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/geo-device-segmentation

Break down user behaviour by country, city, device category, and OS to understand regional patterns and optimise for your key markets.

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google-analytics-mcp
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$ npx -y skills add surendranb/google-analytics-mcp --skill geo-device-segmentation --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/geo-device-segmentation

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Break down user behaviour by country, city, device category, and OS to understand regional patterns and optimise for your key markets.

SKILL.md

geo-device-segmentation.SKILL.md
name: geo-device-segmentation
description: "Break down user behaviour by country, city, device category, and OS to understand regional patterns and optimise for your key markets."

Geo and Device Segmentation

Break down user behaviour by country, city, device category, and OS to understand regional patterns and optimise for your key markets.

Correct dimension names

| Concept | GA4 API name | |---|---| | Country | `country` | | City | `city` | | Region | `region` | | Device category | `deviceCategory` | | Operating system | `operatingSystem` | | OS version | `operatingSystemVersion` | | Browser | `browser` | | Screen resolution | `screenResolution` | | Language | `language` |

Device category values: `desktop`, `mobile`, `tablet`.

Step 1 — Country breakdown

dimensions: ["country"]
metrics: ["totalUsers", "sessions", "userEngagementDuration",
          "screenPageViewsPerSession", "keyEvents"]
date_range: last 30 days
order_by: totalUsers DESC
limit: 20

Step 2 — Device split

dimensions: ["deviceCategory"]
metrics: ["sessions", "totalUsers", "engagementRate",
          "userEngagementDuration", "bounceRate"]
date_range: last 30 days
order_by: sessions DESC

Step 3 — Country + device cross-tab

Understand device preferences by market:

dimensions: ["country", "deviceCategory"]
metrics: ["sessions", "userEngagementDuration", "bounceRate"]
dimension_filter: country IN [your top 5 countries from Step 1]
date_range: last 30 days
order_by: sessions DESC

Note: combining country + deviceCategory + additional dimensions in one query may exceed GA4's cardinality limit. Keep to 2–3 dimensions max.

Step 4 — Single-country deep dive

For a specific country (e.g. Japan):

dimensions: ["city", "deviceCategory"]
metrics: ["sessions", "totalUsers", "userEngagementDuration", "keyEvents"]
dimension_filter: {
  "filter": {
    "fieldName": "country",
    "stringFilter": {"matchType": "EXACT", "value": "Japan"}
  }
}
date_range: last 30 days
order_by: sessions DESC
limit: 20

Step 5 — Browser and OS (for technical optimisation)

dimensions: ["browser", "operatingSystem", "deviceCategory"]
metrics: ["sessions", "bounceRate", "userEngagementDuration"]
date_range: last 30 days
order_by: sessions DESC
limit: 20

What to report

  • Top 10 countries by users and their engagement quality
  • Mobile vs desktop vs tablet split (sessions and engagement rate)
  • Any country where engagement is significantly below average — flagged for investigation
  • Device preferences by your top 3 markets if they differ meaningfully
Read more
Ships withgoogle-analytics-mcp

Model Context Protocol (MCP) server for Google Analytics 4: real-time query exploration, schema discovery, metric aggregation, and audience insights for AI agents. 🌐 Live Documentation & Web Portal:

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