Seller Profit Guard

Break-even ROAS worked example for prospecting

Last updated: 2026-07-31

Written and reviewed by Seller Profit Guard Editorial Team.

A USD 100 retained-revenue prospecting cohort with USD 61.30 of pre-ad variable costs leaves USD 38.70 contribution before ads. Break-even ROAS is 2.58x. Reserving 15% contribution leaves USD 23.70 target-safe spend and a 4.22x target ROAS; USD 20 planned spend leaves USD 3.70 headroom.

Confirm the USD 100 values

Use USD 100 retained revenue and USD 100 platform conversion value for the same mature purchase cohort. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

Matching values are an evidenced fixture, not an assumption that all systems always agree. Review point 1 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Assemble the USD 61.30 cost

Combine USD 35 product, USD 2 packaging, USD 8 fulfillment, USD 10 variable fee, USD 0.30 fixed fee, USD 4 expected loss, and USD 2 other variable cost. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

Keep advertising spend out of the pre-ad pool. Review point 2 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Calculate USD 38.70 contribution

Subtract the complete cost packet from retained revenue. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

This is the maximum modeled break-even ad cost. Review point 3 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Calculate 2.58x break-even ROAS

Divide USD 100 conversion value by USD 38.70. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

The threshold is an outer boundary with zero post-ad contribution. Review point 4 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Reserve USD 15 target contribution

Apply the 15% target to retained revenue. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

The reserve belongs after advertising and before fixed overhead interpretation. Review point 5 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Calculate the 4.22x target

Subtract USD 15 from USD 38.70, then divide USD 100 by the USD 23.70 target-safe ceiling. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

The target ratio is stricter than break-even. Review point 6 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Evaluate USD 20 planned spend

Planned ROAS is 5.00x and post-ad contribution is USD 18.70. Add the result to the prospecting cohort worksheet with its cohort alias, source version, evidence date, owner, currency, window, denominator, scope, and affected output. This makes a traceable prospecting spend decision reproducible instead of dependent on memory or an unversioned dashboard.

The plan retains 18.70% contribution and USD 3.70 target headroom. Review point 7 must distinguish observed data, explicit assumptions, unresolved evidence, and decisions outside the calculator. Keep retained revenue, reported conversion value, spend, variable costs, attribution, refunds, delay, target, and maturity separate.

Validate supported and broken fixtures

Recalculate variable fee, fixed variable-cost pool, contribution before ads, break-even spend, break-even ROAS, target reserve, target-safe spend, target ROAS, planned ROAS, post-ad contribution, reported-value gap, margin, and normalized headroom independently. Test valid, overspend, higher-loss, excessive-value-gap, thin-headroom, no-contribution, and invalid-evidence cases.

Preserve full precision before formatting. A fixture passes only when numeric outputs, Block/Review/Ready state, issue text, reset behavior, browser-local privacy boundary, keyboard path, mobile layout, and correction route match the declared evidence packet.

Apply Block, Review, and Ready consistently

Block invalid amounts, rates, thresholds, source date, confirmations, scenario, attribution context, currency, period, scope, or declared conflicts. Review valid calculations with nonpositive contribution, no target-safe room, planned overspend, negative post-ad contribution, excessive reported-value gap, or insufficient normalized headroom. Ready requires a structurally valid packet and every seller-entered gate.

Ready is calculation readiness only. It cannot approve attribution, bid strategy, budget, audience, creative, platform eligibility, legal terms, tax, accounting treatment, or campaign launch. Record the exact passed condition and operational owner.

Release, observe, and restore safely

Before release, retain narrow local and remote backups plus a rollback identifier. Run typecheck, unit and integration tests, build, content and duplicate audits, SEO and static-route checks, browser interaction, four-image loading, internal links, mobile and keyboard accessibility, privacy review, candidate validation, and origin checks.

After release, verify status, canonical, indexability, Article and Breadcrumb schema, direct answer, parent and sibling links, images, guide-hub discovery, strict 404, sitemap policy, events, and production scenarios. Record Day 0/7/14/28 evidence and restore on formula, privacy, accessibility, routing, or health regression.

Raise variable fees

Increase the fee from 10% to 12% and calculate the lost spend capacity. Deep review 1 stores the tested input, source state, numeric delta, authority boundary, reviewer, expiry, correction condition, and next action in the prospecting cohort worksheet. Retain counterexamples even when they do not support the preferred campaign decision.

Compare the result with a traceable prospecting spend decision, not a generic benchmark or another cohort at a different grain. Explain which single driver moved, which fields stayed constant, what remains unknown, and whether the response is collect, reconcile, stress, review, observe, correct, pause, release, or restore.

Lower conversion value only

Keep seller economics constant and explain why reported ratio thresholds rise. Deep review 2 stores the tested input, source state, numeric delta, authority boundary, reviewer, expiry, correction condition, and next action in the prospecting cohort worksheet. Retain counterexamples even when they do not support the preferred campaign decision.

Compare the result with a traceable prospecting spend decision, not a generic benchmark or another cohort at a different grain. Explain which single driver moved, which fields stayed constant, what remains unknown, and whether the response is collect, reconcile, stress, review, observe, correct, pause, release, or restore.

Raise fulfillment cost

Model a remote-zone product mix without blending it into the standard cohort. Deep review 3 stores the tested input, source state, numeric delta, authority boundary, reviewer, expiry, correction condition, and next action in the prospecting cohort worksheet. Retain counterexamples even when they do not support the preferred campaign decision.

Compare the result with a traceable prospecting spend decision, not a generic benchmark or another cohort at a different grain. Explain which single driver moved, which fields stayed constant, what remains unknown, and whether the response is collect, reconcile, stress, review, observe, correct, pause, release, or restore.

Delay the evaluation

Exclude an immature conversion tail and document why the earlier report is provisional. Deep review 4 stores the tested input, source state, numeric delta, authority boundary, reviewer, expiry, correction condition, and next action in the prospecting cohort worksheet. Retain counterexamples even when they do not support the preferred campaign decision.

Compare the result with a traceable prospecting spend decision, not a generic benchmark or another cohort at a different grain. Explain which single driver moved, which fields stayed constant, what remains unknown, and whether the response is collect, reconcile, stress, review, observe, correct, pause, release, or restore.

Reconcile realized spend

Compare billed campaign cost with the planned USD 20 after the cohort closes. Deep review 5 stores the tested input, source state, numeric delta, authority boundary, reviewer, expiry, correction condition, and next action in the prospecting cohort worksheet. Retain counterexamples even when they do not support the preferred campaign decision.

Compare the result with a traceable prospecting spend decision, not a generic benchmark or another cohort at a different grain. Explain which single driver moved, which fields stayed constant, what remains unknown, and whether the response is collect, reconcile, stress, review, observe, correct, pause, release, or restore.

Confirm the USD 100 values: verification drill

Recreate “Confirm the USD 100 values” from a clean synthetic cohort instead of copying the primary example. Use USD 100 retained revenue and USD 100 platform conversion value for the same mature purchase cohort. Change one driver, retain all other fields, calculate the before-and-after difference, and attach source state and expected output to the prospecting cohort worksheet.

Matching values are an evidenced fixture, not an assumption that all systems always agree. Drill 1 includes a supported case, broken case, late-evidence case, and correction case. Explain why each path produces Block, Review, Ready, no spend room, changed headroom, or a revised threshold for this specific a traceable prospecting spend decision.

Assemble the USD 61.30 cost: verification drill

Recreate “Assemble the USD 61.30 cost” from a clean synthetic cohort instead of copying the primary example. Combine USD 35 product, USD 2 packaging, USD 8 fulfillment, USD 10 variable fee, USD 0.30 fixed fee, USD 4 expected loss, and USD 2 other variable cost. Change one driver, retain all other fields, calculate the before-and-after difference, and attach source state and expected output to the prospecting cohort worksheet.

Keep advertising spend out of the pre-ad pool. Drill 2 includes a supported case, broken case, late-evidence case, and correction case. Explain why each path produces Block, Review, Ready, no spend room, changed headroom, or a revised threshold for this specific a traceable prospecting spend decision.

Calculate USD 38.70 contribution: verification drill

Recreate “Calculate USD 38.70 contribution” from a clean synthetic cohort instead of copying the primary example. Subtract the complete cost packet from retained revenue. Change one driver, retain all other fields, calculate the before-and-after difference, and attach source state and expected output to the prospecting cohort worksheet.

This is the maximum modeled break-even ad cost. Drill 3 includes a supported case, broken case, late-evidence case, and correction case. Explain why each path produces Block, Review, Ready, no spend room, changed headroom, or a revised threshold for this specific a traceable prospecting spend decision.

Calculate 2.58x break-even ROAS: verification drill

Recreate “Calculate 2.58x break-even ROAS” from a clean synthetic cohort instead of copying the primary example. Divide USD 100 conversion value by USD 38.70. Change one driver, retain all other fields, calculate the before-and-after difference, and attach source state and expected output to the prospecting cohort worksheet.

The threshold is an outer boundary with zero post-ad contribution. Drill 4 includes a supported case, broken case, late-evidence case, and correction case. Explain why each path produces Block, Review, Ready, no spend room, changed headroom, or a revised threshold for this specific a traceable prospecting spend decision.

Reserve USD 15 target contribution: verification drill

Recreate “Reserve USD 15 target contribution” from a clean synthetic cohort instead of copying the primary example. Apply the 15% target to retained revenue. Change one driver, retain all other fields, calculate the before-and-after difference, and attach source state and expected output to the prospecting cohort worksheet.

The reserve belongs after advertising and before fixed overhead interpretation. Drill 5 includes a supported case, broken case, late-evidence case, and correction case. Explain why each path produces Block, Review, Ready, no spend room, changed headroom, or a revised threshold for this specific a traceable prospecting spend decision.

Sources and further reading

• Seller Profit Guard methodology: Contribution equations, evidence versions, privacy, correction, release, and rollback.
• Seller Profit Guard data privacy: Local-first boundaries for customer, order, advertising, payment, refund, audience, and raw-record data.
• Google Ads Help: Conversion value per cost definition: Official reporting formula: conversion value divided by cost.
• Google Ads Help: About Target ROAS bidding: Official definition of Target ROAS as an average conversion-value-per-cost objective and guidance on conversion-delay evaluation.
• Google Ads Help: About conversion values: Official context for conversion values, reporting, and value-based bidding.
• Google Ads Help: Data exclusions: Official limits for conversion-tracking data exclusions; exclusions apply to click periods and do not alter reporting.

Related Seller Profit Guard tools

• Break-Even ROAS Calculator: Run the browser-local retained-contribution and ROAS calculation.
• Break-Even ROAS and Return-Loss Guide: Review the existing nine-cost model and return-loss example.
• Etsy Ads Break-Even Calculator: Use the Etsy-specific fee and campaign model when that scope fits.
• Contribution Margin Calculator: Reconstruct retained contribution before advertising.
• Maximum Discount Calculator: Keep merchandise promotion headroom separate from paid-media headroom.
• Methodology: Review evidence, privacy, calculation, correction, release, and rollback.
• Data Privacy: Protect buyer, order, ad-platform, audience, payment, refund, and credential data.
• Break-Even ROAS Formula and Inputs: Derive break-even and target ROAS from retained revenue, conversion value, variable order costs, expected loss, contribution target, and ad spend.
• Break-Even ROAS for Retargeting: Model a retargeting cohort without reusing prospecting attribution, audience, conversion value, product mix, or spend assumptions.
• Break-Even ROAS Calculation Mistakes: Fix numerator, denominator, attribution, fee, refund, return-loss, product-mix, timing, target, and false-profit errors before using ROAS.
• Break-Even ROAS Evidence Sources: Map every ROAS input to advertising reports, retained-order records, cost libraries, fee statements, return cohorts, target policy, and delay evidence.
• Set a Safe ROAS Decision Threshold: Separate break-even, target, stress, warning, and stop thresholds while preserving attribution uncertainty and seller governance.
• Prospecting vs Retargeting ROAS: Compare prospecting and retargeting at one economic grain while keeping audience, attribution, exposure, product mix, and incrementality questions separate.
• Weekly Break-Even ROAS Review Cycle: Run a repeatable ROAS review from source refresh and cohort closure through calculation, approval, observation, correction, and rollback.
• Interpret Break-Even ROAS Results: Read contribution, spend ceilings, break-even ROAS, target ROAS, planned ROAS, post-ad margin, and headroom without false precision.
• Break-Even ROAS Audit Checklist: Audit cohort scope, values, costs, attribution, delays, formulas, fixtures, privacy, release evidence, corrections, and rollback in one log.

Next step: Open Seller Profit Guard.

This is operational planning help, not tax, accounting, legal, financial, or platform-policy advice. Review the Terms and disclaimer, and verify current platform rules and fee assumptions before changing prices.