ad-spend-optimizer

name	ad-spend-optimizer
description	Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use when: planning quarterly ad budget allocation, diagnosing underperforming ad channels, deciding whether to scale spend on a channel, calculating marginal ROI across Google Ads, Meta, LinkedIn, or TikTok, rebalancing media mix after performance shifts, or setting up a test-and-scale framework for new channels.
license	MIT
metadata	{"author":"ClawFu","version":"1.1.0","mcp-server":"@clawfu/mcp-skills"}

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

What Claude Does vs What You Decide

Claude Does	You Decide
Calculates ROAS, CAC, and CPL per channel and campaign	Total budget constraints
Identifies diminishing returns and reallocation opportunities	Risk tolerance for new channels
Models projected outcomes for different allocation scenarios	Business priorities and brand considerations
Creates monitoring dashboards and alert thresholds	Platform selection and creative direction

Instructions

Step 1: Audit Current Performance

Collect these metrics per channel and campaign:

Metric	Formula	Healthy Range
ROAS	Revenue ÷ Ad Spend	>3:1 for most B2B/B2C
CAC	Ad Spend ÷ New Customers	<LTV ÷ 3
CPL	Ad Spend ÷ Leads	Varies by industry
CTR	Clicks ÷ Impressions	>1% search, >0.5% social
Conv Rate	Conversions ÷ 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:

Model	Best For	Trade-off
Last Click	Direct response, short cycles	Ignores awareness
First Click	Awareness campaigns	Ignores conversion assist
Linear	Balanced multi-touch view	Dilutes signal
Time Decay	Shorter sales cycles	Biases toward bottom-funnel
Position-Based	Balanced with emphasis	May miss mid-funnel
Data-Driven	Sophisticated, enough data	Requires volume

Step 3: Calculate Marginal ROI

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

Signal	Meaning	Action
CAC well below target	Headroom to scale	Increase spend 50%, monitor weekly
CAC at target	Optimized	Maintain, test creative
CAC above target	Diminishing returns	Reduce spend, reallocate
Low volume, good CAC	Underinvested	Scale cautiously (2x)
High volume, rising CAC	Hitting ceiling	Cap 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:

Channel	Current	Proposed	Expected CAC
Google Ads	$50K	$35K	$206
Meta	$30K	$50K	$196
LinkedIn	$15K	$8K	$286
Testing	$5K	$7K	Variable

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