Skip to main content
Google Ads performance by geography — derived from user IP and Google’s geolocation services.

​
What this data model represents

Grain: one row per date × ad_account × campaign × adset × location. Metrics, grouped by category — every number you can compute on this data model. Expand below for examples in each.
Dimensions, grouped by category — every way you can split, filter, or group those metrics. Expand below for examples in each.
Source: Google Ads API, daily refresh.
Reporting granularity is bounded by your campaign’s targeting. A campaign that targets only countries cannot be drilled down to city. Don’t expect city-level rows from a national campaign.

​
Slice by

Unique to this data model: Plus the standard campaign hierarchy, time, and account dimensions — documented once on the Google Ads Overview.

​
Use it to answer

  • Which regions deliver the highest ROAS — where should I rebalance budget?
  • Where should we test expansion — which untargeted markets resemble our best ones?
  • What bid modifier is justified by the CPA gap by city?
  • How does AOV vary by geography — different purchase basket mix per market?

​
Available metrics

Everything you can compute on this data model. Need a metric not listed? See the Google Ads metric availability matrix.
ad_spend · conversion_value · conversions · clicks · impressions · view_through_conversions · video_views