Ad Spend Optimizer

This does the math on where your ad dollars are actually working. Feed it performance data across Google, Meta, LinkedIn, or TikTok and it calculates marginal ROI per channel, spots diminishing returns, and models reallocation scenarios to improve ROAS and CAC. Built around a 70/20/10 framework (proven channels, optimization tests, new experiments) with weekly monitoring checklists and specific scaling rules like "if CAC stays 15% below target for two weeks, increase spend 25%." It won't pull live data or touch your campaigns directly, but it will tell you exactly how to rebalance a multi-channel budget when something stops working or you need to justify scaling up.

skills.sh installs: 217
GitHub stars: 150
last updated: Aug 21, 2026

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Install

$ npx -y skills add guia-matthieu/clawfu-skills --skill ad-spend-optimizer --agent claude-code

Installs into .claude/skills of the current project.

Files

Ad Spend Optimizer

Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC.

When to Use This Skill

Quarterly budget planning — reallocate spend based on performance data
Channel mix optimization — find the right balance across platforms
Performance troubleshooting — diagnose why CAC is rising or ROAS declining
Scaling decisions — determine if a channel has headroom to scale
New channel testing — structure test budgets with clear success criteria

Methodology Foundation

Aspect	Details
Source	Marginal ROI optimization + portfolio theory for marketing
Core Principle	Allocate each dollar where the marginal return is highest — shift spend from diminishing-returns channels to underspent ones
Framework	70/20/10 — 70% proven channels, 20% optimization tests, 10% new channel experiments