Ad spend optimizer skill
Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC.
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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 |
| $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 optimizationaarrr-metrics— Full funnel view beyond paid acquisitiongrowth-loops— Sustainable growth beyond paid channels
| 1 | |
| 2 | name ad-spend-optimizer |
| 3 | 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." |
| 4 | license MIT |
| 5 | metadata |
| 6 | author ClawFu |
| 7 | version 1.1.0 |
| 8 | mcp-server "@clawfu/mcp-skills" |
| 9 | |
| 10 | |
| 11 | # Ad Spend Optimizer |
| 12 | |
| 13 | > Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. |
| 14 | |
| 15 | ## When to Use This Skill |
| 16 | |
| 17 | **Quarterly budget planning** — reallocate spend based on performance data |
| 18 | **Channel mix optimization** — find the right balance across platforms |
| 19 | **Performance troubleshooting** — diagnose why CAC is rising or ROAS declining |
| 20 | **Scaling decisions** — determine if a channel has headroom to scale |
| 21 | **New channel testing** — structure test budgets with clear success criteria |
| 22 | |
| 23 | ## Methodology Foundation |
| 24 | |
| 25 | | Aspect | Details | |
| 26 | |--------|---------| |
| 27 | | **Source** | Marginal ROI optimization + portfolio theory for marketing | |
| 28 | | **Core Principle** | Allocate each dollar where the marginal return is highest — shift spend from diminishing-returns channels to underspent ones | |
| 29 | | **Framework** | 70/20/10 — 70% proven channels, 20% optimization tests, 10% new channel experiments | |
| 30 | |
| 31 | ## What Claude Does vs What You Decide |
| 32 | |
| 33 | | Claude Does | You Decide | |
| 34 | |-------------|------------| |
| 35 | | Calculates ROAS, CAC, and CPL per channel and campaign | Total budget constraints | |
| 36 | | Identifies diminishing returns and reallocation opportunities | Risk tolerance for new channels | |
| 37 | | Models projected outcomes for different allocation scenarios | Business priorities and brand considerations | |
| 38 | | Creates monitoring dashboards and alert thresholds | Platform selection and creative direction | |
| 39 | |
| 40 | ## Instructions |
| 41 | |
| 42 | ### Step 1: Audit Current Performance |
| 43 | |
| 44 | Collect these metrics per channel and campaign: |
| 45 | |
| 46 | | Metric | Formula | Healthy Range | |
| 47 | |--------|---------|---------------| |
| 48 | | **ROAS** | Revenue ÷ Ad Spend | >3:1 for most B2B/B2C | |
| 49 | | **CAC** | Ad Spend ÷ New Customers | <LTV ÷ 3 | |
| 50 | | **CPL** | Ad Spend ÷ Leads | Varies by industry | |
| 51 | | **CTR** | Clicks ÷ Impressions | >1% search, >0.5% social | |
| 52 | | **Conv Rate** | Conversions ÷ Clicks | >2% landing pages | |
| 53 | |
| 54 | **Validation checkpoint:** If data is missing for any channel, flag it — incomplete data leads to wrong reallocations. |
| 55 | |
| 56 | ### Step 2: Attribution Analysis |
| 57 | |
| 58 | Choose the model that matches the business: |
| 59 | |
| 60 | | Model | Best For | Trade-off | |
| 61 | |-------|----------|-----------| |
| 62 | | Last Click | Direct response, short cycles | Ignores awareness | |
| 63 | | First Click | Awareness campaigns | Ignores conversion assist | |
| 64 | | Linear | Balanced multi-touch view | Dilutes signal | |
| 65 | | Time Decay | Shorter sales cycles | Biases toward bottom-funnel | |
| 66 | | Position-Based | Balanced with emphasis | May miss mid-funnel | |
| 67 | | Data-Driven | Sophisticated, enough data | Requires volume | |
| 68 | |
| 69 | ### Step 3: Calculate Marginal ROI |
| 70 | |
| 71 | For each channel, answer: **Where does the next $1 produce the most return?** |
| 72 | |
| 73 | | Signal | Meaning | Action | |
| 74 | |--------|---------|--------| |
| 75 | | CAC well below target | Headroom to scale | Increase spend 50%, monitor weekly | |
| 76 | | CAC at target | Optimized | Maintain, test creative | |
| 77 | | CAC above target | Diminishing returns | Reduce spend, reallocate | |
| 78 | | Low volume, good CAC | Underinvested | Scale cautiously (2x) | |
| 79 | | High volume, rising CAC | Hitting ceiling | Cap spend, diversify | |
| 80 | |
| 81 | ### Step 4: Model Reallocation Scenarios |
| 82 | |
| 83 | Build 3 scenarios (conservative, moderate, aggressive) showing projected leads, CAC, and ROAS at each budget level. Include: |
| 84 | |
| 85 | **Per-channel breakdowns** with expected performance |
| 86 | **Warning thresholds** — CAC levels that trigger spend cuts |
| 87 | **Implementation timeline** — weekly changes, not all at once |
| 88 | |
| 89 | ### Step 5: Implement and Monitor |
| 90 | |
| 91 | **Weekly monitoring checklist:** |
| 92 | [ ] Spend pacing vs. plan |
| 93 | [ ] CAC by channel vs. target |
| 94 | [ ] Lead volume vs. forecast |
| 95 | [ ] Any channel crossing warning threshold? |
| 96 | |
| 97 | **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%. |
| 98 | |
| 99 | ## Examples |
| 100 | |
| 101 | ### Example: B2B SaaS Budget Reallocation |
| 102 | |
| 103 | **Input:** $100K/month — Google ($50K), Meta ($30K), LinkedIn ($15K), Other ($5K). Target: $200 CAC, 500 leads/month. Current: 395 leads, $253 CAC. |
| 104 | |
| 105 | **Diagnosis:** |
| 106 | Google Display ($15K → 30 leads, $500 CAC) — cut entirely |
| 107 | Meta Lookalike ($15K → 85 leads, $176 CAC) — star performer, scale |
| 108 | LinkedIn Lead Gen ($5K → 10 leads, $500 CAC) — cut |
| 109 | |
| 110 | **Proposed reallocation:** |
| 111 | |
| 112 | | Channel | Current | Proposed | Expected CAC | |
| 113 | |---------|---------|----------|-------------| |
| 114 | | Google Ads | $50K | $35K | $206 | |
| 115 | | Meta | $30K | $50K | $196 | |
| 116 | | LinkedIn | $15K | $8K | $286 | |
| 117 | | Testing | $5K | $7K | Variable | |
| 118 | |
| 119 | **Projected result:** 473 leads (+20%), $211 CAC (-17%). |
| 120 | |
| 121 | ## Skill Boundaries |
| 122 | |
| 123 | ### What This Skill Does Well |
| 124 | Analyzing multi-channel ad performance from provided data |
| 125 | Recommending budget shifts based on marginal ROI |
| 126 | Modeling reallocation scenarios with projected outcomes |
| 127 | Creating monitoring frameworks with alert thresholds |
| 128 | |
| 129 | ### What This Skill Cannot Do |
| 130 | Access ad platform accounts or pull live data |
| 131 | Make real-time bid adjustments or campaign changes |
| 132 | Evaluate creative quality (headlines, images, video) |
| 133 | Account for brand lift or offline conversion effects |
| 134 | |
| 135 | ## References |
| 136 | |
| 137 | Google Ads Optimization Guide |
| 138 | Meta Business Suite Best Practices |
| 139 | LinkedIn Marketing Solutions |
| 140 | Common Thread Collective — ad spend allocation methodology |
| 141 | |
| 142 | ## Related Skills |
| 143 | |
| 144 | `google-ads-expert` — Google-specific campaign optimization |
| 145 | `aarrr-metrics` — Full funnel view beyond paid acquisition |
| 146 | `growth-loops` — Sustainable growth beyond paid channels |
| 147 |
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