Skill: leooooooow/break-even-calculator-ecommerce (version 1.1.0)

# Break-even Calculator Ecommerce Calculate the real no-loss line before deciding whether to launch harder, discount harder, or scale paid traffic. This is not a generic margin calculator. It separates variable from fixed costs, models real ecommerce unit economics (returns, payment fees, platform takes), and translates math into actionable launch/hold/scale decisions. --- ## Quick Reference | Decision | Key Metric | Green | Yellow | Red | |---|---|---|---|---| | Launch viability | Contribution margin % | > 40% | 20–40% | < 20% | | Ad scaling room | Break-even CPA | CPA < 60% of CM | CPA 60–90% of CM | CPA > 90% of CM | | Discount safety | Margin after discount | > 25% CM remaining | 10–25% CM remaining | < 10% CM remaining | | Free shipping | Margin absorption | Shipping < 30% of CM | Shipping 30–50% of CM | Shipping > 50% of CM | | Scale readiness | Break-even units/mo | < 50% of current vol | 50–80% of current vol | > 80% of current vol | --- ## Solves Ecommerce operators lose money not because they can't calculate margins, but because: - They use gross margin when they should use contribution margin - Platform fees, payment processing, returns, and packaging get excluded from "cost" - Ad scaling decisions are made on ROAS without knowing actual break-even ROAS - Discount and free-shipping policies are set without modeling margin impact - "Profitable" products turn unprofitable at scale because fixed costs aren't allocated - Teams confuse revenue growth with profit growth Goal: **Give operators a clear, reviewable break-even model that supports real decisions — not just a number.** --- ## Use when - You need a break-even view before launching or scaling a product - A team is changing price, discount, bundle, or free-shipping policy - Paid acquisition is growing but true profitability is unclear - Margin pressure is increasing and you need a decision baseline fast - Evaluating whether to run a promotion, flash sale, or bundle offer - Comparing profitability across SKUs, channels, or fulfillment methods - Building a case for price changes or cost reductions ## Do not use when - You need full accounting, tax treatment, or cash-flow modeling - Core inputs are missing and nobody can provide reasonable assumptions - The task is valuation, forecasting, or board-level finance reporting - You only want gross revenue math without cost realism - Legal or compliance-sensitive financial reporting is required --- ## Inputs Gather these inputs — mark any assumptions explicitly: **Revenue side:** - Selling price (or price range if testing) - Average order value (AOV) if bundling - Expected discount % or coupon structure **Variable costs per unit:** - COGS / unit cost (landed cost including freight to warehouse) - Shipping to customer (outbound) - Packaging & pick-pack-ship labor - Payment processing fees (typically 2.5–3.5%) - Platform/marketplace fees (e.g., Amazon 15%, Shopify Payments 2.9%) - Return/refund rate and cost per return **Acquisition costs:** - Ad spend or budget - Target or actual CPA (cost per acquisition) - Target or actual ROAS - Organic vs paid traffic mix if known **Fixed costs (if relevant):** - Monthly overhead (warehouse, tools, staff) - Subscription/platform fees - Content/creative production costs See `references/cost-breakdown-guide.md` for detailed cost taxonomy. --- ## Workflow ### 1. Separate variable costs from fixed costs This is the most common error. Be explicit about what scales with volume and what doesn't. **Variable (per-unit):** - COGS, shipping, packaging, payment fees, platform fees, returns **Fixed (per-period):** - Rent, salaries, SaaS tools, insurance, loan payments **Semi-variable (step functions):** - Warehouse staff (fixed per shift, but add shifts at volume thresholds) - 3PL fees (often tiered) Use the cost classification in `references/cost-breakdown-guide.md` to ensure nothing is missed. ### 2. Calculate contribution margin ``` Contribution Margin (CM) = Selling Price - Total Variable Costs per Unit CM% = CM / Selling Price × 100 ``` **Include ALL variable costs:** - COGS - Outbound shipping (if seller-paid) - Packaging + pick-pack - Payment processing (% of selling price) - Platform/marketplace fees (% of selling price) - Return cost allocation = (return rate × cost per return) ### 3. Calculate break-even points **Break-even units (with fixed costs):** ``` BE Units = Fixed Costs / CM per unit ``` **Break-even CPA:** ``` BE CPA = CM per unit (before ad spend) ``` This is the maximum you can pay to acquire a customer and still break even on first order. **Break-even ROAS:** ``` BE ROAS = Selling Price / (Selling Price - CM + CPA target) ``` Or more simply: ``` BE ROAS = 1 / (CM% before ad spend) ``` ### 4. Run sensitivity analysis Model how the break-even shifts when key inputs change. Focus on the variables the team can actually control: | Variable | Test range | Impact on | |---|---|---| | Selling price | ±10–20% | CM, BE units, BE ROAS | | COGS | ±5–15% | CM, BE units | | Ad CPA | ±20–50% | Profitability, scale room | | Return rate | ±3–10pp | CM, effective margin | | Discount depth | 10/15/20/25% off | CM, BE units, BE ROAS | | Shipping policy | Paid vs free vs threshold | CM, conversion rate | Use `references/sensitivity-template.md` for structured output. ### 5. Translate to decisions Don't just output numbers. Frame results as decisions: | Result | Decision framing | |---|---| | CM > 40%, BE CPA has room | **Scale:** Increase ad spend, test new channels | | CM 20–40%, tight CPA room | **Optimize:** Reduce COGS, improve conversion, test pricing | | CM < 20% | **Hold:** Don't scale until unit economics improve | | Discount breaks BE | **Don't discount:** Use value-adds instead of % off | | Free shipping kills margin | **Set threshold:** Offer free shipping above $X AOV | | High return rate crushing CM | **Fix product/listing:** Returns are a product/expectation problem | ### 6. Quality-check the model Before presenting results, verify with `assets/model-checklist.md`: - Are all variable costs included? - Are assumptions labeled with confidence levels? - Does the model account for returns? - Is payment processing calculated on selling price (not COGS)? - Are platform fees applied correctly? --- ## Output Return a structured analysis package (see `references/output-template.md`): 1. **Assumptions table** - Every input listed with source (actual data vs estimate vs industry benchmark) - Confidence flag: ✅ confirmed / ⚠️ estimated / ❓ assumed 2. **Unit economics breakdown** - Revenue per unit → all variable costs → contribution margin - Show each cost line, not just totals 3. **Break-even results** - Break-even units per month - Break-even CPA - Break-even ROAS - Current margin vs break-even margin 4. **Sensitivity analysis** - 2–3 scenarios showing how key variables shift break-even - Highlight which variable has the strongest impact 5. **Decision recommendation** - Launch / Hold / Scale / Optimize - Specific actions based on the numbers - Risk flags (e.g., "margin too thin for discounting") --- ## Quality bar Strong output should: - Show all math explicitly — no black boxes - Keep variable and fixed costs clearly separated - Include return/refund impact (most calculators ignore this) - Label every assumption with confidence level - Frame results as decisions, not just numbers - Help teams avoid "fake-profit" decisions ## What "better" looks like Better output goes beyond "your break-even is X units." It helps decide: - Whether the offer is viable at current costs - How much ad spend room exists before break-even - Whether discounting breaks the model - Which cost lever matters most (COGS? Shipping? Returns?) - Whether the business is near scale-ready or still too fragile - What would need to change to make the unit economics work --- ## Examples ### Example 1: DTC skincare product **Inputs:** - Selling price: $45 - COGS: $8.50 - Shipping: $5.50 - Packaging: $2.00 - Payment processing (3%): $1.35 - Platform fees: $0 (own Shopify store) - Return rate: 8%, cost per return: $7 **Calculation:** - Return cost allocation: 8% × $7 = $0.56/unit - Total variable cost: $17.91 - **Contribution margin: $27.09 (60.2%)** - Break-even CPA: $27.09 - If actual CPA is $18 → $9.09 profit per order → **Scale** ### Example 2: Amazon marketplace electronics **Inputs:** - Selling price: $29.99 - COGS: $11.00 - FBA fees: $5.50 - Amazon referral (15%): $4.50 - Return rate: 12%, cost per return: $9 **Calculation:** - Return cost allocation: 12% × $9 = $1.08/unit - Total variable cost: $22.08 - **Contribution margin: $7.91 (26.4%)** - Break-even CPA: $7.91 - If PPC CPA is $6.50 → only $1.41 profit per order → **Optimize before scaling** --- ## Common mistakes 1. **Forgetting payment processing fees** — 2.5–3.5% of every sale adds up fast 2. **Ignoring return costs** — A 10% return rate with $8 return cost = $0.80/unit drag 3. **Using gross margin instead of contribution margin** — Gross margin excludes shipping, fees, returns 4. **Not modeling discounts through** — A 20% discount on a 30% margin product leaves only 10% margin 5. **Treating CPA as fixed** — CPA rises as you scale (diminishing returns on ad spend) --- ## Resources - `references/output-template.md` — Structured output format - `references/cost-breakdown-guide.md` — Comprehensive cost taxonomy for ecommerce - `references/sensitivity-template.md` — Sensitivity analysis framework - `assets/model-checklist.md` — Pre-delivery quality checklist


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)