ads-math
agricidaniel/claude-ads
Calculate CPA, ROAS, LTV:CAC, break-even, and paid-media financial models with scenario analysis.
What is ads-math?
A financial modeling skill for paid advertising metrics and decisions. Use it to compute cost-per-acquisition, return-on-ad-spend, lifetime-value-to-customer-acquisition-cost ratios, break-even targets, contribution margins, and budget forecasts with upside/downside scenarios.
- Calculate CPA, CPL, CPC, CPM, ROAS, MER, and LTV:CAC ratios
- Model break-even targets and contribution margins
- Forecast budgets and experiment economics
- Build base, downside, and upside scenarios for uncertainty
- Validate inputs, denominators, and unit conversions
- Return machine-readable formulas, inputs, outputs, and sensitivities
How to install ads-math
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-mathHow to use ads-math
- 1.Identify the financial decision and gather inputs: units, currency, period, margin, attribution basis, and uncertainty ranges
- 2.Provide or cite the source data for revenue, spend, conversions, and any tax or refund treatment
- 3.Request the specific metric (e.g., ROAS, CPA, LTV:CAC, break-even) and decision context
- 4.Review the formula mapping, input validation, and scenario outputs (base, downside, upside)
- 5.Use sensitivities and decision implications to inform budget or strategy changes
Use cases
- Determine if a paid-media campaign meets profitability thresholds before scaling
- Compare ROAS across channels to allocate budget efficiently
- Calculate break-even CPA given margin and LTV constraints
- Model impression-share opportunity and budget impact on volume
- Analyze experiment results with confidence ranges and decision implications
- Performance marketers and PPC specialists
- Marketing finance analysts
- Growth and demand-generation leaders
- Product managers evaluating customer acquisition cost
ads-math FAQ
Platform-attributed revenue is what the ad platform reports; blended business revenue accounts for multi-touch attribution and other channels. The skill keeps them distinct to avoid overstating ROAS.
Point forecasts hide uncertainty. Upside and downside scenarios show how changes in conversion rate, AOV, or cost affect profitability, making decisions more robust.
The skill is designed for paid advertising (PPC, CPM, CPA models). For other financial decisions, you may need different assumptions or frameworks.
The skill will not fabricate missing inputs. It will flag what's needed and ask you to provide or estimate it based on your data.
LTV:CAC > 3 is generally healthy; it means lifetime value is at least 3× the cost to acquire. The skill calculates this given your margin, retention, and acquisition cost.
Full instructions (SKILL.md)
Source of truth, from agricidaniel/claude-ads.
name: ads-math description: "Calculate and model paid-media CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics. Use for PPC math, ad calculator, break-even analysis, ROAS calculator, CPA calculator, budget forecast, LTV CAC, or MER."
Paid Media Financial Model
- Identify the decision and collect units, currency, period, tax/refund treatment, margin, attribution basis, and uncertainty.
- Show the formula and map every input to an operator value or cited artifact.
- Validate denominators, sign, missing values, incompatible windows, and unit conversions.
- Calculate base, downside, and upside cases where uncertainty affects the decision.
- Keep platform-attributed revenue, blended business revenue, cash flow, and contribution margin distinct.
- Return machine-readable inputs, formulas, outputs, sensitivities, and decision implications.
Never fabricate missing financial inputs, hide division-by-zero, or present a point forecast without its assumptions.
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