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ad-spend-optimizer

guia-matthieu
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About

This skill analyzes advertising performance data across platforms like Google Ads and Meta to recommend budget reallocations that maximize return on ad spend (ROAS) and minimize customer acquisition cost (CAC). Developers can use it for quarterly planning, diagnosing underperforming channels, and rebalancing the media mix after performance shifts. Its key capability is calculating marginal ROI to inform data-driven decisions on scaling or reducing spend.

Quick Install

Claude Code

Recommended
Primary
npx skills add guia-matthieu/clawfu-skills -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/guia-matthieu/clawfu-skills
Git CloneAlternative
git clone https://github.com/guia-matthieu/clawfu-skills.git ~/.claude/skills/ad-spend-optimizer

Copy and paste this command in Claude Code to install this skill

Documentation

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

AspectDetails
SourceMarginal ROI optimization + portfolio theory for marketing
Core PrincipleAllocate each dollar where the marginal return is highest — shift spend from diminishing-returns channels to underspent ones
Framework70/20/10 — 70% proven channels, 20% optimization tests, 10% new channel experiments

What Claude Does vs What You Decide

Claude DoesYou Decide
Calculates ROAS, CAC, and CPL per channel and campaignTotal budget constraints
Identifies diminishing returns and reallocation opportunitiesRisk tolerance for new channels
Models projected outcomes for different allocation scenariosBusiness priorities and brand considerations
Creates monitoring dashboards and alert thresholdsPlatform selection and creative direction

Instructions

Step 1: Audit Current Performance

Collect these metrics per channel and campaign:

MetricFormulaHealthy Range
ROASRevenue ÷ Ad Spend>3:1 for most B2B/B2C
CACAd Spend ÷ New Customers<LTV ÷ 3
CPLAd Spend ÷ LeadsVaries by industry
CTRClicks ÷ Impressions>1% search, >0.5% social
Conv RateConversions ÷ Clicks>2% landing pages

Validation checkpoint: If data is missing for any channel, flag it — incomplete data leads to wrong reallocations.

Step 2: Attribution Analysis

Choose the model that matches the business:

ModelBest ForTrade-off
Last ClickDirect response, short cyclesIgnores awareness
First ClickAwareness campaignsIgnores conversion assist
LinearBalanced multi-touch viewDilutes signal
Time DecayShorter sales cyclesBiases toward bottom-funnel
Position-BasedBalanced with emphasisMay miss mid-funnel
Data-DrivenSophisticated, enough dataRequires volume

Step 3: Calculate Marginal ROI

For each channel, answer: Where does the next $1 produce the most return?

SignalMeaningAction
CAC well below targetHeadroom to scaleIncrease spend 50%, monitor weekly
CAC at targetOptimizedMaintain, test creative
CAC above targetDiminishing returnsReduce spend, reallocate
Low volume, good CACUnderinvestedScale cautiously (2x)
High volume, rising CACHitting ceilingCap spend, diversify

Step 4: Model Reallocation Scenarios

Build 3 scenarios (conservative, moderate, aggressive) showing projected leads, CAC, and ROAS at each budget level. Include:

  • Per-channel breakdowns with expected performance
  • Warning thresholds — CAC levels that trigger spend cuts
  • Implementation timeline — weekly changes, not all at once

Step 5: Implement and Monitor

Weekly monitoring checklist:

  • Spend pacing vs. plan
  • CAC by channel vs. target
  • Lead volume vs. forecast
  • Any channel crossing warning threshold?

Scaling rule: If CAC stays 15%+ below target for 2 consecutive weeks, increase spend by 25%. If CAC exceeds target for 2 weeks, reduce by 25%.

Examples

Example: B2B SaaS Budget Reallocation

Input: $100K/month — Google ($50K), Meta ($30K), LinkedIn ($15K), Other ($5K). Target: $200 CAC, 500 leads/month. Current: 395 leads, $253 CAC.

Diagnosis:

  • Google Display ($15K → 30 leads, $500 CAC) — cut entirely
  • Meta Lookalike ($15K → 85 leads, $176 CAC) — star performer, scale
  • LinkedIn Lead Gen ($5K → 10 leads, $500 CAC) — cut

Proposed reallocation:

ChannelCurrentProposedExpected CAC
Google Ads$50K$35K$206
Meta$30K$50K$196
LinkedIn$15K$8K$286
Testing$5K$7KVariable

Projected result: 473 leads (+20%), $211 CAC (-17%).

Skill Boundaries

What This Skill Does Well

  • Analyzing multi-channel ad performance from provided data
  • Recommending budget shifts based on marginal ROI
  • Modeling reallocation scenarios with projected outcomes
  • Creating monitoring frameworks with alert thresholds

What This Skill Cannot Do

  • Access ad platform accounts or pull live data
  • Make real-time bid adjustments or campaign changes
  • Evaluate creative quality (headlines, images, video)
  • Account for brand lift or offline conversion effects

References

  • Google Ads Optimization Guide
  • Meta Business Suite Best Practices
  • LinkedIn Marketing Solutions
  • Common Thread Collective — ad spend allocation methodology

Related Skills

  • google-ads-expert — Google-specific campaign optimization
  • aarrr-metrics — Full funnel view beyond paid acquisition
  • growth-loops — Sustainable growth beyond paid channels

GitHub Repository

guia-matthieu/clawfu-skills
Path: skills/acquisition/ad-spend-optimizer
0
ai-skillsanthropicclaude-codeclaude-skillsmarketingmcp-server

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