24/ Geo Performance Analysis — Google + Meta

SkillDev tools

Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits. Platform: Google and Meta.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the 24/ Geo Performance Analysis — Google + Meta skill

What this skill tells your AI

The instructions your AI receives, as published by irinabuht12-oss/marketing-skills in skills/geo-performance-analysis/SKILL.md and read by ahel’s review.

What it does

Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits.

How it works

Claude analyzes your performance data segmented by location, identifies statistically significant performance differences (not just noise from low-volume areas), and calculates the cost of running campaigns in underperforming regions vs the conversions you'd lose by excluding or reducing them.

Practical example

Your national ecommerce campaigns spend evenly across the US. Claude finds that 8 states produce 65% of your conversions at a $24 CPA, while 12 states spend $8,400/month combined with a $71 CPA and only 118 conversions. Three metro areas — Dallas, Phoenix, and Atlanta — outperform their state averages by 40%+ and could absorb more budget. Recommendation: reduce bids 40% in the 12 underperforming states, increase 25% in the top 8, and create separate campaigns for the 3 outperforming metros to give them dedicated budgets.

What you get back

  • Performance breakdown by geo level with CPA, ROAS, CVR, and volume
  • Tier ranking of geos (top performers, average, underperformers) with clear thresholds
  • Bid adjustment recommendations by geo with projected impact
  • Campaign split recommendations for high-volume geos that deserve independent management
  • Spend reallocation model showing how redistributing from weak to strong geos affects total conversions

When to use it

  • When running national or multi-market campaigns and need to optimize allocation
  • After expanding into new regions to evaluate early performance
  • Quarterly to catch geo performance shifts as market conditions change
  • When clients ask "where should we focus" and you need data behind the recommendation

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

Signals

GitHub stars
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Last commit
Sep 2026
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skill
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geo-performance-analysis
Source
github.com/irinabuht12-oss/marketing-skills