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Geographic performance — which regions are paying back, and how to localize creative for the ones worth doubling down on.
Region granularity is set by your ad targeting, not by this data model. If the campaign targets countries, you’ll see countries; if it targets states or cities, you’ll see those. You can’t slice deeper than the targeting allows.

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What this data model represents

Grain: one row per date × ad_account × campaign × adset × ad × region. 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: Meta Ads API, daily refresh.

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Slice by

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

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Use it to answer

  • Where should I shift budget — which regions have the highest ROAS?
  • Which new markets are emerging based on early-stage high performance?
  • How should creative be localized for regional language and cultural preferences?
  • How does Conversion Value differ across regions — what does that tell me about pricing strategy?

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Available metrics

Everything you can compute on this data model. Need a metric not listed? See the Meta Ads metric availability matrix.
Reach and Frequency are only available here and on Platform & Device. Use Region for geographic concentration of reach; use Platform & Device for platform-mix concentration.
This data model exposes:ad_spend · clicks · impressions · reported_orders · reported_revenue · unique_clicks · inline_clicks · outbound_clicks · landing_page_views · add_to_cart · checkouts_initiated · view_content · post_engagement · post_share