القائمة
Systematic 75+ checkpoint audit based on the Sam Tomlinson framework: ICP validation → signal infrastructure → account structure → audiences → creatives → measurement — with ICE-prioritized recommendations.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Optimize budget allocation across paid media channels using Marketing Efficiency Ratio (MER), marginal ROAS analysis, diminishing returns modeling, and incrementality-informed decisions.
AI search and citation behavior change quickly. The frameworks below use the best available public data as of early 2026 (Google surfaces, ChatGPT, Perplexity, Gemini, and large-sample studies). Re-check assumptions as platforms update.
Plan, write, and maintain content that wins purchase-near buyers in both organic search and AI answer engines. BOFU content is structurally different from TOFU — the reader has accepted they need to decide; the page's job is to resolve the decision. Get it right and a single deep page can outperform dozens of informational posts on revenue contribution.
Analyze paid media performance across dimensions, funnels, cohorts, and channels — turning data into actionable insights and business narratives.
Systematic 70+ checkpoint audit covering tracking, structure, keywords, ads, bidding, budgets, audiences, and competitive positioning — with ICE-prioritized recommendations.
Build and configure Google Ads campaigns across all 10+ campaign types — from campaign type selection through settings, targeting, creatives, and launch.
| name | meta-ads-account-audit |
| description | Systematic 75+ checkpoint audit based on the Sam Tomlinson framework: ICP validation → signal infrastructure → account structure → audiences → creatives → measurement — with ICE-prioritized recommendations. |
This is the foundation. Weak signals = weak delivery via Meta's Andromeda ranking system. Audit this first.
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Pixel active | Meta Pixel firing on all relevant pages | Missing or intermittent |
| CAPI active | Conversions API implemented alongside Pixel | Not configured — this is always Critical in 2025 |
| Event deduplication | Matching event_id between Pixel and CAPI | Not configured or double-counting visible |
| EMQ scores | Event Match Quality per event type | Below 6.0 (minimum acceptable). Target 8.0+ |
| Matching keys sent | Email, phone, fbc, fbp, IP, user agent | Missing high-impact keys (email, phone, fbc) |
| Conversion events | Correct events configured as optimization targets | Optimizing for micro-events (PageView) instead of macro-events (Purchase, Lead) |
| Event volume | Conversions per ad set per week | Below 25/week/ad set (stability minimum). Target 50+/week (optimal) |
| Conversion values | Dynamic values sent with Purchase events | Static or missing values for ecommerce |
| Offline tracking | CRM/offline events flowing through CAPI | Using discontinued Offline Conversions API (killed May 2025) — migrate to standard CAPI with action_source: system_generated or physical_store |
| Attribution windows | 7-day click / 1-day view default | Non-standard windows without clear rationale. Note: 7d_view and 28d_view removed from Insights API October 2025 |
| AEM configuration | Aggregated Event Measurement for iOS 14+ | Event priority not configured, or low-value events prioritized over high-value |
For detailed tracking fixes, use the meta-ads-tracking-setup skill.
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Objective alignment | Campaign objectives match business goals | Using Traffic objective when goal is Sales/Leads |
| Campaign consolidation | Budget concentrated in fewer, well-funded campaigns | Too many small-budget campaigns/ad sets (each needs 50+ conversions/week for optimal learning) |
| Campaign architecture | Clear structure: Prospecting, Retargeting, Testing | No separation between prospecting and retargeting |
| ASC usage (ecommerce) | Advantage+ Shopping Campaigns for ecommerce | Ecommerce account with 100+ conversions/week not testing ASC (typically reduces cost per purchase ~12%) |
| New vs existing split | ASC customer ratio configured intentionally | Default ratio without analysis of actual customer mix |
| Naming conventions | Consistent, parseable taxonomy across campaigns/ad sets/ads | Inconsistent naming making analysis impossible |
| Special Ad Category | Housing, employment, credit categories set where required | Missing Special Ad Category when advertising in regulated industries |
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Audience size (TOF) | Top-of-funnel audience reach | Below 200K for prospecting campaigns |
| Audience size (remarketing) | Retargeting pool size | Below 1,000 (too small for stable delivery) |
| Audience overlap | Overlap between ad sets in same campaign | Significant overlap causing self-competition |
| Exclusion strategy | Recent converters and existing customers excluded from prospecting | No exclusions — wasting budget showing ads to existing customers |
| Targeting exclusions change | Detailed targeting exclusions removed March 31, 2025 | Still trying to use interest-based exclusions. Modern approach: customer list exclusions, recent converter exclusions, lifecycle suppression |
| Custom audiences | Website visitors, CRM uploads, engagement audiences | No custom audiences built. CRM upload match rate benchmark: 40-70% |
| Lookalike seeds | Quality of lookalike source audiences | Low-quality seeds (all website visitors) instead of high-quality seeds (purchasers, high-value customers). Start 1%, test up to 5-10% |
| Advantage+ audience | Using algorithm-driven expansion with suggestions | Not testing Advantage+ audience on accounts with strong Pixel/CAPI data |
| Warm + cold mixing | 2025 best practice: combine in single ad sets | Hyper-segmented audiences in separate ad sets limiting algorithm learning |
| Engagement audiences | Proactively building video viewers, page engagers | No engagement audiences — these only capture data from creation date, not retroactively |
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Creative frequency | Frequency at the creative level (not ad or ad set level) | Frequency > 4 — Meta research: 45% conversion drop at 4 exposures |
| CTR trend | CTR trajectory over 7-day rolling average | CTR declining > 20% from 7-day average = fatigue signal |
| CPC trend | CPC movement correlated with CTR | Rising CPCs alongside declining CTR = confirmed fatigue |
| Creative volume | Number of active creative variants per ad set | Fewer than 4 variants (insufficient for rotation) or more than 150 in ASC (hitting ceiling) |
| Format diversity | Mix of static, video, carousel, Reels-native | Single format only — missing performance from other formats |
| Aspect ratios | 4:5 vertical for Feed/Stories/Reels, 1:1 fallback | Only landscape or only square creative |
| Video hooks | First 3 seconds engagement | No bold hooks, silent-unfriendly (85% of Facebook videos watched without sound) |
| Ad copy length | Primary text effectiveness | Primary text exceeding 125 characters (gets truncated) |
| Refresh cadence | How often new creative is introduced | Same creatives running 30+ days for prospecting (target refresh every 7-14 days) |
| Landing page experience | Post-click experience quality | Slow load (>3 sec), message mismatch, poor mobile UX |
For creative testing frameworks and fatigue management, use the meta-ads-creative-engine skill.
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Learning phase spend | % of total account spend in learning phase | Exceeds 20% of total spend. Meta: advertisers under 20% see up to 68% lower CPA |
| Ad set edits during learning | Significant changes within first 5-7 days | Edits resetting learning phase (budget changes >20%, audience changes, creative swaps, bid changes) |
| Event volume per ad set | Weekly conversion volume | Below 25/week — ad set may never exit learning |
| Ad set consolidation | Fewer, larger ad sets vs many small ones | Multiple ad sets with <25 conversions/week each — consolidate |
| Learning limited status | Ad sets stuck in "Learning Limited" | Prolonged Learning Limited = restructure needed (consolidate audiences, increase budget, broaden optimization event) |
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Budget allocation | Distribution across campaigns and ad sets | 60/30/10 benchmark: 60% best performers, 30% scaling tests, 10% experiments |
| Bid strategy | Highest Volume, Cost Cap, Bid Cap, ROAS Goal | Using Highest Volume without any guardrails when CPA/ROAS targets exist |
| Budget sufficiency | Enough budget for 50+ conversions/week/ad set | Budget too low for optimization event (switch to higher-funnel event or increase budget) |
| Pacing | Spend trajectory vs budget | Consistently underspending (audience too narrow) or front-loading (audience too broad or bid too high) |
| Cost distribution | Spend across ad sets within campaigns | One ad set consuming 90%+ of budget while others starve |
| Scaling method | How budget increases are applied | Increasing budget >20% at once (risks resetting learning) |
| CPM trends | Cost per 1000 impressions trajectory | Rising CPMs without corresponding performance improvement. Context: Meta avg ad price up 9% in 2025 (Q1 2025 earnings) |
| Checkpoint | What to Check | Flag If |
|---|---|---|
| Attribution window | 7d click / 1d view default | Non-standard without documented reason |
| API attribution change | 7d_view and 28d_view removed from Insights API October 2025 | Reporting still pulling deprecated windows |
| Cross-platform attribution | Consistent measurement across Google + Meta | Different windows making cross-channel comparison meaningless |
| Instant Experience | No longer counts as landing page view (June 2025) | Funnel metrics inflated by counting Instant Experience as landing page views |
| Incrementality testing | Conversion lift or geo-based lift tests | No incrementality measurement — relying solely on platform-reported ROAS |
| Section | Weight | Score |
|---|---|---|
| Signal Infrastructure | 25% | /10 |
| Account Structure | 10% | /10 |
| Audience Strategy | 15% | /10 |
| Creative Health | 20% | /10 |
| Learning Phase | 10% | /10 |
| Budget & Bid Efficiency | 15% | /10 |
| Measurement & Attribution | 5% | /10 |
| Weighted Total | /10 |
Interpretation: 8-10 = Healthy, 6-7.9 = Needs optimization, 4-5.9 = Significant issues, <4 = Critical.
## Meta Ads Account Audit
### Health Score: [X.X / 10] — [Healthy / Needs Optimization / Significant Issues / Critical]
### Critical Issues (fix immediately)
1. **[Issue]** — [What's wrong, specific data] — ICE: [I×C×E = score]
- Action: [Specific fix]
- Expected impact: [Estimated improvement]
### Optimization Opportunities (fix within 2 weeks)
1. **[Issue]** — [What's wrong, specific data] — ICE: [score]
- Action: [Specific fix]
- Expected impact: [Estimated improvement]
### Working Well (maintain)
- [What's working and why]
### Priority Action Plan (next 30 days)
| Priority | Action | ICE Score | Timeline | Owner |
|----------|--------|-----------|----------|-------|
| 1 | [Highest ICE action] | [score] | Week 1 | [who] |
### 2025 Platform Change Flags
- [ ] CAPI implemented (mandatory in 2025)
- [ ] Offline Conversions API migrated (discontinued May 2025)
- [ ] Detailed targeting exclusions replaced with suppression strategy (removed March 2025)
- [ ] Instant Experience funnel metric adjustment (June 2025)
- [ ] 7d_view/28d_view API reporting updated (removed October 2025)
- [ ] ASC evaluated for ecommerce
- [ ] CPM trend accounted for (Meta avg +9% in 2025)
Input: "I run a DTC skincare brand on Meta. Spending $8K/month across 6 campaigns. ROAS dropped from 4.2 to 2.1 over the last month. What's going on?"
Output:
Creative fatigue across all prospecting ad sets — Average creative frequency is 6.8 (threshold: >4). CTR dropped 34% over 30 days. Same 5 creatives running for 45+ days with no refresh. Meta research: 45% conversion drop at 4 exposures. — ICE: 10×9×7 = 630
No CAPI — Pixel only — Missing ~20-30% of conversion events. EMQ unavailable (no server events). Algorithm optimizing on incomplete data. — ICE: 9×9×8 = 648
6 campaigns with $8K/month = ~$44/day per campaign — Most ad sets getting <15 conversions/week. 4 of 6 campaigns stuck in Learning Limited. Meta: need 50+/week for optimal, 25+ minimum. — ICE: 9×8×6 = 432
No customer exclusions on prospecting — Existing customers seeing acquisition ads. Wasted spend + inflated ROAS (counting repeat purchases as new). — ICE: 7×8×9 = 504
All creatives are 1:1 square — Missing 4:5 vertical which outperforms 1:1 by ~15% in Feed (Billo data). No Reels-native content. — ICE: 6×7×6 = 252
No ASC campaign — DTC ecommerce brand with sufficient volume should test Advantage+ Shopping Campaigns. Typically reduces cost per purchase ~12% vs manual. — ICE: 7×6×5 = 210
| Priority | Action | ICE Score | Timeline | Owner |
|---|---|---|---|---|
| 1 | Implement CAPI | 648 | Week 1-2 | Dev + media buyer |
| 2 | Refresh all creatives (new variants + formats) | 630 | Week 1-2 | Creative + media buyer |
| 3 | Upload customer exclusion list | 504 | Day 1 | Media buyer |
| 4 | Consolidate 6 campaigns → 3 | 432 | Week 1 | Media buyer |
| 5 | Create 4:5 vertical creative variants | 252 | Week 2-3 | Creative team |
| 6 | Launch ASC test | 210 | Week 3-4 | Media buyer |
7d_view and 28d_view windows removed from Insights API October 2025. Flag any reporting that still references these.