| name | ads-meta |
| description | Meta Ads deep analysis covering Facebook and Instagram advertising. Evaluates 46 checks across Pixel/CAPI health, creative diversity and fatigue, account structure, and audience targeting. Includes Advantage+ assessment. Use when user says "Meta Ads", "Facebook Ads", "Instagram Ads", "Advantage+", or "Meta campaign".
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Meta Ads Deep Analysis
Process
- Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
- Read
ads/references/meta-audit.md for full 46-check audit
- Read
ads/references/benchmarks.md for Meta-specific benchmarks
- Read
ads/references/scoring-system.md for weighted scoring
- Evaluate all applicable checks as PASS, WARNING, or FAIL
- Calculate Meta Ads Health Score (0-100)
- Generate findings report with action plan
What to Analyze
Pixel / CAPI Health (30% weight)
- Meta Pixel installed and firing on all pages
- Conversions API (CAPI) active (30-40% data loss without it post-iOS 14.5)
- Event deduplication configured (event_id matching, ≥90% dedup rate)
- Event Match Quality (EMQ) ≥8.0 for Purchase event
- All standard events configured (ViewContent, AddToCart, Purchase, Lead)
- Custom conversions created for non-standard events
- Aggregated Event Measurement (AEM) configured for iOS
- Domain verification completed
- Server-side events include customer_information parameters
- Pixel fires with correct currency and value parameters
Creative (30% weight)
- ≥3 creative formats active (image, video, carousel, collection)
- ≥5 creatives per ad set (Meta recommendation)
- Creative fatigue detection: CTR drop >20% over 14 days = FAIL
- Video creative: 15s max for Stories/Reels, 30s max for Feed
- UGC/testimonial creative tested
- Dynamic Creative Optimization (DCO) tested
- Ad copy: headline under 40 chars, primary text under 125 chars
- Creative refresh cadence: every 2-4 weeks for high-spend
Account Structure (20% weight)
- Campaign Budget Optimization (CBO) vs Ad Set Budget (ABO) intentional
- Campaign consolidation: ≤5 active campaigns per objective type
- Learning phase health: <30% ad sets in "Learning Limited" (FAIL >50%)
- Budget per ad set: ≥5x target CPA (minimum for learning phase exit)
- Ad set audience overlap <30% (Audience Overlap tool)
- Campaign naming conventions consistent and descriptive
- Advantage+ Shopping Campaigns (ASC) active for e-commerce
- Simplified campaign structure (fewer, larger ad sets preferred)
Audience & Targeting (20% weight)
- Prospecting frequency (7-day): <3.0 (WARNING 3-5, FAIL >5)
- Retargeting frequency (7-day): <8.0 (WARNING 8-12, FAIL >12)
- Custom Audiences: website visitors, customer lists, engagement
- Lookalike Audiences: multiple seed sizes tested (1%, 3%, 5%)
- Advantage+ Audience tested vs manual targeting
- Interest targeting: broad enough for algorithm optimization
- Exclusions: purchasers excluded from prospecting, overlap managed
- Location targeting reviewed for relevance
Advantage+ Assessment
If Advantage+ features are in use:
- ASC (Shopping Campaigns): catalog connected, existing customer cap set
- Advantage+ Audience: performance vs manual audience compared
- Advantage+ Creative: enhancements enabled (text, brightness, music)
- Advantage+ Placements: enabled (let Meta optimize placement mix)
- Budget allocation: Advantage+ campaigns getting fair test budget
Special Ad Categories
If ads are in restricted categories:
- Special Ad Category declared before campaign creation
- Targeting restrictions verified (no ZIP, age 18-65+ only, no Lookalike)
- Creative compliance with category-specific policies
- Read
ads/references/compliance.md for full requirements
EMQ Optimization Guide
| EMQ Score | Status | Action |
|---|
| 8.0-10.0 | Excellent | Maintain current setup |
| 6.0-7.9 | Good | Add more customer_information parameters |
| 4.0-5.9 | Fair | Implement CAPI, improve data quality |
| <4.0 | Poor | Critical: CAPI + Enhanced Matching required |
Key parameters to maximize EMQ:
em (email) — highest match rate signalph (phone) — second highest match signalfn, ln (first/last name) — improves match accuracyct, st, zp (city, state, zip) — geographic matchingexternal_id — CRM/user ID for cross-device matching
Key Thresholds
| Metric | Pass | Warning | Fail |
|---|
| EMQ (Purchase) | ≥8.0 | 6.0-7.9 | <6.0 |
| Dedup rate | ≥90% | 70-90% | <70% |
| CTR | ≥1.0% | 0.5-1.0% | <0.5% |
| Creative formats | ≥3 | 2 | 1 |
| Creatives per ad set | ≥5 | 3-4 | <3 |
| Learning Limited | <30% | 30-50% | >50% |
| Budget per ad set | ≥5x CPA | 2-5x CPA | <2x CPA |
Budget-edit safety (operational landmine)
When you edit a live campaign's budget mid-day, Meta treats the daily budget as a hard calendar-day cap. Setting it below what the campaign has already spent today halts ALL delivery until midnight — while the campaign still shows "Active" in Ads Manager.
Real incident (2026-06-11): trimming HV ASC Core 52639162668484 from $800→$300/day at 11:33 ET, after ~$396 had already spent that morning → zero delivery for ~3 hours, sales stalled. "Active" ≠ delivering.
Before ANY mid-day budget cut:
- Pull
date_preset=today spend for the campaign; the new cap must be comfortably ABOVE today's spend (today_spend + expected evening spend). Meta pacing can front-load 30%+ of the daily budget into one good auction hour, so weekly-average spend massively understates intraday spend.
- Prefer applying cuts just after midnight ad-account time, when
today_spend = 0.
- After any budget edit, verify delivery within the hour via the hourly insights breakdown — not just the status field.
- Check
effective_status at all three levels (campaign, ad set, ad) after changes — someone may have manually paused a level in parallel.
Output
Meta Ads Health Score
Meta Ads Health Score: XX/100 (Grade: X)
Pixel / CAPI Health: XX/100 ████████░░ (30%)
Creative: XX/100 ██████████ (30%)
Account Structure: XX/100 ███████░░░ (20%)
Audience: XX/100 █████░░░░░ (20%)
Deliverables
META-ADS-REPORT.md — Full 46-check findings with pass/warning/fail- EMQ improvement roadmap
- Creative fatigue alerts (any creative with CTR declining >20%)
- Quick Wins sorted by impact
- Advantage+ adoption recommendations
