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21-ads-audit-global

This Claude Code skill conducts a comprehensive audit of advertising accounts across Meta, Google, and TikTok platforms, assigning a Health Score between 0 and 100 based on 84 checkpoints across six dimensions: Account, Campaign, AdSet, Ad, Tracking, and Optimization. Use it when ROAS drops significantly, inheriting accounts from other teams, spending over $5,000 monthly without systematic review, encountering pixel or conversion API errors, preparing to scale spend substantially, or managing dropshipping operations with attribution discrepancies.

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git clone --depth 1 https://github.com/minhnv0807/ai-business-skills /tmp/21-ads-audit-global && cp -r /tmp/21-ads-audit-global/skills/en/21-ads-audit-global ~/.claude/skills/21-ads-audit-global
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SKILL.md

# Ads Audit (Global) — Health Score & Action Plan

> **Difference from `03-performance-eval-global`:**
> - `03` evaluates current performance (CPM, ROAS, funnel) — diagnoses symptoms.
> - `21` audits account configuration (setup, structure, tracking, creative) — scores 0-100 and finds systemic issues.
>
> Insight before numbers. Lead with judgment; illustrate with metrics.

---

## For Newbies — Start Here

**What is an ads audit?**
A structured review of your ad accounts (Meta, Google, TikTok) to find leaks, misconfigurations, and missed opportunities. The output is a **Health Score (0-100)**, a list of **Quick Wins**, and a **7-day Action Plan**.

**When do you need one?**
- ROAS dropped suddenly (>20% week-over-week).
- New account inherited from another agency or in-house team.
- Spending >$5K/month with no clear performance review process.
- Pixel/CAPI showed errors or duplicate events.
- About to scale spend by 2-3x and want to verify foundation.
- Dropshipping store with attribution confusion (Shopify vs Meta vs Triple Whale numbers don't match).

**What you'll need before starting:**
1. Read access to ad accounts (or screen-share / data export).
2. Last 30 days of spend, impressions, clicks, conversions, ROAS.
3. Pixel/CAPI status (Events Manager, GA4, TikTok Events).
4. Region context (US, EU, SEA, LATAM) — benchmarks differ widely.
5. Business model (DTC e-com, B2B SaaS, lead gen, dropshipping) — optimization rules differ.

**How long does it take?**
- Quick audit: 2-3 hours (Health Score + Quick Wins).
- Full audit: 6-10 hours (Health Score + 84 checkpoints + 7-day plan + creative review).

---

## Step 0 — Read Context + Select Region Variant

Before audit, pull two contexts:

1. **Product context** — call `product-marketing-context-global` if not already in conversation. This gives the auditor: pricing, target CAC, business model, current channels.
2. **Region variant** — load the appropriate file:

| Region | File | Currency | Key benchmarks |
|--------|------|----------|----------------|
| **US / North America** | `variants/01-us.md` | USD | Meta CPM $7-12, Google CPC $1-3, ROAS 3-5x |
| **EU / UK** | `variants/02-eu.md` | EUR / GBP | Meta CPM €5-10, Google CPC €1-3, ROAS 3-4x |
| **SEA (VN, TH, ID, PH, SG, MY)** | `variants/03-sea.md` | USD-equivalent | Meta CPM $1-2, Google CPC $0.30-1, ROAS 2-3x |
| **LATAM (BR, MX, AR, CO, CL)** | `variants/04-latam.md` | USD-equivalent | Meta CPM $0.50-1.5, Google CPC $0.20-0.80, ROAS 2-3x |

> **Why region matters:** A $5 CPM is excellent in US but terrible in Vietnam. Audit grading without regional context produces false positives or false negatives.

---

## Information Gathering

Ask up to 4 questions:

1. **Which platforms?** Meta / Google / TikTok / multi-platform — and what % of total ad spend each represents.
2. **Industry + business model?** (DTC e-com, dropshipping, B2B SaaS, lead-gen, local service, course/info-product.)
3. **Monthly ad spend + region?** (e.g. "$15K/month, 70% US, 30% Canada".)
4. **Can you share data?** Either paste tables, share a Looker Studio link, or grant view access to the ad account.

### Auto-pull via MCP (if connected)

If user has connected an MCP server, pull data directly:

| Platform | MCP recommended | Key tools used |
|----------|-----------------|----------------|
| Meta Ads | Meta Official MCP (`mcp.facebook.com/ads`) | `ads_insights_anomaly_signal`, `ads_insights_auction_ranking_benchmarks`, `ads_get_dataset_quality`, `ads_get_opportunity_score` |
| Google Ads | Google Official MCP | GAQL: campaign performance, search terms, quality score |
| TikTok Ads | AdsMCP / tiktok-ads-mcp-server | Performance reports, creative library |
| Cross-platform | Adspirer ads-mcp | Unified analytics across 175+ tools |

**Sample Meta Insights fields when MCP unavailable:**
```
fields=spend,impressions,clicks,ctr,cpc,cpm,actions,cost_per_action_type,
       purchase_roas,frequency,reach
date_preset=last_30d
level=adset
breakdowns=age,gender
```

**Sample GAQL query for Google audit:**
```sql
SELECT campaign.name, campaign.status, campaign.bidding_strategy_type,
       metrics.impressions, metrics.clicks, metrics.cost_micros,
       metrics.conversions, metrics.cost_per_conversion,
       metrics.search_impression_share
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
  AND campaign.status != 'REMOVED'
ORDER BY metrics.cost_micros DESC
```

---

## Health Score Framework (0-100)

### Formula
```
Health Score = Σ(Check_pass × Severity_weight × Dimension_weight)
             / Σ(Check_total × Severity_weight × Dimension_weight) × 100
```

### Severity weights
| Severity | Multiplier | Meaning |
|----------|-----------|---------|
| Critical | 5.0× | Active money/data loss — fix today |
| High | 3.0× | Major impact — fix within 7 days |
| Medium | 1.5× | Best practice gap — fix within 30 days |
| Low | 0.5× | Optimization — fix when possible |

### Grade scale
| Score | Grade | Meaning |
|-------|-------|---------|
| 90-100 | **A** | Excellent — maintain & scale |
| 75-89 | **B** | Good — a few improvements needed |
| 60-74 | **C** | Average — needs serious investment |
| 40-59 | **D** | Poor — significant performance leaks |
| <40 | **F** | Critical — likely losing money in real time |

### 6 Dimensions

```
1. Account     (10%) — billing, permissions, BM/MCC structure, account warnings
2. Campaign    (15%) — objectives, separation (cold/warm/retarget), budget allocation
3. AdSet/AdGroup (20%) — audience, budget, scheduling, exclusions, learning phase
4. Ad/Creative (25%) — diversity, freshness, hook quality, format mix
5. Tracking    (20%) — pixel/CAPI/server-side, event quality, attribution model
6. Optimization (10%) — bid strategy, ML signals, budget pacing, automation rules
```

---

## 84 Checkpoints (Universal Core)

> Region-specific benchmark numbers live in the variant files. The checkpoint logic is identical worldwide.

### Dimension 1 — ACCOUNT (12 checks, weight 10%)

| # | Check | Severity |
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