Contribution Margin Template

AND Studio · math layer · V1 draft

AND

The math layer of every engagement. One template, one method, every client. Built on Taylor Holiday's framework. Refresh after deeper portal review.

What CM Actually Is

Contribution margin is the dollars left from a sale after every variable cost, including marketing. It's what's available to cover fixed costs (rent, salaries, software) and profit.

CM is the most important number a DTC operator can know. ROAS lies. MER hides COGS. CM tells you whether each order is actually making money.

Revenue minus COGS minus shipping + fulfillment minus payment processing minus returns minus marketing spend = Contribution Margin

The Inputs

Five variable cost lanes. Four come from the client. One we control.

Input	Source	Format	Notes
COGS per unit	Client	Dollar per unit	Landed cost. Per-unit packaging, inserts, freight-in included.
Shipping + fulfillment per order	Client	Dollar per order	3PL pick/pack/ship blended cost. Proxy at $7–$10 if unknown.
Payment processing rate	Client	% of revenue	Usually 2.5%–3.5%. Shopify Payments + PayPal blend.
Return rate	Client	% of revenue	Apparel 20%+, supplements 2–5%, body care 3–8%.
Marketing spend	AND pulls	Dollar per period	From Meta + Google + any other paid channel.

The one ask the client cannot skip The first four inputs are the only ASK in the intake. Without them we cannot model CM. Directional is fine, exact is better. We refine as actuals come in.

Engine design question · Shopify access CTC's Admission platform pulls these inputs directly from Shopify. Three of the four ASKs above (shipping + fulfillment, processing rate, return rate) are derivable from Shopify order data when we have read access. Only COGS per unit stays a true client ASK.

Today (ask-driven): Client provides all 4 inputs. Lower trust threshold. Faster to start.
Tomorrow (pull-driven): Shopify read access. We derive 3 of 4. Client confirms COGS per unit only. Operator posture.

Open question for SOP 02.01: does Shopify read access become a standard ask for new engagements, especially On the Keys mode where we're making spend calls against unit economics. Recommendation: yes, as default for On the Keys; optional for Creative Only.

The Calculation

Per-order CM

AOV (average order value)
  − COGS per order (COGS × units per order)
  − Shipping + fulfillment per order
  − Processing (AOV × processing rate)
  − Returns reserve (AOV × return rate)
  − Marketing cost per order (period spend ÷ orders in period)
  = Contribution Margin per Order

CM percent

CM per order ÷ AOV = CM %

Pre-marketing CM (the most useful number)

AOV − COGS − Shipping/Fulfillment − Processing − Returns
  = Pre-marketing CM per order
  ÷ AOV
  = Pre-marketing CM %

This is the ceiling. Marketing eats into this. Whatever's left is true CM.

Break-even MER

Break-even MER = 1 ÷ Pre-marketing CM %

If pre-marketing CM is 40%, break-even MER is 2.5. Spending below that MER, you lose money on marketing. Above it, you make CM dollars on every dollar spent.

Target MER for a target CM %

Target MER = 1 ÷ (Pre-marketing CM % − Target CM %)

If pre-marketing CM is 40% and you want 15% CM, target MER is 1 ÷ (0.40 − 0.15) = 1 ÷ 0.25 = 4.0.

Live Calculator

Plug in any brand's numbers. CM and MER targets recalc instantly. Defaults below are a hypothetical body care brand at $58 AOV.

CM Calculator

Numbers update on the fly. Change any input.

Inputs · from the client

Average Order Value ($)

Units per order

COGS per unit ($)

Shipping + fulfillment / order ($)

Processing rate (%)

Return rate (%)

Inputs · marketing (AND pulls)

Marketing spend (period $)

Orders in period

Target

Target CM % (for required MER)

Outputs · pre-marketing

COGS per order—

Shipping + fulfillment—

Processing—

Returns reserve—

Pre-marketing CM ($)—

Pre-marketing CM (%)—

Outputs · post-marketing

Marketing cost per order—

Period MER (blended)—

Contribution Margin / order—

CM %—

Outputs · MER targets

Break-even MER—

MER required for target CM—

Period MER = revenue in period ÷ marketing spend in period. Revenue in period is approximated as AOV × Orders in period.

Worked Example

Hypothetical body care brand at $58 AOV, 1 unit per order, supplements category economics.

Line	Value	Notes
AOV	$58.00
COGS	($11.60)	20% of AOV
Shipping + fulfillment	($8.50)	3PL blended
Processing	($1.74)	3.0% of AOV
Returns reserve	($2.32)	4% of AOV
Pre-marketing CM	$33.84	58.3% of AOV
Marketing spend	($14.50)	at MER of 4.0 ($58 ÷ $14.50)
Contribution Margin	$19.34	33.3% of AOV

Break-even MER = 1 ÷ 0.583 = 1.72
MER for 15% CM = 1 ÷ (0.583 − 0.15) = 2.31
MER for 25% CM = 1 ÷ (0.583 − 0.25) = 3.00
MER for 33% CM = 1 ÷ (0.583 − 0.33) = 3.95

At MER 4.0, this brand makes 33% CM. At MER 3.0 it makes 25%. At MER 2.0 it's near break-even. This is the engine of every weekly read.

New Customer CM (nCM)

For the launch and the first 90 days, model nCM separately. New customers cost more to acquire than returning customers. Use a new-customer-only AOV (often lower) and a new-customer-only MER (always lower than blended because returning customers don't need ads).

nMER = New customer revenue ÷ Total marketing spend

Standard model: target new-customer CM near zero or slightly negative for the first 30–90 days IF LTV justifies it. If LTV doesn't, do not buy the customer.

LTV target for a body care launch: 90-day LTV at minimum 1.5x first-order CM. If a customer who costs $X in CM the first order returns $1.5X within 90 days, we can scale.

How AND Uses This

At intake

Client sends the four inputs.
We model pre-marketing CM, break-even MER, target MER for their margin goal.
Engagement memo names the MER target as a contract-level metric.

Weekly read

Pull marketing spend from Meta + Google for the period.
Pull revenue, orders, AOV from Shopify.
Calculate CM per order, CM %, MER, nMER.
Compare to target. Decide: scale, hold, kill.

Monthly read

30-day rolling CM.
30-day rolling nMER.
30-day rolling LTV cohort (first-order revenue + 30/60/90-day repeat revenue).
Recommendation: budget shape next 30 days.

Quarterly read

90-day cohort lift on nCM.
Re-baseline the four inputs (COGS may have moved, return rate may have shifted, processing may have changed).
Adjust target MER for next quarter.

The CM Dashboard View

Each client gets a CM tab on their Evergreen Dashboard. Columns:

Metric	L7	L30	L90	L365
Revenue	—	—	—	—
Orders	—	—	—	—
AOV	—	—	—	—
Marketing spend	—	—	—	—
MER (blended)	—	—	—	—
Pre-marketing CM %	—	—	—	—
CM $	—	—	—	—
CM %	—	—	—	—
nMER	—	—	—	—
30-day repeat rate	—	—	—	—

Refreshed weekly. Owned by the Performance Lead (today: TBD, closing through Director of Growth Analytics search + Growth Strategist hire).

What Clients See

Plain-English version, in the engagement memo:

Your contribution margin is the dollars left from a sale after every variable cost, including marketing. We model this from day one. Every weekly read shows: how much is each order making, how does this compare to your target, what's the next move.

The four asks (in the intake email):

COGS per unit
Shipping + fulfillment per order
Payment processing rate
Return rate

Directional is fine. We refine as actuals come in.

Where This Lives in the SOP

Lives in 02 Creative Strategy · 02.04 Evergreen Dashboard and 04 Performance · 04.04 Contribution Margin Model.

Cross-referenced from 02.01 Onboarding (the ASK) and 02.08 Engagement Memo (the target).

Open Items

Shopify access posture decision. Does Shopify read access become a standard ask in SOP 02.01? If yes, the inputs section above shifts from ask-driven to pull-driven for ship/fulfill, processing rate, and return rate. COGS per unit remains the one true ask. Recommended default: standard for On the Keys engagements; optional for Creative Only.
Worked example with real Smooch numbers (pending Luisa's four inputs back).
nMER target by tier (Crawl / Walk / Run benchmarks) once 30 days of data lands on the first three engagements.
Refresh against the ADmission portal's specific tooling once we're inside it (Statlas or whatever lives behind the login).
Decide: Google Sheet template, Notion calculator, or wire into the Evergreen Dashboard product directly. Recommendation: Sheet first, dashboard second.