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ad-spend-optimizer

Optimize paid advertising budget allocation across channels using performance data, attribution models, and ROI analysis

personAuthor: jakexiaohubgithub
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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 | | 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