Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. Platform: Meta.
git clone https://github.com/irinabuht12-oss/marketing-skills.git--- name: audience-overlap-analysis description: Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. Platform: Meta. metadata: platform: Meta --- # 8/ Audience Overlap Analysis — Meta ## What it does Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. ## How it works Claude analyzes your ad set targeting parameters — custom audiences, lookalikes, interest stacks, age/gender splits, and geo targeting — and maps the overlap between them. It cross-references this with delivery data to identify where auction overlap is actually driving up costs vs where it's theoretical but not impactful. ## Practical example You're running 6 prospecting ad sets on Meta, each targeting different interest stacks. Claude identifies that ad sets 2, 4, and 6 have an estimated 60%+ audience overlap because the interest categories share the same underlying user pool. These three ad sets have CPMs 28% higher than the non-overlapping ones. Recommendation: consolidate into one ad set with broader targeting and let Meta's algorithm optimize, or use audience exclusions to create clean segments. ## What you get back - Overlap map showing which ad sets share significant audience pools - Estimated CPM inflation from internal competition - Specific targeting overlaps causing the issue (which interests, lookalikes, or custom audiences) - Consolidation recommendations with projected CPM savings - Exclusion strategy if you want to keep separate ad sets with clean audiences ## When to use it - When scaling Meta campaigns and adding new ad sets - If CPMs are rising without clear external cause - During account restructuring to clean up legacy targeting - When frequency is high across multiple ad sets targeting similar people ## Data access (Ryze MCP) This skill works best with live account data. Connect the free Ryze MCP once and Claude reads your Google Ads, Meta Ads, GA4 and Search Console directly: - claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → `https://connector.get-ryze.ai/mcp` - Claude Code: `claude mcp add ryze --transport http https://connector.get-ryze.ai/mcp` - Cursor: Settings → MCP → add the same URL Setup guide: https://www.get-ryze.ai/how-to-connect-claude-to-google-meta-ads-mcp
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/irinabuht12-oss/marketing-skills/tree/main/skills/audience-overlap-analysisCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
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Check the GitHub repository or documentation for usage examples.
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