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Performance Max
Fake installs

Stop fake installs on Performance Max App campaigns

When Performance Max is used for app promotion, fake installs corrupt your cost-per-install metrics, poison the audience signals that drive Smart Bidding, and make your app campaign appear to perform far better than it actually does.

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Tiffany & Co.
Adidas
Azadea
Punt Roma
Salsa Jeans
Sunglass Hut
Virgin Megastore
Decathlon
Honda
Lexus
Mercedes-Benz
On
TOD
Toyota
Volvo
Dominos
STC
Porsche
Almosafer
Infiniti
Marks & Spencer
LEGOLAND
du
Cleveland Clinic
Nissan
Boggi Milano
Kiko Milano
Hyundai
Chevrolet
Aape
Kiabi
Watsons
Maje Paris
Sandro
Ted Baker
ACE
Tawuniya
TOEFL
Regit
You.gr
Spitishop

Fake installs teach Performance Max to optimize toward an audience that does not exist

Performance Max for app promotion runs across Google's full network: Search, Display, YouTube, Gmail, Play Store, and Discover, making it one of the broadest app install campaign types available. Smart Bidding for app campaigns learns from install signals to find new audiences likely to install and engage with your app. When fake installs are injected into that signal stream, Smart Bidding develops a model of your ideal user that is partially or entirely fictional. It then allocates budget toward audience segments resembling invalid installers, producing more fake installs and compounding the problem over time.

Fake installs on PMax app campaigns arrive through several mechanisms. Click flooding generates hundreds of invalid clicks before a real user installs organically, intercepting attribution credit. Device farms use real physical devices to simulate genuine installs, complete with post-install events designed to pass basic invalid traffic filters. Because PMax for apps is a single unified campaign with no channel-level breakdown, advertisers cannot easily identify which placements are producing invalid install volume without external tooling. Tapper integrates with your MMP to cross-reference install attribution against behavioral signals, identifying invalid installs before they corrupt your bidding model.

How Tapper stops fake installs on Google performance max

Three steps from connection to clean campaign data, no engineering required.

01

Cross-reference install attribution with behavioral signals

Tapper connects with your MMP to analyze every install attributed to your PMax app campaign, comparing attribution data against behavioral and device signals to identify invalid installs.

02

Flag fake installs before they reach Smart Bidding

Invalid installs are identified and excluded from the conversion signals your PMax campaign uses for Smart Bidding optimization, preventing the algorithm from learning toward fake audiences.

03

Clean your cost-per-install reporting

With fake installs removed, your CPI reflects the true cost of acquiring real users. Smart Bidding receives accurate audience signals and optimizes toward genuine high-value installers.

Fake installs on Google performance max by the numbers

Data from Tapper's platform analysis and published industry research.

0%

Of PMax clicks estimated to be invalid, exposing app campaigns to attribution abuse

0%

Of PMax advertisers have no invalid traffic monitoring for app campaigns

0x

ROAS lift reported after removing invalid traffic from PMax campaigns

0%

Tapper false positive rate on install attribution analysis

Tapper vs Google's Built-in Detection

See exactly where the gaps are, and why they matter to your performance max performance.

Capability
Tapper
Google's Built-in Detection

Fake install detection

Behavioral and device analysis cross-referenced with MMP attribution data

Basic device signal checks; real-device fake installs pass through

Smart Bidding audience protection

Excludes invalid installs from bidding model learning signals

All attributed installs influence Smart Bidding optimization

MMP integration

Works alongside AppsFlyer, Adjust, Kochava, Singular, and Branch

No integration with third-party MMP traffic analysis

Post-install event verification

Analyzes in-app events for invalid traffic patterns beyond install level

Detection limited to install-time signals

CPI data accuracy

Reports true CPI from verified real installs only

CPI includes fake installs, understating true acquisition cost

Case studies

Leading brands growing with Tapper

See how companies are protecting their ad budgets and improving ROI with Tapper.

Mindshare, a WPP Media Brand logo

13%

lower CPA

8.6%

higher order rate

“Tapper played a key role in improving the efficiency of Du's performance marketing activity by addressing traffic quality issues within campaigns. Following implementation, Du achieved a 13% reduction in CPA and an 8.6% increase in order rate, demonstrating a clear improvement in conversion quality and overall campaign effectiveness.”

Joseph Elbcherrawy

Joseph Elbcherrawy

Client Leadership Director, Mindshare, a WPP Media Brand

Read the case study→
WPP Media MENA logo

40%

higher conversion rate

“When we take low-quality traffic out of the funnel before it reaches the algorithm, the campaign optimises against cleaner signals and the efficiency comes through quickly. For AMA Nissan, that was a 40% lift in conversion rate and a lower CPA on Google, with nothing else in the setup changing. That is the kind of result we want to offer clients as a matter of course.”

Sohail Khan

Sohail Khan

Senior Performance Manager, WPP Media MENA

Disrupt.com logo

20%

lower CPA

Up to $50K

saved per year

“We've been using Tapper for over a year now, and it has become a core part of how we run paid media. Invalid traffic was always something we knew existed but couldn't really act on. Tapper changed that. We're now saving up to $50K per year, and on PureSquare specifically, we saw around a 20% decrease in CPA. Based on these results, we decided to roll it out across other ventures under Disrupt as well.”

Nurkan Kirkan

Nurkan Kirkan

GTM Consultant / Paid Growth, Disrupt.com

Trusted by leading brands worldwide

Infiniti
Dominos
TOEFL
STC
Public Group
Almosafer
Porsche

Frequently asked questions

Everything about fake installs on Google Ads performance max.

PMax app campaigns use install signals to build an audience model for Smart Bidding. Every fake install tells the algorithm that a particular device type, demographic profile, or behavioral pattern is associated with app installation. Smart Bidding then seeks more users who resemble those invalid profiles, driving spend toward audiences that are unlikely to produce genuine users. The longer fake installs go undetected, the more deeply corrupted the bidding model becomes.

Yes. Tapper integrates with major mobile measurement partners including AppsFlyer, Adjust, Kochava, Singular, and Branch. For PMax app campaigns, Tapper adds an additional invalid traffic detection layer that cross-references install attribution data against behavioral signals. This catches invalid installs that pass your MMP's built-in filters, particularly device farm installs and attribution manipulation through click flooding.

Exactly. Fake installs inflate your install volume and reduce your reported cost-per-install, making the campaign appear to be achieving strong efficiency. This can lead to increased budget allocation toward a campaign that is actually producing few real users. When the fake installs are eventually removed from attribution, the true CPI is often significantly higher than what was reported, and the real user base is smaller than the install count suggested.

Other invalid traffic types on Google Ads performance max

Performance Max campaigns face multiple invalid traffic threats. Tapper protects against all of them.

Competitor clicks

On Performance Max →

Stop fake installs on your Google performance max

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