Geographic performance — which regions are paying back, and how to localize creative for the ones worth doubling down on.Documentation Index
Fetch the complete documentation index at: https://docs.ocular.dev/llms.txt
Use this file to discover all available pages before exploring further.
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.
What this data model represents
Grain: one row perdate × 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.
Show sample metrics in each category
Show sample metrics in each category
Show sample dimensions in each category
Show sample dimensions in each category
Slice by
Unique to this data model:| Dimension | Type | Example values |
|---|---|---|
region | String | Countries: United States, Canada · States: California, Texas · Cities: Los Angeles, New York |
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?
Available metrics
Everything you can compute on this data model. Need a metric not listed? See the Meta Ads metric availability matrix.| Metric | Formula |
|---|---|
| Spend & revenue | |
| Ad Spend | Sum of daily spend |
| Conversion Value | Sum of reported revenue |
| ROAS | Conversion Value ÷ Ad Spend |
| Conversions | Sum of reported orders |
| Clicks & impressions | |
| Clicks (All) | Sum of clicks (inline + outbound) |
| Impressions | Sum of impressions |
| CTR (All) | Clicks ÷ Impressions × 100 |
| Outbound Clicks | Sum of clicks leading off Meta |
| Inline Clicks | Sum of on-platform engagement clicks |
| Unique Clicks | Avg of deduplicated user clicks |
| Cost efficiency | |
| CPC (All) | Ad Spend ÷ Clicks |
| CPM | Ad Spend ÷ Impressions × 1,000 |
| CPA | Ad Spend ÷ Conversions |
| Cost Per Outbound Click | Ad Spend ÷ Outbound Clicks |
| Engagement | |
| Landing Page Views | Sum |
| Post Engagement | Sum (reactions + comments + shares + clicks) |
| Post Shares | Sum |
| Cost Per Post Engagement | Ad Spend ÷ Post Engagements |
| Conversion funnel | |
| View Content | Sum |
| Add to Cart | Sum |
| Checkouts Initiated | Sum |
| Reach & frequency | |
| Reach | Sum of unique people who saw ads |
| Frequency | Impressions ÷ Reach |
Raw fields (for custom calculations)
Raw fields (for custom calculations)
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