Cross Platform Audit

Cross-Platform Audit — Unified Paid Media Assessment

Orchestrates parallel scored audits across Google Ads, Meta Ads, and Microsoft Ads, then merges results into a single budget-weighted health score with cross-platform intelligence.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/cross-platform-audit ~/.claude/skills/

Context Intake (Always Do First)

Before running audits, collect this information. Without it, benchmarks will be generic and recommendations may be wrong.

Ask these questions (combine into one prompt):

1. Business type — E-commerce/DTC, SaaS/B2B, Local Service, Lead Gen, Agency, Other
2. Monthly ad spend — Total and per-platform breakdown (approximate is fine)
3. Primary goal — Revenue/ROAS, Leads/CPA, App Installs, Brand Awareness
4. Active platforms — Which platforms are they advertising on? (Google, Meta, Microsoft, others)
5. Data available — What can they provide? (exports, screenshots, pasted metrics, MCP access)

Use the provided context to:

• Determine which platform audits to run (skip platforms they don't use)
• Calculate budget share per platform for aggregate scoring
• Calibrate severity based on spend level ($5K/mo gets different advice than $100K/mo)

Orchestration Workflow

Step 1: Collect Context

Gather business type, platforms, budgets, goals, and available data per the intake above.

Step 2: Spawn Parallel Audits

Use the Task tool to run platform audits simultaneously. Each audit task should:

1. Load skills/shared/scoring-system.md for the scoring algorithm
2. Load the platform-specific CHECKS.md for the audit checklist
3. Load the platform-specific SKILL.md and REFERENCE.md for diagnostic context
4. Evaluate each applicable check as PASS, WARNING, or FAIL
5. Calculate the platform health score using weighted formula
6. Identify Quick Wins
7. Write results to a structured output

Spawn these tasks in parallel (adjust based on which platforms the user has):

Task 1: Google Ads Audit
  → Read skills/shared/scoring-system.md
  → Read skills/google-ads/CHECKS.md
  → Evaluate 74 checks against provided data
  → Calculate score → Write google-audit-results.md

Task 2: Meta Ads Audit
  → Read skills/shared/scoring-system.md
  → Read skills/facebook-ads/CHECKS.md
  → Evaluate 46 checks against provided data
  → Calculate score → Write meta-audit-results.md

Task 3: Microsoft Ads Audit
  → Read skills/shared/scoring-system.md
  → Read skills/microsoft-ads/CHECKS.md
  → Evaluate 30 checks against provided data
  → Calculate score → Write microsoft-audit-results.md

If the user only has 2 platforms, spawn only those 2 tasks.

Step 3: Merge Results

After all audit tasks complete:

1. Read all *-audit-results.md files
2. Extract per-platform scores and grades
3. Calculate budget-weighted aggregate score:

   Aggregate = Σ(Platform_Score × Platform_Budget_Share)

4. Run cross-platform analysis (see Cross-Platform Analysis below)
5. Merge Quick Wins from all platforms into a unified priority list
6. Generate the unified report

Step 4: Cross-Platform Analysis

Add intelligence that no single-platform audit can provide:

Budget Allocation Analysis

• Is spend distributed optimally across platforms?
• Are high-performing platforms budget-constrained while low performers have excess?
• Does the platform mix match the business type? (e.g., B2B without LinkedIn, ecom without Shopping)
• Compare platform CPAs and flag reallocation opportunities

Tracking Consistency

• Are conversion events defined consistently across platforms?
• Is revenue/value tracking active on all platforms or only some?
• Are attribution windows aligned? (7-day click on Meta but 30-day on Google = inconsistent reporting)
• Is there a single source of truth (GA4) or are platforms reporting independently?

Creative Alignment

• Is messaging consistent across platforms or contradictory?
• Are creative formats appropriate per platform? (vertical video for Meta/TikTok, text-heavy for Search)
• Is creative being refreshed at similar cadences or is one platform stale?

Attribution Overlap

• Are platforms double-counting conversions? (same user converts, Google and Meta both claim credit)
• What percentage of total reported conversions exceeds actual conversions?
• Is there a de-duplication strategy (UTMs + GA4 as arbiter)?

Kill List

• Campaigns/ad sets across ALL platforms with CPA >3x target
• Aggregate wasted spend across platforms
• Quick calculation: total monthly waste = Σ(flagged campaign spend)

Scaling Opportunities

• Which campaigns across all platforms have CPA below target AND are budget-constrained?
• What is the estimated incremental revenue from reallocating waste to winners?