Optimize paid advertising budget allocation across channels using performance data, attribution models, and ROI analysis
Install
npx skillscat add guia-matthieu/clawfu-skills/ad-spend-optimizer Install via the SkillsCat registry.
Ad Spend Optimizer
Systematically optimize paid advertising budget allocation across channels based on performance data, attribution analysis, and ROI targets.
When to Use This Skill
- Quarterly budget planning
- Channel mix optimization
- Performance troubleshooting
- Scaling paid acquisition
- ROI analysis and reporting
Methodology Foundation
Based on marginal ROI optimization and portfolio theory for marketing, combining:
- Channel performance analysis
- Attribution modeling
- Diminishing returns curves
- Test and scale frameworks
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Analyzes channel performance | Budget constraints |
| Calculates ROI by channel | Risk tolerance |
| Recommends allocation shifts | Testing budgets |
| Identifies optimization opportunities | Business priorities |
| Creates performance dashboards | Platform selection |
Instructions
Step 1: Audit Current Performance
Key Metrics by Channel:
| Metric | Definition | Target |
|---|---|---|
| ROAS | Revenue / Ad Spend | >3:1 |
| CAC | Cost to Acquire Customer | <LTV/3 |
| CPA | Cost per Acquisition | Varies |
| CTR | Clicks / Impressions | Benchmark |
| Conv Rate | Conversions / Clicks | Benchmark |
Step 2: Attribution Analysis
Attribution Models:
| Model | Logic | Best For |
|---|---|---|
| Last Click | 100% to final touchpoint | Direct response |
| First Click | 100% to first touchpoint | Awareness campaigns |
| Linear | Equal across all touchpoints | Balanced view |
| Time Decay | More to recent touchpoints | Shorter cycles |
| Position | 40% first, 40% last, 20% middle | Balanced with emphasis |
| Data-Driven | ML-based attribution | Sophisticated analysis |
Step 3: Identify Optimization Opportunities
Optimization Levers:
| Lever | Impact | Effort |
|---|---|---|
| Budget reallocation | High | Low |
| Audience targeting | High | Medium |
| Creative refresh | Medium | Medium |
| Bid optimization | Medium | Low |
| Landing page | High | High |
| New channel test | Variable | Medium |
Step 4: Calculate Optimal Allocation
Marginal ROI Analysis:
- Where is next $1 best spent?
- Identify diminishing returns
- Find underinvested channels
- Balance efficiency vs. scale
Step 5: Implement and Monitor
Test Framework:
- 70% proven channels
- 20% optimization tests
- 10% new channel experiments
Examples
Example 1: Full Budget Optimization
Input:
Optimize this ad spend:
- Monthly budget: $100,000
- Channels: Google Ads (50K), Meta (30K), LinkedIn (15K), Other (5K)
- Goals: B2B SaaS, $200 target CAC, need 500 leads/monthOutput:
## Ad Spend Optimization Analysis
### Current Performance Audit
| Channel | Spend | Leads | CAC | ROAS | CPL |
|---------|-------|-------|-----|------|-----|
| Google Ads | $50,000 | 180 | $278 | 2.1x | $278 |
| Meta | $30,000 | 150 | $200 | 2.8x | $200 |
| LinkedIn | $15,000 | 45 | $333 | 1.5x | $333 |
| Other | $5,000 | 20 | $250 | 2.0x | $250 |
| **Total** | **$100,000** | **395** | **$253** | **2.2x** | **$253** |
**Current Status:**
- Missing target: 395 leads vs 500 goal (79%)
- Above CAC target: $253 vs $200 goal
---
### Channel Analysis
#### Google Ads ($50K)
| Breakdown | Spend | Leads | CAC | Assessment |
|-----------|-------|-------|-----|------------|
| Brand | $10,000 | 80 | $125 | ✅ Efficient |
| Non-Brand | $25,000 | 70 | $357 | ⚠️ High CAC |
| Display | $15,000 | 30 | $500 | ❌ Cut |
**Findings:**
- Brand is highly efficient but limited scale
- Non-brand has high CAC but scalable
- Display not performing—recommend pause
**Recommendations:**
- Increase brand budget (limited by search volume)
- Optimize non-brand (better audiences, negatives)
- Pause display, reallocate to Meta
---
#### Meta ($30K)
| Breakdown | Spend | Leads | CAC | Assessment |
|-----------|-------|-------|-----|------------|
| Lookalike | $15,000 | 85 | $176 | ✅ Best performer |
| Interest | $10,000 | 45 | $222 | ✅ Good |
| Retargeting | $5,000 | 20 | $250 | ✅ Standard |
**Findings:**
- Lookalike audiences are star performers
- Interest targeting has room to scale
- Strong overall channel
**Recommendations:**
- Increase lookalike budget significantly
- Test new lookalike seeds
- Shift underperforming Google budget here
---
#### LinkedIn ($15K)
| Breakdown | Spend | Leads | CAC | Assessment |
|-----------|-------|-------|-----|------------|
| Sponsored Content | $10,000 | 35 | $286 | ⚠️ High |
| Lead Gen Forms | $5,000 | 10 | $500 | ❌ Very high |
**Findings:**
- Highest CAC channel
- But: LinkedIn leads often higher quality (enterprise)
- Lead Gen Forms underperforming
**Recommendations:**
- Reduce overall LinkedIn spend
- Shift to sponsored content only
- Test LinkedIn for enterprise segment specifically
---
#### Other ($5K)
**Breakdown:** Reddit, Quora, programmatic
**Performance:** Mixed, small sample sizes
**Recommendation:** Continue testing but don't scale yet
---
### Recommended Budget Reallocation
#### Before vs After
| Channel | Current | Proposed | Change |
|---------|---------|----------|--------|
| Google Ads | $50,000 | $35,000 | -$15,000 |
| Meta | $30,000 | $50,000 | +$20,000 |
| LinkedIn | $15,000 | $8,000 | -$7,000 |
| Testing | $5,000 | $7,000 | +$2,000 |
| **Total** | **$100,000** | **$100,000** | - |
---
#### Detailed Allocation
**Google Ads ($35K)**
| Campaign | Budget | Expected Leads | Expected CAC |
|----------|--------|----------------|--------------|
| Brand | $12,000 | 95 | $126 |
| Non-Brand (optimized) | $23,000 | 75 | $307 |
| Display | $0 | 0 | - |
| **Total** | **$35,000** | **170** | **$206** |
**Meta ($50K)**
| Campaign | Budget | Expected Leads | Expected CAC |
|----------|--------|----------------|--------------|
| Lookalike | $30,000 | 170 | $176 |
| Interest | $15,000 | 65 | $231 |
| Retargeting | $5,000 | 20 | $250 |
| **Total** | **$50,000** | **255** | **$196** |
**LinkedIn ($8K)**
| Campaign | Budget | Expected Leads | Expected CAC |
|----------|--------|----------------|--------------|
| Sponsored Content | $8,000 | 28 | $286 |
| Lead Gen | $0 | 0 | - |
| **Total** | **$8,000** | **28** | **$286** |
**Testing ($7K)**
| Test | Budget | Purpose |
|------|--------|---------|
| TikTok | $3,000 | New channel |
| YouTube | $2,500 | Video content |
| Reddit (scale) | $1,500 | Community |
---
### Projected Results
| Metric | Current | Proposed | Change |
|--------|---------|----------|--------|
| Total Leads | 395 | 473 | +20% |
| Blended CAC | $253 | $211 | -17% |
| Goal Achievement | 79% | 95% | +16 pts |
| ROAS | 2.2x | 2.6x | +18% |
---
### Implementation Roadmap
**Week 1:**
- [ ] Pause Google Display campaigns
- [ ] Reduce LinkedIn Lead Gen to $0
- [ ] Increase Meta Lookalike by $5K
**Week 2:**
- [ ] Complete Google to Meta shift
- [ ] Launch TikTok test campaign
- [ ] Set up new Lookalike audiences
**Week 3-4:**
- [ ] Monitor and optimize
- [ ] Scale what's working
- [ ] Report on progress
---
### Monitoring Dashboard
┌────────────────────────────────────────────────────────┐
│ AD SPEND DASHBOARD Week 1 │
├────────────────────────────────────────────────────────┤
│ │
│ SPEND PACING │
│ Google: ████████░░░░ $8,200/$8,750 (94%) │
│ Meta: █████████░░░ $11,800/$12,500 (94%) │
│ LinkedIn:██████░░░░░░ $1,500/$2,000 (75%) │
│ Testing: █████░░░░░░░ $900/$1,750 (51%) │
│ │
│ LEADS THIS WEEK │
│ Target: 118 | Actual: 124 | Pacing: +5% │
│ │
│ CAC THIS WEEK │
│ Target: $211 | Actual: $195 | Status: ✅ │
│ │
│ ALERTS: │
│ ⚠️ LinkedIn CPC up 15% - monitor │
│ ✅ Meta Lookalike exceeding expectations │
│ │
└────────────────────────────────────────────────────────┘
Example 2: Quick Channel Assessment
Input:
Should we increase spend on this channel?
- Channel: Facebook
- Current spend: $10K/month
- CAC: $150
- Target CAC: $200
- Leads: 67
- Need: More leadsOutput:
## Channel Scale Assessment: Facebook
### Current Performance
| Metric | Value | Status |
|--------|-------|--------|
| Spend | $10,000 | Baseline |
| Leads | 67 | - |
| CAC | $150 | ✅ Below target |
| Headroom | $50 | Room to scale |
### Scale Recommendation: YES, but carefully
**Why scale:**
- CAC ($150) is 25% below target ($200)
- Indicates efficiency headroom
- Leads are needed
**How to scale:**
| Scenario | Spend | Expected Leads | Expected CAC |
|----------|-------|----------------|--------------|
| Conservative | $15,000 | 90 | $167 |
| Moderate | $20,000 | 110 | $182 |
| Aggressive | $25,000 | 125 | $200 |
**Recommendation:** Start with moderate (+$10K)
### Scaling Checklist
- [ ] Expand Lookalike audiences
- [ ] Test new interest targets
- [ ] Increase frequency caps gradually
- [ ] Monitor CAC weekly
- [ ] Set alert at $185 CAC
### Warning Signs (Stop Scaling)
- CAC exceeds $200
- CTR drops >20%
- Frequency >3.0
- Negative ROI on incrementSkill Boundaries
What This Skill Does Well
- Analyzing channel performance
- Recommending budget shifts
- Calculating ROI projections
- Creating optimization frameworks
What This Skill Cannot Do
- Access your ad accounts
- Make real-time bid changes
- Know your specific creative
- Guarantee performance
Iteration Guide
Follow-up Prompts:
- "Analyze [specific channel] performance"
- "How should we test [new channel]?"
- "Create a pacing dashboard for [budget]"
- "What's causing [performance issue]?"
References
- Google Ads Optimization Guide
- Meta Business Suite Best Practices
- LinkedIn Marketing Solutions
- AdEspresso Budget Allocation
Related Skills
google-ads-expert- Google-specificaarrr-metrics- Full funnel viewgrowth-loops- Sustainable growth
Skill Metadata
- Domain: Acquisition
- Complexity: Intermediate-Advanced
- Mode: centaur
- Time to Value: 2-3 hours per analysis
- Prerequisites: Ad account access, performance data