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Get Started Free →Optimize digital advertising campaigns across Google Ads, Meta Ads, and LINE LAP including bidding strategies, audience targeting, creative testing, and ROAS optimization. Use this skill when the user needs to improve ad performance, reduce CPA, select bidding strategies, or allocate budget across platforms — even if they say 'our ads aren't working', 'reduce our cost per acquisition', 'Google vs Facebook ads', or 'improve our ROAS'.
.claude/skills/asgard-ai-platform-mkt-ad-optimization/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 36% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 33% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 59% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 69% | 0% |
IRON LAW: Optimize for the Business Metric, Not the Ad Metric
High CTR with low conversion = wasted clicks (attracting curiosity, not buyers).
Low CPC with no sales = cheap traffic that doesn't convert.
The only metrics that matter: CPA (Cost Per Acquisition), ROAS (Return On Ad Spend),
and ultimately: profit per ad dollar. Optimize the funnel, not the ad.| Platform | Best For | Audience | Avg CPC (Taiwan) | Targeting Strength | |----------|---------|---------|-----------------|-------------------| | Google Search | High-intent queries, direct response | Active searchers | NT$5-30 | Keyword intent (strongest) | | Google Display | Awareness, retargeting, broad reach | Passive browsing | NT$1-5 | Contextual, audience | | Meta (FB/IG) | Social discovery, visual products, lookalike | Social users | NT$3-15 | Interest, behavior, lookalike | | LINE LAP | Taiwan-specific, broad reach | LINE users (95% Taiwan) | NT$3-20 | Demographics, interests | | YouTube | Video branding, consideration | Video viewers | NT$1-5 (CPV) | Intent, affinity, in-market | | TikTok | Gen Z, viral products, short-form video | Young demographic | NT$2-10 | Interest, behavior |
| Strategy | How It Works | When to Use | |----------|-------------|------------| | Manual CPC | You set max CPC | Learning phase, small budgets, full control | | Target CPA | Algorithm optimizes for target cost per acquisition | 30+ conversions/month, known CPA target | | Target ROAS | Algorithm optimizes for target return on ad spend | E-commerce, known revenue per conversion | | Maximize Conversions | Spend full budget to get max conversions | Growth phase, less concerned about CPA | | Maximize Clicks | Most clicks for budget | Traffic campaigns, awareness |
Phase 1: Audit Current Performance
Phase 2: Quick Wins (Week 1-2)
Phase 3: Structural Improvements (Week 3-4)
Phase 4: Scaling (Month 2+)
| Element | What to Test | Minimum Sample | |---------|-------------|---------------| | Headline | Benefit vs feature, question vs statement | 1,000 impressions each | | Image/Video | Product shot vs lifestyle, static vs video | 1,000 impressions each | | CTA | "Shop Now" vs "Learn More" vs "Get Offer" | 500 clicks each | | Offer | Free shipping vs % discount vs gift | 100 conversions each |
markdown# Ad Optimization Report: {Campaign/Account} ## Performance Summary | Metric | Current | Target | Status | |--------|---------|--------|--------| | Spend | NT${X}/month | — | — | | CPA | NT${X} | NT${X} | 🟢/🟡/🔴 | | ROAS | {X}x | {X}x | 🟢/🟡/🔴 | | CVR | {%} | {%} | 🟢/🟡/🔴 | ## Top Performing | Campaign/Ad | CPA | ROAS | Action | |------------|-----|------|--------| | {name} | NT${X} | {X}x | Scale +20% | ## Underperforming | Campaign/Ad | CPA | Issue | Action | |------------|-----|-------|--------| | {name} | NT${X} | {diagnosis} | Pause/Optimize/Restructure | ## Optimization Plan | Priority | Action | Expected Impact | Timeline | |----------|--------|----------------|----------| | 1 | {action} | CPA -{X%} | {weeks} |
references/google-ads-structure.mdreferences/meta-creative.md| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 28,410 | 23,523 | -17% | 1 | 1 | 0% | 3,910 | 4,964 | +27% | 0 | 0 | — |
case-02 | fail→fail | 38,209 | 17,110 | -55% | 1 | 1 | 0% | 6,093 | 4,118 | -32% | 0 | 0 | — |
case-03 | fail→fail | 51,781 | 16,899 | -67% | 1 | 1 | 0% | 8,268 | 4,178 | -49% | 0 | 0 | — |
case-04 | pass→pass | 13,972 | 15,308 | +10% | 1 | 1 | 0% | 2,212 | 3,509 | +59% | 0 | 0 | — |
case-05 | pass→pass | 11,088 | 11,696 | +5% | 1 | 1 | 0% | 1,877 | 3,166 | +69% | 0 | 0 | — |
case-06 | pass→pass | 13,000 | 12,431 | -4% | 1 | 1 | 0% | 2,226 | 3,314 | +49% | 0 | 0 | — |
case-07 | pass→pass | 10,162 | 6,304 | -38% | 1 | 1 | 0% | 1,724 | 2,409 | +40% | 0 | 0 | — |
case-08 | pass→pass | 12,791 | 24,950 | +95% | 1 | 1 | 0% | 1,925 | 3,442 | +79% | 0 | 0 | — |
case-09 | pass→pass | 11,537 | 9,856 | -15% | 1 | 1 | 0% | 2,022 | 2,934 | +45% | 0 | 0 | — |
case-10 | pass→pass | 10,240 | 13,223 | +29% | 1 | 1 | 0% | 1,850 | 3,254 | +76% | 0 | 0 | — |
case-11 | pass→pass | 13,695 | 12,643 | -8% | 1 | 1 | 0% | 1,891 | 3,409 | +80% | 0 | 0 | — |
case-12 | pass→pass | 11,955 | 13,993 | +17% | 1 | 1 | 0% | 1,926 | 3,281 | +70% | 0 | 0 | — |
case-13 | fail→pass | 20,680 | 16,587 | -20% | 1 | 1 | 0% | 2,858 | 3,899 | +36% | 0 | 0 | — |
case-14 | fail→fail | 15,379 | 17,096 | +11% | 1 | 1 | 0% | 2,227 | 3,771 | +69% | 0 | 0 | — |
case-15 | pass→pass | 15,115 | 10,669 | -29% | 1 | 1 | 0% | 2,516 | 3,071 | +22% | 0 | 0 | — |
case-16 | pass→pass | 14,955 | 18,049 | +21% | 1 | 1 | 0% | 2,440 | 4,363 | +79% | 0 | 0 | — |
case-22 | pass→pass | 13,067 | 13,344 | +2% | 1 | 1 | 0% | 2,216 | 3,577 | +61% | 0 | 0 | — |
case-17 | pass→pass | 14,900 | 16,302 | +9% | 1 | 1 | 0% | 2,581 | 3,825 | +48% | 0 | 0 | — |
case-18 | fail→pass | 12,311 | 9,102 | -26% | 1 | 1 | 0% | 2,231 | 2,978 | +33% | 0 | 0 | — |
case-19 | pass→pass | 17,671 | 13,192 | -25% | 1 | 1 | 0% | 3,131 | 3,642 | +16% | 0 | 0 | — |
case-20 | pass→pass | 16,312 | 17,833 | +9% | 1 | 1 | 0% | 2,376 | 4,010 | +69% | 0 | 0 | — |
case-21 | pass→pass | 30,270 | 35,243 | +16% | 1 | 1 | 0% | 6,930 | 7,670 | +11% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +14 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.