geo-performance-analysis
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.
Install / Use
npx skills add irinabuht12-oss/marketing-skills --skill geo-performance-analysisInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of geo-performance-analysis
geo-performance-analysis scores 80/100 on our quality scale, 2292nd of 3,680 Development & Engineering skills we index.
Its SKILL.md is 2.8 KB long, split into 7 sections and no code examples: a solid amount of guidance for an agent.
With 1,836 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 6 days ago, so geo-performance-analysis is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-30. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
geo-performance-analysis compared with similar skills
All 4 of these similar skills score higher than geo-performance-analysis; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| geo-performance-analysis (this skill)by irinabuht12-oss | 80 | 1.8k | 6d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 44.5k | 1d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 7d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 7d ago | SKILL.md |
Frequently asked questions
- How do I install geo-performance-analysis?
- Run
npx skills add irinabuht12-oss/marketing-skills --skill geo-performance-analysis. The install tabs above show the steps for each supported agent. - Which AI agents does geo-performance-analysis work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is geo-performance-analysis safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is geo-performance-analysis still maintained?
- The repository was last updated 6 days ago, so geo-performance-analysis is actively maintained.
Skill content
View source on GitHubname: geo-performance-analysis description: 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. metadata: platform: Google and Meta
24/ Geo Performance Analysis — Google + Meta
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
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
