Meta vs RevenueCat vs Adjust. Or, more generally: ad platform vs subscription management platform vs MMP.
Nobody wants to reconcile these numbers. The differences are messy, the definitions are complicated, and the results often look inconsistent.
But making all three tools agree is not the goal. You can lose in two directions:
- Trust attributed revenue that never becomes cash, and eventually run out of money. Goodbye.
- Become so conservative that you stop spending while braver competitors take the market. Goodbye.
The goal is to understand what each comparison can and cannot tell you.
| Comparison | The question it answers | Check first |
|---|---|---|
| Meta vs RevenueCat | What paid revenue can be directly proven? | The unattributed share |
| Meta vs Adjust | How much credit should paid receive? | Campaigns, spend, timing, windows match |
| Adjust vs RevenueCat | Did the revenue actually arrive? | Same complete dates, both totals |
Meta vs RevenueCat: what paid revenue can be directly proven?
RevenueCat sees the charge. But under ATT, its per-channel revenue is often a floor, because much of the revenue stays unattributed.
What to look for:
- The unattributed share
- Stable paid and organic proportions
- A repeatable gap, rather than identical totals
Meta vs Adjust: how much credit should paid receive?
This is the useful budget comparison, but only after you match the campaigns, spend, timing basis, and attribution windows.
Match first:
- Campaigns and spend
- Snapshot against snapshot
- Click and view-through windows
Adjust vs RevenueCat: did the revenue actually arrive?
Compare total snapshot revenue over the same complete dates. A cash-reality check.
What to look for:
- Totals stay close
- Complete weeks move together
- Edge and partial weeks are excluded
Consistency does not mean identical numbers
When looking for consistency, do not ask whether the numbers are identical. Ask whether:
- the same users and campaigns are being compared
- the same dates and timing logic are being used
- the attribution rules are aligned
- the difference stays reasonably stable over time
A trustworthy difference is explainable, repeatable, and measured on the same basis. That is enough to make a decision.