[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M718N7WDNSPDX4RWNSMQ2XF8":3,"skill-same:01M718N7WDNSPDX4RWNSMQ2XF8":70},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M718N7WDNSPDX4RWNSMQ2XF8","google-ads-optimizer",null,"Optimize running Google Ads campaigns — bid strategy tuning, budget reallocation, Quality Score improvement, ad copy iteration, audience refinement, placement management, and scaling.","narayan-metaflow\u002Fmetaflow-marketing-skills","narayan-metaflow","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F181216517?v=4","01M718MB0Y27AYKTC9ZKT16V86","narayan","01M718MB209XRYRTS3ZZFK0JXS",19,"MIT","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fgoogle-ads-optimizer\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000040","财务","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"ads","google","google ads optimizer","google ads","optimizer","management","copy","refinement","quality","ad","strategy","campaigns","improvement","running","tuning","Budget","optimize","iteration","scaling","2026-11-10 10:12:30",false,"---\nname: google-ads-optimizer\ndescription: \"Optimize running Google Ads campaigns — bid strategy tuning, budget reallocation, Quality Score improvement, ad copy iteration, audience refinement, placement management, and scaling.\"\n---\n\n## Process\n\n1. **Diagnose** — Identify the specific performance problem (rising CPA, declining ROAS, low impression share, poor Quality Score, etc.)\n2. **Analyze root cause** — Use the Diagnostic Decision Tree to pinpoint the issue\n3. **Select optimization lever** — Match the problem to the right framework below\n4. **Implement changes** — Follow the specific optimization playbook\n5. **Monitor learning phase** — Wait 7-14 days before judging results\n6. **Iterate** — Review, adjust 10-15% incrementally, repeat\n\n## Diagnostic Decision Tree\n\n**What's the primary symptom?**\n\n| Symptom | Most Likely Cause | Start Here |\n|---------|------------------|-----------|\n| CPA rising, conversions stable | Increased competition or bid inflation | Bid Optimization → Budget Reallocation |\n| CPA rising, conversions declining | Tracking issue, audience exhaustion, or creative fatigue | Check tracking first → Audience Refinement |\n| Low impression share (\u003C30%) | Underbidding or budget constraints | Impression Share Analysis |\n| High impression share (>95%) with low ROI | Overspending on low-value queries | Search Term Management → Negative Keywords |\n| Quality Score declining | Landing page, ad relevance, or CTR issues | Quality Score Optimization |\n| Good clicks, low conversion rate | Landing page problem or audience mismatch | Landing Page Optimization |\n| PMax underperforming | Asset quality, audience signals, or budget | PMax Optimization |\n| AI Max volatile | Still in learning or exploring new queries | Wait 7-14 days → review Smart Bidding Exploration |\n\n## Bid Optimization\n\n### Smart Bidding Adjustment Rules\n\n| Scenario | Action | Increment |\n|----------|--------|-----------|\n| CPA consistently below target for 2+ weeks | Lower tCPA target to capture more efficient range | Decrease 10-15% |\n| CPA consistently above target for 2+ weeks | Raise tCPA target (or algorithm delivery collapses) | Increase 10-15% |\n| ROAS above target for 2+ weeks | Lower tROAS target to allow more volume | Decrease 10-15% |\n| ROAS below target for 2+ weeks | Raise tROAS target to tighten efficiency | Increase 10-15% |\n| Campaign in learning phase | **Do nothing.** Wait 7-14 days | No changes |\n| Delivery collapsed (near-zero spend) | Target too aggressive — raise tCPA \u002F lower tROAS | Increase 20-30% to restore delivery |\n\n**Key rules:**\n- Never change targets by more than 15-20% at once (except delivery collapse rescue)\n- Use bid simulators before making changes — forecast the impact\n- Day-of-week and hour-of-day adjustments: analyze 90 days of conversion data, then apply bid modifiers to high\u002Flow performing time slots\n- **ECPC is deprecated (March 2025).** If any campaign is running ECPC, it reverted to Manual CPC. Migrate to Maximize Conversions or tCPA immediately\n\n### Portfolio Bid Strategy Optimization\n\nPortfolio strategies pool data across multiple campaigns for better optimization.\n\n| When to Use | Benefit |\n|------------|---------|\n| Multiple campaigns targeting same conversion | Shared learning = faster optimization |\n| Related campaigns with different budgets | Dynamic reallocation across campaigns |\n| Account-wide ROAS\u002FCPA goal | Unified strategy. Typical lift: 19-27% ROAS improvement |\n\n**Setup:** Create portfolio strategy → assign related campaigns → set shared target → monitor at portfolio level, not individual campaign level.\n\n## Budget Reallocation\n\n### Intra-Account Reallocation Framework\n\n| Step | Action |\n|------|--------|\n| 1. Rank campaigns | Sort by primary KPI (CPA, ROAS, or conversion volume) |\n| 2. Identify donors | Campaigns with CPA > 1.5x target OR ROAS \u003C 50% of target for 30+ days |\n| 3. Identify recipients | Campaigns with CPA \u003C target AND impression share lost to budget > 10% |\n| 4. Shift budget | Move 20% of donor budget to recipients. Monitor for 2 weeks |\n| 5. Repeat | Continue rebalancing every 2-4 weeks |\n\n**Scaling rule:** Increase winning campaign budgets by 20% increments maximum. Larger jumps destabilize Smart Bidding.\n\n**Day-of-week pacing:** Analyze 90 days of conversion data by day of week. If Tuesdays convert 2x better than Saturdays, use dayparting scripts or budget adjustments to concentrate spend on high-converting days.\n\n**For automated budget pacing and redistribution scripts, use the **google-ads-scripts** skill.**\n\n## Impression Share Analysis\n\n| Metric | Threshold | Interpretation | Action |\n|--------|----------|---------------|--------|\n| Search IS | \u003C30% | Significantly underbidding or underfunded | Increase budget or raise bids (if profitable) |\n| Search IS | 30-70% | Room to grow | Evaluate if more spend is profitable before scaling |\n| Search IS | >95% | Dominating — but is it efficient? | If ROI is strong, maintain. If ROI is weak, you're overspending |\n| IS Lost (Budget) | >20% on profitable campaigns | Budget-constrained on winners | Priority budget increase |\n| IS Lost (Rank) | >30% | Ad rank too low | Improve Quality Score or increase bids |\n| Top IS | \u003C50% for brand terms | Competitors above you on your brand | Increase brand campaign bids |\n\n## Quality Score Optimization\n\nQuality Score components, in order of optimization impact:\n\n### 1. Landing Page Experience (widest impact)\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Page speed \u003C3 seconds (GTmetrix \u002F PageSpeed Insights) | Major — Google's 2025 quality system heavily weights navigation ease |\n| Message match: landing page headline mirrors ad headline | High — direct relevance signal |\n| Mobile optimization (responsive, thumb-friendly, no pop-ups) | High — mobile-first indexing active |\n| Relevant content depth (not thin landing pages) | Medium |\n| Clear CTA above the fold | Medium |\n| Trust signals (testimonials, badges, reviews) | Medium |\n\n### 2. Ad Relevance\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Tighten ad group themes (5-15 related keywords per group) | High |\n| Write intent-specific headlines matching the keyword theme | High |\n| Use keyword insertion in headlines (where natural) | Medium |\n| Create separate ad groups for distinct intent clusters | High |\n\n### 3. Expected CTR\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Add negative keywords to filter irrelevant impressions | High (removes low-CTR impressions) |\n| Test new headline angles emphasizing benefits and CTAs | Medium |\n| Add extensions (sitelinks, callouts increase ad real estate → CTR) | Medium |\n| Improve ad position (higher position → higher CTR, but check ROI) | Low-Medium |\n\n**QS impact on CPC:** Moving Quality Score from 4 to 6 typically reduces CPC by 15-25%. From 6 to 8 reduces another 10-15%. Compounding effect is significant at scale.\n\n## Ad Copy Iteration\n\n### RSA Asset Performance Review\n\nUse Google's 2025 asset-level reporting:\n\n| Asset Rating | Action |\n|-------------|--------|\n| **Best** | Keep. This is a proven winner. Don't change it |\n| **Good** | Maintain but consider testing alternatives |\n| **Low** | Replace with new variation. Test a different angle |\n| **Unrated** | Needs more data. Wait for significance |\n\n**Replacement strategy:**\n1. Review asset ratings monthly\n2. Replace 2-3 \"Low\" rated headlines per RSA\n3. Keep at least 5 \"Best\" or \"Good\" headlines stable\n4. Test new messaging angles: different benefit, different proof point, different CTA\n5. Isolate one variable per test cycle\n\n**Ad copy testing areas:**\n- Value propositions (speed vs cost vs quality vs convenience)\n- Social proof styles (numbers, names, ratings)\n- CTA types (demo vs trial vs quote vs buy)\n- Emotional vs rational appeals\n- Price inclusion vs exclusion\n\nRead `references\u002Frsa-copy-guide.md` in the **google-ads-campaign-builder** skill for headline frameworks.\n\n## Audience Optimization\n\n| Action | When |\n|--------|------|\n| Refresh remarketing lists | Lists approaching expiration or audience size dropping |\n| Upload new customer match lists | Monthly CRM sync minimum |\n| Test new in-market segments | Performance plateau — need new audience pools |\n| Expand custom intent audiences | Add new URLs and search terms based on converting queries |\n| Switch observation → targeting | Audience segment shows strong performance in observation mode |\n| Remove underperforming segments | Audience with high spend, zero conversions for 30+ days |\n| Add audience signals to PMax | Missing signals = slower PMax learning |\n\n## Placement & Channel Optimization\n\n### PMax Channel Review (2025)\n\nUse PMax channel performance reports to assess where budget is going:\n\n| Channel | Healthy Signal | Problem Signal |\n|---------|---------------|---------------|\n| Search | Converting at or below tCPA | Queries irrelevant — add negatives |\n| Shopping | Product-level conversions visible | Underperforming products need feed optimization |\n| YouTube | Assists showing in conversion paths | Clicks but zero conversions — improve video assets |\n| Display | Remarketing conversions | Low-quality placements — review placement reports |\n| Discover\u002FGmail | Engagement leading to conversions | High impressions, no conversions — creative issue |\n\n**PMax negatives (January 2025):** Use campaign-level negative keywords to block irrelevant Search queries. Also add exact-match keywords in Search campaigns to control which campaign serves on high-value queries.\n\n### Display Placement Hygiene\n\n- Review placement report monthly\n- Exclude low-quality sites, mobile apps, and gaming apps\n- Use third-party exclusion lists: DoubleVerify, IAS, Zefr (expanded for PMax in 2025)\n- Exclude sensitive content categories\n\n## Landing Page Optimization\n\n| Test | Method | Priority |\n|------|--------|----------|\n| Headlines | A\u002FB test headline messaging (match winning ad copy) | High |\n| CTA button | Text, color, placement, size | High |\n| Form length | Fewer fields vs more qualified leads | High (lead gen) |\n| Social proof | Type, placement, volume of testimonials | Medium |\n| Page layout | Long-form vs short-form, single-column vs multi | Medium |\n| Mobile experience | Mobile-specific design, thumb-friendly buttons | High |\n\n**Message match audit:** After changing ad copy, always check that the landing page still matches the new message. Mismatched message = high bounce rate = lower Quality Score.\n\n**Speed target:** \u003C3 seconds load time. Re-test monthly. Use GTmetrix or Google PageSpeed Insights.\n\n## Scaling Playbook\n\n| Phase | Timing | Action |\n|-------|--------|--------|\n| **Peak window** | Days 7-14 post-launch | Algorithm has data but creative isn't fatigued. Best time to scale |\n| **Budget increase** | When CPA \u003C target for 2+ weeks | Increase by 20% max. Monitor for 1-2 weeks |\n| **New ad groups** | When current groups saturated | Expand keyword themes based on search term mining |\n| **Campaign experiments** | For aggressive tests | Google Campaign Experiments: 50\u002F50 split without risking main campaign |\n| **New campaign types** | When ready for full-funnel | Add Demand Gen (awareness) and PMax (full-funnel) per Power Pack strategy |\n\n**AI Max for Search scaling:** Monitor Smart Bidding Exploration for new query categories being discovered. If AI Max is finding converting queries that standard Search misses, consider shifting more budget to AI Max. Learning phase: 7-14 days.\n\n## Output Format\n\n```\n## Google Ads Optimization Plan\n\n### Current Performance Summary\n| Metric | Current | Target | Gap |\n|--------|---------|--------|-----|\n| CPA | $[X] | $[X] | [+\u002F-X%] |\n| ROAS | [X]x | [X]x | [+\u002F-X%] |\n| Impression Share | [X]% | [X]% | [gap] |\n\n### Optimization Actions (ICE-prioritized)\n| Priority | Action | Lever | ICE Score | Timeline |\n|----------|--------|-------|-----------|----------|\n| 1 | [action] | [bid\u002Fbudget\u002FQS\u002Fetc] | [score] | [when] |\n\n### Changes to Implement\n[Specific changes with exact values]\n\n### Monitoring Plan\n- Check [metric] after [X] days\n- Success criteria: [what good looks like]\n- Rollback plan: [if it doesn't work]\n```\n\n## Example\n\n**Input:** \"My Google Ads CPA went from $85 to $140 over 6 weeks. I'm spending $12K\u002Fmonth across 3 Search campaigns and 1 PMax campaign. ROAS dropped from 5.2x to 3.1x. tROAS is set at 500%. What should I do?\"\n\n**Output:**\n\n## Google Ads Optimization Plan\n\n### Current Performance Summary\n| Metric | Current | Target | Gap |\n|--------|---------|--------|-----|\n| CPA | $140 | $85 | +65% above target |\n| ROAS | 3.1x | 5.0x | -38% below target |\n| Monthly spend | $12,000 | $12,000 | On budget |\n\n### Root Cause Analysis\nWith tROAS set at 500% but actual ROAS at 310%, the algorithm is likely throttling delivery to try to hit an unrealistic target. This creates a death spiral: less data → worse optimization → worse performance → algorithm throttles more.\n\n### Optimization Actions\n| Priority | Action | Lever | ICE Score | Timeline |\n|----------|--------|-------|-----------|----------|\n| 1 | Lower tROAS from 500% to 350% (current actual + 10% buffer) | Bid | 9×9×10 = 810 | Day 1 |\n| 2 | Run n-gram analysis on search terms — find and negate $50+ zero-conversion terms | Keywords | 9×8×9 = 648 | Day 1-3 |\n| 3 | Review PMax channel performance — identify underperforming channels | Channel | 7×7×8 = 392 | Week 1 |\n| 4 | Refresh RSA copy — replace \"Low\" rated assets | Creative | 6×6×7 = 252 | Week 2 |\n| 5 | Test portfolio bid strategy across 3 Search campaigns | Bid | 7×6×6 = 252 | Week 2 |\n| 6 | Landing page speed audit + message match review | QS | 6×7×5 = 210 | Week 2-3 |\n\n### Changes to Implement\n1. **tROAS adjustment:** Lower from 500% to 350% immediately. This matches actual performance with a 10% improvement buffer. Algorithm can deliver here. After 2 weeks at stable delivery, tighten by 10-15% increments toward 400%.\n2. **Search term cleanup:** Export 90-day search term report. Run n-gram analysis. Flag n-grams with $50+ spend and 0 conversions. Based on typical accounts at this spend level, expect to find $1,000-2,000\u002Fmonth in waste.\n3. **PMax channel audit:** Pull channel performance reports (2025 feature). If YouTube is consuming 30%+ of PMax budget with no conversions, create more targeted video assets or add negative keywords to block irrelevant Search queries in PMax.\n4. **Portfolio bid strategy:** Consolidate 3 Search campaigns into a portfolio strategy with shared tROAS. Typical improvement: 19-27% ROAS lift from dynamic cross-campaign reallocation.\n\n### Monitoring Plan\n- **Day 7:** Check if tROAS reduction restored delivery volume. Expect CPA to initially be above target — that's OK. Volume recovery matters first\n- **Day 14:** Evaluate CPA trend. Should be declining toward $100-120 range\n- **Day 21:** If stable, tighten tROAS by 10% (350% → 385%)\n- **Success criteria:** CPA below $110 within 30 days, ROAS above 3.8x\n- **Rollback:** If delivery collapses further after tROAS change, drop to Maximize Conversion Value (no target) for 2 weeks to accumulate data, then reintroduce tROAS target\n\n## Guidelines\n\n- **Don't change bid targets by more than 15-20% at once.** Gradual adjustments let the algorithm adapt. Exception: delivery collapse rescue (increase 20-30%).\n- **Don't touch campaigns during learning phase.** 7-14 days. Performance will fluctuate. Premature changes reset learning and waste the data collection period.\n- **Don't ignore the tROAS\u002FtCPA death spiral.** If targets are set above actual performance, the algorithm throttles delivery, gets less data, and performs worse. Always set targets at or slightly above current performance, then tighten gradually.\n- **Don't optimize on fractional conversions.** Data-driven attribution creates fractions. Filter to > 1 conversion before evaluating keyword or ad group CPA.\n- **Don't skip search term review.** Even with Smart Bidding, irrelevant queries waste budget. Weekly for new campaigns, bi-weekly for stable ones.\n- **ECPC is gone (March 2025).** Any campaign still on ECPC reverted to Manual CPC. Migrate immediately to Maximize Conversions or tCPA.\n- **AI Max needs patience (September 2025).** Smart Bidding Exploration tests new query categories. Initial volatility is expected. Monitor but don't intervene for 7-14 days.\n- **PMax now has transparency (2025).** Campaign-level negatives, full search term reporting, and channel performance reports. Use them before declaring PMax doesn't work.\n- **Cross-references:** For full account diagnostic, use the **google-ads-audit** skill. For keyword research and n-gram analysis, use the **google-ads-keyword-engine** skill. For automation scripts (budget pacing, anomaly detection, n-gram), use the **google-ads-scripts** skill. For Meta optimization, use the **meta-ads-optimizer** skill. For cross-channel budget allocation, use the **ad-spend-allocator** skill.\n- **Confidence:** Bid simulator forecasts are directional, not guarantees. The 19-27% ROAS improvement from portfolio strategies is a Google benchmark — results vary by account. Always set rollback criteria before making major changes.\n","## Process\n\n1. **Diagnose** — Identify the specific performance problem (rising CPA, declining ROAS, low impression share, poor Quality Score, etc.)\n2. **Analyze root cause** — Use the Diagnostic Decision Tree to pinpoint the issue\n3. **Select optimization lever** — Match the problem to the right framework below\n4. **Implement changes** — Follow the specific optimization playbook\n5. **Monitor learning phase** — Wait 7-14 days before judging results\n6. **Iterate** — Review, adjust 10-15% incrementally, repeat\n\n## Diagnostic Decision Tree\n\n**What's the primary symptom?**\n\n| Symptom | Most Likely Cause | Start Here |\n|---------|------------------|-----------|\n| CPA rising, conversions stable | Increased competition or bid inflation | Bid Optimization → Budget Reallocation |\n| CPA rising, conversions declining | Tracking issue, audience exhaustion, or creative fatigue | Check tracking first → Audience Refinement |\n| Low impression share (\u003C30%) | Underbidding or budget constraints | Impression Share Analysis |\n| High impression share (>95%) with low ROI | Overspending on low-value queries | Search Term Management → Negative Keywords |\n| Quality Score declining | Landing page, ad relevance, or CTR issues | Quality Score Optimization |\n| Good clicks, low conversion rate | Landing page problem or audience mismatch | Landing Page Optimization |\n| PMax underperforming | Asset quality, audience signals, or budget | PMax Optimization |\n| AI Max volatile | Still in learning or exploring new queries | Wait 7-14 days → review Smart Bidding Exploration |\n\n## Bid Optimization\n\n### Smart Bidding Adjustment Rules\n\n| Scenario | Action | Increment |\n|----------|--------|-----------|\n| CPA consistently below target for 2+ weeks | Lower tCPA target to capture more efficient range | Decrease 10-15% |\n| CPA consistently above target for 2+ weeks | Raise tCPA target (or algorithm delivery collapses) | Increase 10-15% |\n| ROAS above target for 2+ weeks | Lower tROAS target to allow more volume | Decrease 10-15% |\n| ROAS below target for 2+ weeks | Raise tROAS target to tighten efficiency | Increase 10-15% |\n| Campaign in learning phase | **Do nothing.** Wait 7-14 days | No changes |\n| Delivery collapsed (near-zero spend) | Target too aggressive — raise tCPA \u002F lower tROAS | Increase 20-30% to restore delivery |\n\n**Key rules:**\n- Never change targets by more than 15-20% at once (except delivery collapse rescue)\n- Use bid simulators before making changes — forecast the impact\n- Day-of-week and hour-of-day adjustments: analyze 90 days of conversion data, then apply bid modifiers to high\u002Flow performing time slots\n- **ECPC is deprecated (March 2025).** If any campaign is running ECPC, it reverted to Manual CPC. Migrate to Maximize Conversions or tCPA immediately\n\n### Portfolio Bid Strategy Optimization\n\nPortfolio strategies pool data across multiple campaigns for better optimization.\n\n| When to Use | Benefit |\n|------------|---------|\n| Multiple campaigns targeting same conversion | Shared learning = faster optimization |\n| Related campaigns with different budgets | Dynamic reallocation across campaigns |\n| Account-wide ROAS\u002FCPA goal | Unified strategy. Typical lift: 19-27% ROAS improvement |\n\n**Setup:** Create portfolio strategy → assign related campaigns → set shared target → monitor at portfolio level, not individual campaign level.\n\n## Budget Reallocation\n\n### Intra-Account Reallocation Framework\n\n| Step | Action |\n|------|--------|\n| 1. Rank campaigns | Sort by primary KPI (CPA, ROAS, or conversion volume) |\n| 2. Identify donors | Campaigns with CPA > 1.5x target OR ROAS \u003C 50% of target for 30+ days |\n| 3. Identify recipients | Campaigns with CPA \u003C target AND impression share lost to budget > 10% |\n| 4. Shift budget | Move 20% of donor budget to recipients. Monitor for 2 weeks |\n| 5. Repeat | Continue rebalancing every 2-4 weeks |\n\n**Scaling rule:** Increase winning campaign budgets by 20% increments maximum. Larger jumps destabilize Smart Bidding.\n\n**Day-of-week pacing:** Analyze 90 days of conversion data by day of week. If Tuesdays convert 2x better than Saturdays, use dayparting scripts or budget adjustments to concentrate spend on high-converting days.\n\n**For automated budget pacing and redistribution scripts, use the **google-ads-scripts** skill.**\n\n## Impression Share Analysis\n\n| Metric | Threshold | Interpretation | Action |\n|--------|----------|---------------|--------|\n| Search IS | \u003C30% | Significantly underbidding or underfunded | Increase budget or raise bids (if profitable) |\n| Search IS | 30-70% | Room to grow | Evaluate if more spend is profitable before scaling |\n| Search IS | >95% | Dominating — but is it efficient? | If ROI is strong, maintain. If ROI is weak, you're overspending |\n| IS Lost (Budget) | >20% on profitable campaigns | Budget-constrained on winners | Priority budget increase |\n| IS Lost (Rank) | >30% | Ad rank too low | Improve Quality Score or increase bids |\n| Top IS | \u003C50% for brand terms | Competitors above you on your brand | Increase brand campaign bids |\n\n## Quality Score Optimization\n\nQuality Score components, in order of optimization impact:\n\n### 1. Landing Page Experience (widest impact)\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Page speed \u003C3 seconds (GTmetrix \u002F PageSpeed Insights) | Major — Google's 2025 quality system heavily weights navigation ease |\n| Message match: landing page headline mirrors ad headline | High — direct relevance signal |\n| Mobile optimization (responsive, thumb-friendly, no pop-ups) | High — mobile-first indexing active |\n| Relevant content depth (not thin landing pages) | Medium |\n| Clear CTA above the fold | Medium |\n| Trust signals (testimonials, badges, reviews) | Medium |\n\n### 2. Ad Relevance\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Tighten ad group themes (5-15 related keywords per group) | High |\n| Write intent-specific headlines matching the keyword theme | High |\n| Use keyword insertion in headlines (where natural) | Medium |\n| Create separate ad groups for distinct intent clusters | High |\n\n### 3. Expected CTR\n\n| Fix | Expected Impact |\n|-----|----------------|\n| Add negative keywords to filter irrelevant impressions | High (removes low-CTR impressions) |\n| Test new headline angles emphasizing benefits and CTAs | Medium |\n| Add extensions (sitelinks, callouts increase ad real estate → CTR) | Medium |\n| Improve ad position (higher position → higher CTR, but check ROI) | Low-Medium |\n\n**QS impact on CPC:** Moving Quality Score from 4 to 6 typically reduces CPC by 15-25%. From 6 to 8 reduces another 10-15%. Compounding effect is significant at scale.\n\n## Ad Copy Iteration\n\n### RSA Asset Performance Review\n\nUse Google's 2025 asset-level reporting:\n\n| Asset Rating | Action |\n|-------------|--------|\n| **Best** | Keep. This is a proven winner. Don't change it |\n| **Good** | Maintain but consider testing alternatives |\n| **Low** | Replace with new variation. Test a different angle |\n| **Unrated** | Needs more data. Wait for significance |\n\n**Replacement strategy:**\n1. Review asset ratings monthly\n2. Replace 2-3 \"Low\" rated headlines per RSA\n3. Keep at least 5 \"Best\" or \"Good\" headlines stable\n4. Test new messaging angles: different benefit, different proof point, different CTA\n5. Isolate one variable per test cycle\n\n**Ad copy testing areas:**\n- Value propositions (speed vs cost vs quality vs convenience)\n- Social proof styles (numbers, names, ratings)\n- CTA types (demo vs trial vs quote vs buy)\n- Emotional vs rational appeals\n- Price inclusion vs exclusion\n\nRead `references\u002Frsa-copy-guide.md` in the **google-ads-campaign-builder** skill for headline frameworks.\n\n## Audience Optimization\n\n| Action | When |\n|--------|------|\n| Refresh remarketing lists | Lists approaching expiration or audience size dropping |\n| Upload new customer match lists | Monthly CRM sync minimum |\n| Test new in-market segments | Performance plateau — need new audience pools |\n| Expand custom intent audiences | Add new URLs and search terms based on converting queries |\n| Switch observation → targeting | Audience segment shows strong performance in observation mode |\n| Remove underperforming segments | Audience with high spend, zero conversions for 30+ days |\n| Add audience signals to PMax | Missing signals = slower PMax learning |\n\n## Placement & Channel Optimization\n\n### PMax Channel Review (2025)\n\nUse PMax channel performance reports to assess where budget is going:\n\n| Channel | Healthy Signal | Problem Signal |\n|---------|---------------|---------------|\n| Search | Converting at or below tCPA | Queries irrelevant — add negatives |\n| Shopping | Product-level conversions visible | Underperforming products need feed optimization |\n| YouTube | Assists showing in conversion paths | Clicks but zero conversions — improve video assets |\n| Display | Remarketing conversions | Low-quality placements — review placement reports |\n| Discover\u002FGmail | Engagement leading to conversions | High impressions, no conversions — creative issue |\n\n**PMax negatives (January 2025):** Use campaign-level negative keywords to block irrelevant Search queries. Also add exact-match keywords in Search campaigns to control which campaign serves on high-value queries.\n\n### Display Placement Hygiene\n\n- Review placement report monthly\n- Exclude low-quality sites, mobile apps, and gaming apps\n- Use third-party exclusion lists: DoubleVerify, IAS, Zefr (expanded for PMax in 2025)\n- Exclude sensitive content categories\n\n## Landing Page Optimization\n\n| Test | Method | Priority |\n|------|--------|----------|\n| Headlines | A\u002FB test headline messaging (match winning ad copy) | High |\n| CTA button | Text, color, placement, size | High |\n| Form length | Fewer fields vs more qualified leads | High (lead gen) |\n| Social proof | Type, placement, volume of testimonials | Medium |\n| Page layout | Long-form vs short-form, single-column vs multi | Medium |\n| Mobile experience | Mobile-specific design, thumb-friendly buttons | High |\n\n**Message match audit:** After changing ad copy, always check that the landing page still matches the new message. Mismatched message = high bounce rate = lower Quality Score.\n\n**Speed target:** \u003C3 seconds load time. Re-test monthly. Use GTmetrix or Google PageSpeed Insights.\n\n## Scaling Playbook\n\n| Phase | Timing | Action |\n|-------|--------|--------|\n| **Peak window** | Days 7-14 post-launch | Algorithm has data but creative isn't fatigued. Best time to scale |\n| **Budget increase** | When CPA \u003C target for 2+ weeks | Increase by 20% max. Monitor for 1-2 weeks |\n| **New ad groups** | When current groups saturated | Expand keyword themes based on search term mining |\n| **Campaign experiments** | For aggressive tests | Google Campaign Experiments: 50\u002F50 split without risking main campaign |\n| **New campaign types** | When ready for full-funnel | Add Demand Gen (awareness) and PMax (full-funnel) per Power Pack strategy |\n\n**AI Max for Search scaling:** Monitor Smart Bidding Exploration for new query categories being discovered. If AI Max is finding converting queries that standard Search misses, consider shifting more budget to AI Max. Learning phase: 7-14 days.\n\n## Output Format\n\n```\n## Google Ads Optimization Plan\n\n### Current Performance Summary\n| Metric | Current | Target | Gap |\n|--------|---------|--------|-----|\n| CPA | $[X] | $[X] | [+\u002F-X%] |\n| ROAS | [X]x | [X]x | [+\u002F-X%] |\n| Impression Share | [X]% | [X]% | [gap] |\n\n### Optimization Actions (ICE-prioritized)\n| Priority | Action | Lever | ICE Score | Timeline |\n|----------|--------|-------|-----------|----------|\n| 1 | [action] | [bid\u002Fbudget\u002FQS\u002Fetc] | [score] | [when] |\n\n### Changes to Implement\n[Specific changes with exact values]\n\n### Monitoring Plan\n- Check [metric] after [X] days\n- Success criteria: [what good looks like]\n- Rollback plan: [if it doesn't work]\n```\n\n## Example\n\n**Input:** \"My Google Ads CPA went from $85 to $140 over 6 weeks. I'm spending $12K\u002Fmonth across 3 Search campaigns and 1 PMax campaign. ROAS dropped from 5.2x to 3.1x. tROAS is set at 500%. What should I do?\"\n\n**Output:**\n\n## Google Ads Optimization Plan\n\n### Current Performance Summary\n| Metric | Current | Target | Gap |\n|--------|---------|--------|-----|\n| CPA | $140 | $85 | +65% above target |\n| ROAS | 3.1x | 5.0x | -38% below target |\n| Monthly spend | $12,000 | $12,000 | On budget |\n\n### Root Cause Analysis\nWith tROAS set at 500% but actual ROAS at 310%, the algorithm is likely throttling delivery to try to hit an unrealistic target. This creates a death spiral: less data → worse optimization → worse performance → algorithm throttles more.\n\n### Optimization Actions\n| Priority | Action | Lever | ICE Score | Timeline |\n|----------|--------|-------|-----------|----------|\n| 1 | Lower tROAS from 500% to 350% (current actual + 10% buffer) | Bid | 9×9×10 = 810 | Day 1 |\n| 2 | Run n-gram analysis on search terms — find and negate $50+ zero-conversion terms | Keywords | 9×8×9 = 648 | Day 1-3 |\n| 3 | Review PMax channel performance — identify underperforming channels | Channel | 7×7×8 = 392 | Week 1 |\n| 4 | Refresh RSA copy — replace \"Low\" rated assets | Creative | 6×6×7 = 252 | Week 2 |\n| 5 | Test portfolio bid strategy across 3 Search campaigns | Bid | 7×6×6 = 252 | Week 2 |\n| 6 | Landing page speed audit + message match review | QS | 6×7×5 = 210 | Week 2-3 |\n\n### Changes to Implement\n1. **tROAS adjustment:** Lower from 500% to 350% immediately. This matches actual performance with a 10% improvement buffer. Algorithm can deliver here. After 2 weeks at stable delivery, tighten by 10-15% increments toward 400%.\n2. **Search term cleanup:** Export 90-day search term report. Run n-gram analysis. Flag n-grams with $50+ spend and 0 conversions. Based on typical accounts at this spend level, expect to find $1,000-2,000\u002Fmonth in waste.\n3. **PMax channel audit:** Pull channel performance reports (2025 feature). If YouTube is consuming 30%+ of PMax budget with no conversions, create more targeted video assets or add negative keywords to block irrelevant Search queries in PMax.\n4. **Portfolio bid strategy:** Consolidate 3 Search campaigns into a portfolio strategy with shared tROAS. Typical improvement: 19-27% ROAS lift from dynamic cross-campaign reallocation.\n\n### Monitoring Plan\n- **Day 7:** Check if tROAS reduction restored delivery volume. Expect CPA to initially be above target — that's OK. Volume recovery matters first\n- **Day 14:** Evaluate CPA trend. Should be declining toward $100-120 range\n- **Day 21:** If stable, tighten tROAS by 10% (350% → 385%)\n- **Success criteria:** CPA below $110 within 30 days, ROAS above 3.8x\n- **Rollback:** If delivery collapses further after tROAS change, drop to Maximize Conversion Value (no target) for 2 weeks to accumulate data, then reintroduce tROAS target\n\n## Guidelines\n\n- **Don't change bid targets by more than 15-20% at once.** Gradual adjustments let the algorithm adapt. Exception: delivery collapse rescue (increase 20-30%).\n- **Don't touch campaigns during learning phase.** 7-14 days. Performance will fluctuate. Premature changes reset learning and waste the data collection period.\n- **Don't ignore the tROAS\u002FtCPA death spiral.** If targets are set above actual performance, the algorithm throttles delivery, gets less data, and performs worse. Always set targets at or slightly above current performance, then tighten gradually.\n- **Don't optimize on fractional conversions.** Data-driven attribution creates fractions. Filter to > 1 conversion before evaluating keyword or ad group CPA.\n- **Don't skip search term review.** Even with Smart Bidding, irrelevant queries waste budget. Weekly for new campaigns, bi-weekly for stable ones.\n- **ECPC is gone (March 2025).** Any campaign still on ECPC reverted to Manual CPC. Migrate immediately to Maximize Conversions or tCPA.\n- **AI Max needs patience (September 2025).** Smart Bidding Exploration tests new query categories. Initial volatility is expected. Monitor but don't intervene for 7-14 days.\n- **PMax now has transparency (2025).** Campaign-level negatives, full search term reporting, and channel performance reports. Use them before declaring PMax doesn't work.\n- **Cross-references:** For full account diagnostic, use the **google-ads-audit** skill. For keyword research and n-gram analysis, use the **google-ads-keyword-engine** skill. For automation scripts (budget pacing, anomaly detection, n-gram), use the **google-ads-scripts** skill. For Meta optimization, use the **meta-ads-optimizer** skill. For cross-channel budget allocation, use the **ad-spend-allocator** skill.\n- **Confidence:** Bid simulator forecasts are directional, not guarantees. The 19-27% ROAS improvement from portfolio strategies is a Google benchmark — results vary by account. Always set rollback criteria before making major changes.\n",{"name":5,"description":7},"main","c137446804eb85b2cc0ba009c62068253a7c47be","skills\u002Fgoogle-ads-optimizer",2,"https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow","engineer by education, marketer by profession, building rn","2026-09-16 13:41:44",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add narayan-metaflow\u002Fmetaflow-marketing-skills --skill google-ads-optimizer",{"tool":62,"command":63},"bunx","bunx skills add narayan-metaflow\u002Fmetaflow-marketing-skills --skill google-ads-optimizer",{"tool":65,"command":66},"pnpm","pnpm dlx skills add narayan-metaflow\u002Fmetaflow-marketing-skills --skill google-ads-optimizer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fgoogle-ads-optimizer\u002FSKILL.md",true,[],[71,103,132,153,182,209],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":85,"publishedAt":43},"01M718Q16XB7D7ZMGNNA1226G5","technical-seo-ai-crawler-audit","Diagnose and prioritize the technical issues blocking a site from being crawled, indexed, ranked, and cited. Modern technical SEO has two audiences: Google's crawler\u002Findexer and AI answer engines (GPTBot, PerplexityBot, ClaudeBot, etc.). Both need HTML-visible content and a clean crawl path.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Ftechnical-seo-ai-crawler-audit\u002FSKILL.md",[77,82],{"categoryNo":78,"categoryName":79,"taxonomyType":80,"taxonomyTypeDesc":81},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000035","市场营销",[86,87,88,89,90,91,92,93,94,95,96,97,25,98,99,100,101,102],"seo","technical","technical seo","technical seo ai crawler audit","audit","crawler","crawl","diagnose","answer","issues","clean","indexer","prioritize","site","content","html","path",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":114,"publishedAt":43},"01M718PY2PKA7BYS5KNJ2A9DRT","seo-reporting-measurement","Build reports that stakeholders trust, rooted in data sources that are actually reliable. Modern SEO measurement has to reckon with a very specific constraint: **the primary data source (GSC) is ~75% incomplete**, and the AI visibility layer is **probabilistic**, not deterministic. Building reports that ignore these realities produces false confidence.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fseo-reporting-measurement\u002FSKILL.md",[109,110,113],{"categoryNo":78,"categoryName":79,"taxonomyType":80,"taxonomyTypeDesc":81},{"categoryNo":111,"categoryName":112,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师",{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},[115,116,117,118,86,119,120,121,122,123,124,125,126,127,128,129,130,131],"seo reporting","seo reporting measurement","reporting","measurement","sources","gsc","false","reports","data sources","data","layer","source","deterministic","trust","with","build","constraint",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":140,"publishedAt":43},"01M718PVF0SP35J6S9EHRGQZQ1","seo-max-kt","Long-form SEO and AEO methodology bundle; read SEO_AND_AEO_KT.md for the full corpus.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fseo-max-kt\u002FSKILL.md",[138,139],{"categoryNo":78,"categoryName":79,"taxonomyType":80,"taxonomyTypeDesc":81},{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},[141,86,142,143,144,145,146,147,148,149,150,151,152],"kt","seo max kt","max","aeo","long-form","methodology","form","for","bundle","full","read","long",{"skillNo":154,"name":155,"nameZh":6,"description":156,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":157,"categories":158,"keywords":164,"publishedAt":43},"01M718PRQNX2JF71GBFTH3MV19","seo-keyword-research-intent-mapping","Build a keyword universe that reflects how both humans *and* AI answer engines search. Traditional keyword research looks at standalone terms; modern research also maps the **fan-out sub-queries** AI tools generate when breaking down a user prompt.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fseo-keyword-research-intent-mapping\u002FSKILL.md",[159,160,163],{"categoryNo":78,"categoryName":79,"taxonomyType":80,"taxonomyTypeDesc":81},{"categoryNo":161,"categoryName":162,"taxonomyType":80,"taxonomyTypeDesc":81},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},[86,165,166,167,168,169,170,171,172,173,94,174,175,176,177,178,179,130,180,181],"seo keyword research","seo keyword research intent mapping","research","intent","keyword research","mapping","ai tools","standalone","down","search","prompt","when","maps","queries","generate","how","at",{"skillNo":183,"name":184,"nameZh":6,"description":185,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":186,"categories":187,"keywords":196,"publishedAt":43},"01M718PNDT3A19SV7KVWC9083P","seo-aeo-content-strategy","Design content systems that earn both Google rankings *and* AI citations. The core insight: AI answer engines read content differently than humans — they extract the highest-information-gain sentences and treat H2 headings as prompts. The \"ski ramp\" structure optimizes for both.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fseo-aeo-content-strategy\u002FSKILL.md",[188,191,192,193],{"categoryNo":189,"categoryName":190,"taxonomyType":80,"taxonomyTypeDesc":81},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":78,"categoryName":79,"taxonomyType":80,"taxonomyTypeDesc":81},{"categoryNo":83,"categoryName":84,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":194,"categoryName":195,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000036","内容创作者",[86,144,34,197,198,100,199,200,201,148,94,202,203,204,205,151,206,207,25,208],"seo aeo content strategy","content strategy","Citations","as","core","design","information","earn","structure","systems","ramp","prompts",{"skillNo":210,"name":211,"nameZh":6,"description":212,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":213,"categories":214,"keywords":218,"publishedAt":43},"01M718PJM103BE7581G6NRCC7T","prompt-picker","Build a prompt library that reveals how a brand shows up across the full buyer journey in AI search systems. The library is designed for actual LLM visibility tracking, not theoretical SEO keyword research.","https:\u002F\u002Fgithub.com\u002Fnarayan-metaflow\u002Fmetaflow-marketing-skills\u002Fblob\u002Fmain\u002Fskills\u002Fprompt-picker\u002FSKILL.md",[215],{"categoryNo":216,"categoryName":217,"taxonomyType":80,"taxonomyTypeDesc":81},"01JBSEEDCAT000000000000023","Skill与智能体开发",[219,175,220,221,86,148,165,174,222,223,224,225,167,130,180,206,169,226,227,150],"prompt picker","llm visibility","brand","up","journey","prompt library","across","library","tracking"]