| 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 |
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
PDF Export
When the user asks to export as PDF, use the shared converter at ads/references/md_to_pdf.py.
Usage: Copy it to the working directory, update INPUT/OUTPUT paths in __main__, run with python3.
CRITICAL fpdf2 rules (these prevent content from being cut off):
- NEVER use
cell() + multi_cell() combos for list items. fpdf2 breaks page handling across this pattern. Instead, prepend the number/bullet to the text and use a SINGLE multi_cell() call:
- Numbered:
pdf.multi_cell(w, lh, f"{num}. {text}")
- Bullet:
pdf.multi_cell(w, lh, f" • {text}")
- ALWAYS call
pdf.set_x(pdf.l_margin) before every multi_cell() call. After tables and other elements, the X cursor can be in an unpredictable position, causing "Not enough horizontal space" errors.
- NEVER use
multi_cell(0, ...) (width=0). Always use an explicit width like pdf.cw (content width property). Width 0 calculates from current X which may be wrong.
- Always
check_page() before rendering. Estimate line count with wrapped_line_count() and call check_page(lines * line_height) to force a page break before content starts, not in the middle of it.
Campaign Build Guide Structure
When generating campaign build guides, structure each campaign with clear stages that match the Ads Manager UI flow:
- Stage 1: Campaign Settings — objective, name, budget, CBO, bidding
- Stage 2: Ad Set Settings — audience, targeting, placements, optimization (each ad set as its own subsection with numbering restarting at 1)
- Stage 3: Ad Settings — creative, copy, URLs, CTA
This prevents mixing campaign/ad set/ad level settings into one confusing numbered list.
