gross margin (revenue minus COGS) with contribution margin (revenue minus all costs that scale with customer count); the latter determines whether scaling helps or hurts.

Check what the plan treats as "fixed" that is actually variable per customer:

• Customer support / success cost per account. For complex products, support and CS scale with customer count. A "fixed cost" support model collapses once customer count triples. If modeled as overhead, ask the per-account cost at scale.
• Onboarding and implementation. One-time per customer but real — especially B2B with multi-week implementations. Capitalizing implementation cost without amortizing into contribution margin overstates per-customer profitability.
• Variable infrastructure. Cloud costs, per-seat third-party licenses (analytics, comms, payment processing), usage-based API costs. Plans quoting 80% gross margin from a SaaS comp set sometimes have 60% real gross margin once usage-based costs are included.
• Payment processing and revenue-share. 2.9% to a payment processor, 30% to an app store, 20% to a channel partner — direct revenue deductions showing up in contribution margin but rarely in headline pricing.

Most actionable finding here is usually: "contribution margin at scale is X% lower than the stated gross margin, which changes the unit-economics conclusion to Y." Make that calculation explicit when the inputs are available.

4. Payback period

Payback period (months to recover CAC from gross-margin-weighted revenue) is the working-capital question: how much cash does the business consume per customer before that customer becomes net positive, and can it fund that gap at the planned growth rate?

Moves:

• CAC payback math. Payback ≈ CAC / (monthly revenue × contribution margin). A 24-month payback on a $50K CAC funds $50K per customer for two years before recovery. At 10 new customers per month, that's $1M of working-capital tied up in unrecovered CAC at any given time — before growth.
• Growth-rate × payback interaction. Faster growth means more new customers in unrecovered CAC simultaneously. A 12-month payback at 100% YoY growth is dramatically more capital-intensive than a 12-month payback at flat growth. Does the plan size the funding ask against this interaction, or a static-state model?
• Industry benchmarks. SaaS rule of thumb: 12-month payback for healthy, 18-24 for acceptable, >24 for problematic absent unusually low churn. Consumer subscription typically faster (<6 months). Marketplaces vary with take rate. Situate the plan's payback against the relevant comp set, not an absolute target.
• What payback ignores. Payback doesn't capture lifetime profitability — a 6-month payback with 7-month average lifetime is worse than an 18-month payback with 5-year lifetime. Use payback for capital efficiency; use LTV/CAC for long-term value. Plans leaning on one and ignoring the other are usually hiding something in the other.

If payback is long and lifetime is short, the business may never reach positive cumulative cash per customer even before fixed costs. That's the most serious unit-economics finding — flag it explicitly.

5. Gross-margin trajectory

A plan's unit economics today are almost never the economics it's funded against — investors fund toward the steady-state margin, which requires a credible path. The trajectory question: does gross margin actually move toward steady state as the business scales, or stall?

Check the levers:

• Where does margin expansion come from? Common drivers: volume discounts from suppliers, in-housing outsourced functions, automation of manual operations, mix shift to higher-margin products, scale economies on infrastructure. Each is real but earned. Name specific levers, not just a 60%→80% margin curve.
• Margin compression risks. Symmetric: what makes margin worse at scale? Competitive price pressure, customer concentration enabling negotiation, regulatory cost loads (compliance, security, audit), support-cost growth on complex customers, usage-based cost outpacing pricing. The plan should acknowledge the compression vectors it's betting against.
• Mix-shift assumptions. If margin expansion depends on selling more enterprise (or premium-tier, or add-on modules), that's a go-to-market claim wearing a margin-trajectory mask. Is there evidence the mix is shifting that way, or does the plan assume the mix that delivers the model?
• Hardware, services, and one-time revenue. Plans including implementation-services revenue at low or negative margin can show healthy blended margin today that deteriorates as services revenue grows with customer count. Separate recurring SaaS margin from services margin in the trajectory.

Most useful framing here: "the plan reports X% gross margin today and projects Y% at steady state. The implicit assumption is [specific lever]. Has that lever been demonstrated in a comparable company at comparable scale?" If not, the trajectory is a hypothesis, not a baseline — say so.

How to Structure the Critique

Output the critique as a Markdown document. Use this exact section layout so downstream consumers (orchestrators, format tests, human readers comparing critiques) can rely on the structure:

# Unit-Economics Critique: <draft title or topic>

## CAC Assessment
## LTV Assessment
## Contribution Margin Assessment
## Payback Period Assessment
## Gross-Margin Trajectory Assessment
## Factual Foundation
## Overall Assessment

If a lens does not apply (e.g., the plan reports no LTV figure), keep the section heading and state what the plan is missing rather than dropping the section. The skeleton is fixed; the content adapts.

CAC Assessment

Decompose CAC by channel where the plan permits. Identify reliance on a non-scaling channel that materially understates sustainable CAC. State whether the CAC figure appears fully-loaded or ad-spend-only.

LTV Assessment

Recover the implied retention, expansion, and gross-margin inputs from the stated LTV. Flag any input exceeding best-in-class comp performance. Note whether LTV appears margin-weighted; if not, recompute roughly and note the corrected figure.

Contribution Margin Assessment

Identify costs the plan treats as fixed that are actually variable per customer (support, onboarding, usage-based infra, processing fees, revenue share). Estimate how much these deductions reduce the stated gross margin at scale, and what that does to the unit-economics conclusion.

Payback Period Assessment

State the implied payback period from CAC, monthly revenue, and contribution margin. Compare to the relevant industry benchmark. Assess working-capital intensity at the planned growth rate — funding ask vs. unrecovered CAC at peak.

Gross-Margin Trajectory Assessment

Name the specific levers the plan implicitly relies on to reach steady-state margin. Note compression vectors the plan ignores. If margin expansion depends on mix shift or a specific operational lever, assess whether that lever has been demonstrated.

Factual Foundation

If a fact-check report was provided, briefly summarize findings bearing on unit economics — especially Unverified or Inaccurate findings about quoted CAC, churn benchmarks, or comp-set margins. If no report was provided, identify the 2-3 numerical claims that would most benefit from fact-checking.

Overall Assessment

Of the five lenses, which surfaces the strongest unit-economics signal and which the weakest? End with the single most important revision the author should make to the model. End constructively — the goal is a more defensible plan, not a takedown.

Output Location

When run standalone (not via the draft-review orchestrator), save your critique as docs/reviews/business-plan-critique-unit-economics.md in the project root. Create docs/reviews/ if it doesn't exist.

When run via the orchestrator, follow the output path the orchestrator specifies.

Goal-Alignment Note

When dispatched by an orchestrator, append a Goal-Alignment Note at the end of your critique using the canonical form from `patterns/orchestrated-review.md`:

## Goal-Alignment Note
- Answered: [yes / partial / no — one phrase]
- Out of scope: [what was set aside and why, or "none"]
- Escalate: [what the orchestrator should action separately, or "nothing"]
- Questions I would have asked: [1-3 short questions, only if scope was unclear; otherwise omit this bullet]

Use the Out of scope line to flag moat/distribution or market-sizing weaknesses you noticed but did not critique (those belong to sibling skills). The Escalate line surfaces a finding crossing into another critic's territory — a CAC argument depending on a distribution claim the moat critic should re-examine, or a churn assumption depending on a fact-check claim the orchestrator should re-examine.

Tone

Direct but constructive. The spirit is "let's see whether the math actually compounds" rather than "let me show you why the numbers don't work." Founders have already heard generic skepticism on unit economics; they need structural diagnosis they can act on. Be specific about what input is doing the load-bearing work in the model, not just what looks optimistic.

Comfort with uncertainty matters. Many unit-economics questions lack a clean early-stage answer — "the LTV figure is consistent with the cohort data observed so far, but the cohort is too young to be confident about steady-state churn" is more useful than either "LTV is wrong" or "numbers look fine." Calibrate confidence explicitly, and when the plan's number could be right but the supporting evidence is thin, say that exactly.