---
name: Budget and Bidding
slug: budget-and-bidding
category: Data
description: "Budget and Bidding plans and reviews paid-media budgets, bidding, pacing, marginal return, forecasts, and key metrics like CPA, ROAS, MER, LTV:CAC across platforms. Use it for allocation, scaling, pacing, forecast, or investment tradeoffs."
github: "https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-budget"
language: Python
stars: 8064
forks: 1200
install: "npx degit https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-budget ~/.claude/skills/ads-budget"
installs_to: ~/.claude/skills/ads-budget
source_path: skills/ads-budget/SKILL.md
collection_size: 25
category_size: 668
collection_url: "https://dirskills.com/collections/AgriciDaniel/claude-ads"
added: 2026-08-15T06:51:06.403Z
last_synced: 2026-08-15T06:51:06.403Z
canonical_url: "https://dirskills.com/skills/budget-and-bidding"
---

# Budget and Bidding

Budget and Bidding plans and reviews paid-media budgets, bidding, pacing, marginal return, forecasts, and key metrics like CPA, ROAS, MER, LTV:CAC across platforms. Use it for allocation, scaling, pacing, forecast, or investment tradeoffs.

**Install:**

```bash
npx degit https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-budget ~/.claude/skills/ads-budget
```

## README

# Budget and Bidding

1. Establish objective, conversion value, gross margin, cash constraints, sales
   capacity, attribution uncertainty, seasonality, and platform minimum evidence.
2. Normalize spend and outcomes to comparable windows and definitions.
3. Calculate break-even boundaries and show formulas, inputs, uncertainty, and
   sensitivity cases.
4. Distinguish committed baseline, controlled experiments, and reserve capacity.
5. Compare hold, reallocate, scale, reduce, or experiment options using marginal
   evidence rather than blended averages alone.
6. Return a decision-complete plan with platform/campaign amount, timing, owner,
   guardrails, success measure, and rollback trigger.

Rules such as 70/20/10, fixed CPA multiples, fixed budget-to-CPA ratios, and fixed
percentage scaling are optional heuristics, never universal authorization.