ads-meta

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. Triggers on: "Meta Ads", "Facebook Ads", "Instagram Ads", "Advantage+", "Meta campaign", "Meta audit", "FB ads"

/ads meta — Meta Ads Deep Analysis

46-check audit of Meta (Facebook/Instagram) advertising accounts.

Usage

/ads meta

Process

1. Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
2. Evaluate all applicable checks as PASS, WARNING, or FAIL
3. Calculate Meta Ads Health Score (0-100)
4. 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

Advantage+ Assessment

• ASC (Shopping Campaigns): catalog connected, existing customer cap set
• Advantage+ Audience: performance vs manual audience compared
• Advantage+ Creative: enhancements enabled
• Advantage+ Placements: enabled
• Budget allocation: Advantage+ campaigns getting fair test budget

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 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

Deliverables

• META-ADS-REPORT.md — Full 46-check findings with pass/warning/fail
• EMQ improvement roadmap
• Creative fatigue alerts
• Quick Wins sorted by impact
• Advantage+ adoption recommendations