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:
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 optimizationaarrr-metrics — Full funnel view beyond paid acquisitiongrowth-loops — Sustainable growth beyond paid channels
1---2name: ad-spend-optimizer3description: 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.4license: MIT5---6
7# Ad Spend Optimizer
8
9> Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC.
10
11## When to Use This Skill
12
13- **Quarterly budget planning** — reallocate spend based on performance data
14- **Channel mix optimization** — find the right balance across platforms
15- **Performance troubleshooting** — diagnose why CAC is rising or ROAS declining
16- **Scaling decisions** — determine if a channel has headroom to scale
17- **New channel testing** — structure test budgets with clear success criteria
18
19## Methodology Foundation
20
21| Aspect | Details |
22|--------|---------|
23| **Source** | Marginal ROI optimization + portfolio theory for marketing |
24| **Core Principle** | Allocate each dollar where the marginal return is highest — shift spend from diminishing-returns channels to underspent ones |
25| **Framework** | 70/20/10 — 70% proven channels, 20% optimization tests, 10% new channel experiments |
26
27## What Claude Does vs What You Decide
28
29| Claude Does | You Decide |
30|-------------|------------|
31| Calculates ROAS, CAC, and CPL per channel and campaign | Total budget constraints |
32| Identifies diminishing returns and reallocation opportunities | Risk tolerance for new channels |
33| Models projected outcomes for different allocation scenarios | Business priorities and brand considerations |
34| Creates monitoring dashboards and alert thresholds | Platform selection and creative direction |
35
36## Instructions
37
38### Step 1: Audit Current Performance
39
40Collect these metrics per channel and campaign:
41
42| Metric | Formula | Healthy Range |
43|--------|---------|---------------|
44| **ROAS** | Revenue ÷ Ad Spend | >3:1 for most B2B/B2C |
45| **CAC** | Ad Spend ÷ New Customers | <LTV ÷ 3 |
46| **CPL** | Ad Spend ÷ Leads | Varies by industry |
47| **CTR** | Clicks ÷ Impressions | >1% search, >0.5% social |
48| **Conv Rate** | Conversions ÷ Clicks | >2% landing pages |
49
50**Validation checkpoint:** If data is missing for any channel, flag it — incomplete data leads to wrong reallocations.
51
52### Step 2: Attribution Analysis
53
54Choose the model that matches the business:
55
56| Model | Best For | Trade-off |
57|-------|----------|-----------|
58| Last Click | Direct response, short cycles | Ignores awareness |
59| First Click | Awareness campaigns | Ignores conversion assist |
60| Linear | Balanced multi-touch view | Dilutes signal |
61| Time Decay | Shorter sales cycles | Biases toward bottom-funnel |
62| Position-Based | Balanced with emphasis | May miss mid-funnel |
63| Data-Driven | Sophisticated, enough data | Requires volume |
64
65### Step 3: Calculate Marginal ROI
66
67For each channel, answer: **Where does the next $1 produce the most return?**
68
69| Signal | Meaning | Action |
70|--------|---------|--------|
71| CAC well below target | Headroom to scale | Increase spend 50%, monitor weekly |
72| CAC at target | Optimized | Maintain, test creative |
73| CAC above target | Diminishing returns | Reduce spend, reallocate |
74| Low volume, good CAC | Underinvested | Scale cautiously (2x) |
75| High volume, rising CAC | Hitting ceiling | Cap spend, diversify |
76
77### Step 4: Model Reallocation Scenarios
78
79Build 3 scenarios (conservative, moderate, aggressive) showing projected leads, CAC, and ROAS at each budget level. Include:
80
81- **Per-channel breakdowns** with expected performance
82- **Warning thresholds** — CAC levels that trigger spend cuts
83- **Implementation timeline** — weekly changes, not all at once
84
85### Step 5: Implement and Monitor
86
87**Weekly monitoring checklist:**
88- [ ] Spend pacing vs. plan
89- [ ] CAC by channel vs. target
90- [ ] Lead volume vs. forecast
91- [ ] Any channel crossing warning threshold?
92
93**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%.
94
95## Examples
96
97### Example: B2B SaaS Budget Reallocation
98
99**Input:** $100K/month — Google ($50K), Meta ($30K), LinkedIn ($15K), Other ($5K). Target: $200 CAC, 500 leads/month. Current: 395 leads, $253 CAC.
100
101**Diagnosis:**
102- Google Display ($15K → 30 leads, $500 CAC) — cut entirely
103- Meta Lookalike ($15K → 85 leads, $176 CAC) — star performer, scale
104- LinkedIn Lead Gen ($5K → 10 leads, $500 CAC) — cut
105
106**Proposed reallocation:**
107
108| Channel | Current | Proposed | Expected CAC |
109|---------|---------|----------|-------------|
110| Google Ads | $50K | $35K | $206 |
111| Meta | $30K | $50K | $196 |
112| LinkedIn | $15K | $8K | $286 |
113| Testing | $5K | $7K | Variable |
114
115**Projected result:** 473 leads (+20%), $211 CAC (-17%).
116
117## Skill Boundaries
118
119### What This Skill Does Well
120- Analyzing multi-channel ad performance from provided data
121- Recommending budget shifts based on marginal ROI
122- Modeling reallocation scenarios with projected outcomes
123- Creating monitoring frameworks with alert thresholds
124
125### What This Skill Cannot Do
126- Access ad platform accounts or pull live data
127- Make real-time bid adjustments or campaign changes
128- Evaluate creative quality (headlines, images, video)
129- Account for brand lift or offline conversion effects
130
131## References
132
133- Google Ads Optimization Guide
134- Meta Business Suite Best Practices
135- LinkedIn Marketing Solutions
136- Common Thread Collective — ad spend allocation methodology
137
138## Related Skills
139
140- `google-ads-expert` — Google-specific campaign optimization
141- `aarrr-metrics` — Full funnel view beyond paid acquisition
142- `growth-loops` — Sustainable growth beyond paid channels
guia-matthieu