ad-spend-optimizer
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npx mdskill add guia-matthieu/clawfu-skills/ad-spend-optimizerOptimizes ad budgets across channels to maximize ROAS and minimize CAC during quarterly planning or performance shifts.
- Helps reallocate spend for quarterly budgets, diagnose underperforming channels, and decide on scaling or testing new channels.
- Integrates with advertising platforms like Google Ads, Meta, LinkedIn, and TikTok for performance analysis.
- Uses marginal ROI optimization and portfolio theory to allocate budgets where returns are highest.
- Presents recommendations through structured frameworks, such as 70/20/10, for budget allocation and test criteria.
SKILL.md
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--- name: ad-spend-optimizer 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." license: MIT metadata: author: ClawFu version: 1.1.0 mcp-server: "@clawfu/mcp-skills" --- # 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
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