---
title: Incrementality for Meta, Google and Apple Search Ads
description: How to test incrementality on Meta, Google App Campaigns and Apple Search Ads: what each platform's lift tools offer, their published rules and the fallbacks.
url: https://incrementalitycalculator.com/learn/incrementality-meta-google-apple/
---

[Start](https://incrementalitycalculator.com/) / [Learn](https://incrementalitycalculator.com/learn/) / Meta, Google and Apple

# Incrementality on Meta, Google and Apple Search Ads

How to test incrementality on Meta, Google App Campaigns and Apple Search Ads: what each platform's lift tools offer, their published rules and the fallbacks.

**Short answer**

Google Ads offers Conversion Lift studies that support App campaigns (not those targeting iOS), with a published minimum of $5,000 in budget and 1,000 observed conversions. Meta runs randomised lift studies, but Conversion Lift access is limited and arranged through a Meta representative. We found no built-in lift study in Apple's documentation, so Apple Search Ads is usually tested with geo or on/off tests.

## What a platform lift study is

A platform lift study is a holdout test run by the ad platform itself: it randomly keeps part of your audience from seeing your ads and reports the difference in conversions.

**Platform lift study:** a randomised test where the ad platform assigns people to test and control groups and measures the conversion difference. It measures that one platform in isolation.

Platforms are well placed to run these, because they control delivery and can hold people out at the auction. The catch is that each study covers only its own platform and depends on the platform's own counting. The facts below are taken from each platform's own help or developer pages, read on 26 Oct 2026. Requirements change, so check the linked page before planning.

## Google Ads: Conversion Lift and App Uplift experiments

Google's help page on [Conversion Lift based on users](https://support.google.com/google-ads/answer/12005564?hl=en) states:

- Supported campaign types include App campaigns, alongside Display, Search, Video, Demand Gen and Performance Max.
- App campaigns that target iOS are not supported.
- The study needs a minimum campaign budget of $5,000 USD and at least 1,000 observed conversions.
- Google recommends running the study for at least 14 days.
- Conversion Lift is not available for all Google Ads accounts.

Separately, Google's [App Uplift experiment best practices](https://support.google.com/google-ads/answer/14074599?hl=en) page describes experiments that measure the uplift from adding video assets to an App campaign. That is a base-versus-treatment campaign comparison, not a test against no ads. Google recommends a 50/50 split, about 30 days, a budget giving at least 100 (ideally 150 or more) conversions a day, and an 80% confidence level, and notes iOS apps are not currently supported.

**What this means in practice:** Android App campaigns at meaningful spend can get a native user-level lift study. iOS App campaigns, and smaller accounts, need a geo or on/off test instead. This [Google UAC checklist](https://linkrunner.io/blog/google-uac-campaign-checklist?utm_source=incrementalitycalculator&utm_medium=referral&utm_campaign=learn-incrementality-meta-google-apple&utm_content=inline) covers the campaign settings worth fixing before you test.

## Meta: lift studies

Meta's Marketing API documentation on [lift studies](https://developers.facebook.com/docs/marketing-api/guides/lift-studies) describes how they work: Meta randomises the audience, assigns Accounts Center accounts to a test group that can see your ads or a control group that cannot, and after the study calculates the difference between the groups.

The same page says Conversion Lift measurement is currently limited, and advertisers should contact their Meta representative about access. We did not find an official Meta page stating minimum budgets or conversion counts, so none are given here.

**What this means in practice:** if you have a Meta representative, ask about a lift study for your app campaigns. If you do not, a geo test with Meta's location targeting is the practical alternative.

## Apple Search Ads

When we checked Apple's documentation on 26 Oct 2026, we did not find a built-in lift or incrementality study for Apple Search Ads. Teams typically test it themselves:

- **On/off tests on brand keywords:** pause brand terms for two to four weeks and watch total installs from App Store search, not just paid. If total installs barely move, most brand-term installs were coming anyway.
- **Geo tests:** Apple Search Ads campaigns target by country or region, so you can switch campaigns off in some markets and compare.

Brand keywords are the most common cannibalisation risk on Apple Search Ads, because the person searching for your app's name is already looking for it. A piece on [Apple Search Ads beyond brand keyword defence](https://linkrunner.io/blog/apple-search-ads-strategy-for-performance-marketers-beyond-brand-keyword-defense?utm_source=incrementalitycalculator&utm_medium=referral&utm_campaign=learn-incrementality-meta-google-apple&utm_content=inline) covers where the incremental installs usually are. The [cannibalisation guide](https://incrementalitycalculator.com/learn/cannibalisation-brand-retargeting/) explains how to read a brand pause.

## How the options compare

| Platform | Native user-level lift study | Published requirement (official page) | Fallback |
|---|---|---|---|
| Google Ads App campaigns | Yes, Conversion Lift | $5,000 USD budget, 1,000 observed conversions; iOS App campaigns not supported | Geo or on/off |
| Meta | Yes, lift studies | Access limited; via Meta representative | Geo test |
| Apple Search Ads | None found in Apple's documentation | n/a | On/off on brand terms, geo |

## Platform results and your own numbers

Each platform counts conversions it can see, using its own attribution rules. Its lift study measures incrementality *of that platform's reported conversions*. Three cautions:

- **Self-reported counts.** Platforms such as Google and Meta attribute installs to themselves, which is why their numbers rarely match an MMP's. The App Attribution Guide's chapter on [self-attributing networks](https://appattributionguide.com/self-attributing-networks/) explains the mechanics.
- **One platform at a time.** A lift study on Meta says nothing about overlap with Google. Two campaigns can each show lift while partly reaching the same people.
- **Confidence levels differ.** Read the confidence level on the report and compare like with like; the [results guide](https://incrementalitycalculator.com/learn/read-lift-test-results/) shows why it matters.

Where you can, check platform results against total installs from your own data. A geo test read on MMP totals is a useful second opinion on a platform's study.

Run this on your own data

Platform lift studies grade each platform on its own numbers. Reading them against your MMP's totals, organic included, gives you a second opinion. Linkrunner's free plan covers 25k attributed installs, with no credit card and every feature included.

- [Why Meta ROAS and MMP ROAS do not match](https://linkrunner.io/blog/why-your-meta-roas-and-mmp-roas-don-t-match-and-which-one-to-trust?utm_source=incrementalitycalculator&utm_medium=referral&utm_campaign=learn-incrementality-meta-google-apple&utm_content=panel)
- [Incrementality testing, defined](https://linkrunner.io/glossary/what-is-incrementality-testing?utm_source=incrementalitycalculator&utm_medium=referral&utm_campaign=learn-incrementality-meta-google-apple&utm_content=panel)
- [Create a free account](https://dashboard.linkrunner.io/sign-in?utm_source=incrementalitycalculator&utm_medium=referral&utm_campaign=learn-incrementality-meta-google-apple&utm_content=panel)

## Questions

**Can I run a Google Conversion Lift study on iOS App campaigns?**

Not according to Google's help page as read on 26 Oct 2026, which says App campaigns targeting iOS are not supported. Use a geo test or an on/off test for iOS instead.

**What is the minimum budget for Google Conversion Lift?**

Google's help page states a minimum campaign budget of $5,000 USD and at least 1,000 observed conversions. It also says Conversion Lift is not available for all accounts, so check eligibility in your account.

**Does Apple Search Ads have a lift study?**

We did not find one in Apple's documentation when we checked on 26 Oct 2026. Most teams use brand keyword pauses or regional tests and read them on total App Store installs.

**What is incrementality in app marketing?**

Incrementality is the share of conversions that would not have happened without the ad. It is measured by comparing people who could see the ads with a similar group who could not, so it captures what the ads changed rather than what they were credited with.

**Is attributed the same as incremental?**

No. Attribution credits a campaign when a user touched an ad before installing, even if that user would have installed anyway. Incremental installs are only the ones the ads caused, so they are always equal to or fewer than attributed installs.

**How big should my holdout group be?**

Big enough that the control group collects enough conversions to detect the lift you care about within the time you can wait. Lower conversion rates and smaller expected lifts need bigger holdouts or longer tests; the holdout simulator on this site shows the trade-off.

## More guides

- [01 **What is incrementality in app marketing?** Incrementality in app marketing explained: the share of installs and revenue your ads really caused, how it differs from attribution, and how to measure it.](https://incrementalitycalculator.com/learn/what-is-incrementality/)
- [02 **Holdout, geo lift, ghost ads, PSA and on/off tests** Compare incrementality test types for app marketers: user holdouts, geo lift, ghost ads, PSA and on/off tests, plus how to run a geo lift test for installs.](https://incrementalitycalculator.com/learn/incrementality-test-types/)
- [03 **How big should my holdout group be?** How to size an incrementality holdout for an app: control conversions needed, and how holdout share, install rate and expected lift set the test length.](https://incrementalitycalculator.com/learn/holdout-group-size/)
- [04 **How to read lift test results without fooling yourself** How to read an incrementality lift test: lift, confidence interval, p-value and incremental installs, the mistakes that turn noise into wins, what to report.](https://incrementalitycalculator.com/learn/read-lift-test-results/)
- [05 **Which UA campaigns are cannibalising organic installs?** How to identify which UA campaigns are cannibalising organic installs: brand search and retargeting patterns, a four-step data check, and how to test it.](https://incrementalitycalculator.com/learn/cannibalisation-brand-retargeting/)
- [06 **MMM vs MTA vs incrementality testing** Media mix modelling, multi-touch attribution and incrementality tests compared for app marketers: what each measures, the data needed, how they fit together.](https://incrementalitycalculator.com/learn/mmm-mta-incrementality/)
- [07 **How to act on incrementality results** Turn incrementality test results into budget decisions: incremental CPI and iROAS by channel, moving spend in steps, when to retest, and reading CTV and brand.](https://incrementalitycalculator.com/learn/act-on-incrementality-results/)