Geographic Breakdown
Geographic analytics show where a publisher's package installs are coming from — broken down by region and country. This data helps publishers understand their global reach and identify markets where packages are gaining traction or where localization might be valuable.
Available Geographic Data
| View | Granularity | Update Frequency |
|---|---|---|
| World map | Country-level — choropleth map shaded by install count | Daily |
| Region table | Regional groupings (North America, Europe, Asia-Pacific, etc.) with install count and % of total | Daily |
| Country table | Individual country rows sorted by install count, with % share | Daily |
| Top 10 countries | Quick-reference bar chart of top 10 countries by install count | Daily |
What Geographic Data Reveals
Market Concentration
If 80% of installs come from two countries, the publisher has a highly concentrated install base. This creates risk (market-specific policy changes) but also a clear focus for community engagement and support.
Emerging Markets
A country with a small but rapidly growing install share may represent an emerging market opportunity. Cross-referencing geographic trend with the install trend chart can reveal which regions are driving overall growth.
Localization Signals
High installs in regions where the primary language differs from the package's documentation language may indicate latent demand that localized documentation could unlock.
Compliance Awareness
Understanding which countries have active installations helps publishers plan for data residency and compliance requirements — relevant if the package processes or stores tenant data.
Geographic Data and Privacy
Geographic data is aggregated at the country level. No tenant-specific location data is exposed to publishers — publishers see only aggregate install counts per country. Individual tenant identities, exact locations, or sub-national data (state/province/city) are not shown.
Unlike the 15-minute-update install counts on other analytics pages, geographic data is aggregated daily. Selecting a 7-day date range shows the cumulative geographic distribution for that period, not a daily granular breakdown. For historical geographic trend analysis, use the 12-month date range to compare monthly distribution shifts.
Filtering by Package
Publishers with multiple packages can filter the geographic view to a specific package — useful for understanding whether different packages have different geographic profiles. A publisher might find that one package has strong adoption in Europe while another is primarily adopted in North America — each warranting different community and support language priorities.