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