If your Facebook Page is monetized, you may see different earnings metrics in Measure Studio depending on how your account is set up. This guide explains the three types of Facebook earnings metrics we track and what they mean.
⚠️ Important: Meta applies disclaimers to all monetization metrics, noting that reported earnings may differ from your final invoice payment. Measure Studio reflects the data as provided via Meta’s API.
The Three Types of Facebook Earnings Metrics
1. Ad Break Earnings (Legacy Model)
What it is: Earnings from video ads in traditional video posts (not reels).
Who it applies to: Pages still using the old monetization model.
Notes:
These earnings don’t match Meta Business Suite exactly but are typically within 1% accuracy after about 30 days.
Measure Studio collects this data weekly.
If your page has opted into the new monetization model, Ad Break Earnings data is no longer available.
2. Approximate Earnings (Legacy Model with Broader Coverage)
What it is: A more comprehensive earnings estimate that includes:
Reels
Stars
Bonuses
Who it applies to: Pages still using the old monetization model.
Notes:
Closely matches Meta Business Suite data.
Stops reporting once a page switches to the new monetization model.
Meta may phase this out in the future.
3. Content Monetization Earnings (New Model)
What it is: Facebook’s new, evolving earnings metric for all post types, including:
Videos
Reels
Stories
Images
Bonuses
Who it applies to: Pages that have opted into Meta’s new content monetization model.
Notes:
Slightly lower than what is shown in Meta Business Suite due to differences in how Meta’s API reports this data.
Meta labels this metric as “still in development,” so accuracy may vary.
Measure Studio re-collects this data daily, which helps it stabilize over time.
Recommended Setup in Measure Studio
To get the most complete picture of your Facebook earnings per page, we recommend creating a custom metric that adds together:
Approximate Earnings - TotalContent Monetization Total Earnings
This combined metric gives you a reliable view whether you’re using the old model, the new model, or transitioning between the two.