Conversions on iOS Campaigns: Meta Underestimates, Google Overestimates

📢If you run iOS campaigns on Google Ads and Meta using their modeling technologies simultaneously, you need to know this:

👉Google ALWAYS tends to overestimate conversions
👉Meta ALWAYS tends to underestimate conversions

And to prove it, I will share a recent case I had with one new client which I recently audited and had NOT SKAN schema in place (they just had cv=0 for installs and that’s it)

First, let’s analyze Google Ads numbers:
They were running one AEO campaigns for “start_trial” in the US. Since they didn’t set up any event in SKAN schema, these trials were purely modeled by Google.

➡Google modeled installs: 537
➡SKAN installs: 427
➡ASC App Referrer: 419 installs

With ASC and SKAN being so close, it’s hard to trust Google’s numbers. (I know ASC & SKAN are not attributed in the same way, and they’re even different conversions)

➡Google modeled trials: 139 –> this means that Start Rate is +25%
➡Estimated trials applying realistic Start Rate (18%) on realistic installs: 79

❌Google modeled CPA: $55
✅Estimated CPA based on realistic metrics: $98
Difference: 78%!!😳😳😳

Now, let’s move to Meta.
They were running the exact same campaign based on start_trial event but using AEM. The key difference? They had the Meta SDK in place, meaning conversions weren’t purely modeled—Meta received actual conversion data.

➡Meta modeled installs: 1753
➡SKAN installs: 1142
➡ASC App Referrer: 1904 installs

Here, AEM and ASC are much closer to reality than SKAN. To take a more pessimistic approach, I applied an Adjustment Factor of 80% to my AEM installs (I’ll cover this in detail in my upcoming guide 😉).

➡Meta modeled trials: 160 –> this means that Start Rate is 9%
➡Estimated trials (using a realistic Start Rate of 18% on 80% of AEM installs): 252

❌Meta modeled CPA: $38
✅Estimated CPA based on realistic metrics: $24
Difference: -36%!!!!!!!!🔥🔥

And that’s based on the WORST-case scenario. If you work with ASC numbers directly, the estimated CPA would be even lower in Meta!

The takeaway? 👉This client should shift more budget to Meta until these calculations no longer justify the lower CPA.

This isn’t the first case I’ve seen where Google Ads overestimates while Meta underestimates iOS app conversions, but it’s a great example of how to find the real numbers.

As a final tip, I always recommend adding a question during onboarding to track user origin. This gives you another data point to validate whether ASC, AEM, SKAN, or Google are accurate or not.