Fake users/installs
Аraudulent or artificially generated engagements (installs, clicks, or in-app actions) designed to deceive advertisers, MMPs (Mobile Measurement Partners), or ad networks into paying for non-genuine traffic. These are commonly used in mobile ad fraud schemes to steal marketing budgets or inflate performance metrics.
Definition of Fake users/installs
Fake Users and Fake Installs refer to fraudulent, non-human traffic generated by malicious actors to falsely claim Cost Per Install (CPI) or Cost Per Action (CPA) payouts from advertisers.
In mobile user acquisition, a fake install occurs when an app is downloaded and opened not by a genuine person interested in the product, but by automated scripts, botnets, or manipulated hardware. Because these “users” will never make an in-app purchase, engage with the app, or generate Lifetime Value (LTV), they act as a direct drain on marketing budgets.
Why fake users and installs are a problem
Fake engagements are a core element of mobile ad fraud. They drain advertising budgets by generating paid actions that provide no real value. Fraudsters often employ automated tools, scripts, or emulated devices to create installs, clicks, or in-app events that appear legitimate. As a result, campaigns may seem more successful than they actually are, misleading advertisers about performance and ROI.
This type of fraud is particularly harmful because it not only wastes budget but also contaminates analytics data. By inflating metrics, fake traffic can distort insights, making it difficult for marketing teams to understand which campaigns, channels, or creatives are truly effective.
How fake traffic impacts performance
The presence of fake users and installs can have multiple negative effects on campaign performance:
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Distorts user acquisition costs by including non-genuine activity.
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Compromises ROI calculations and campaign optimization.
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Skews attribution, making it harder to identify high-performing traffic sources.
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Reduces long-term app growth potential by directing spend toward non-valuable activity.
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Inflates engagement and retention metrics, giving a false sense of success.
Fake traffic can also erode trust in advertising platforms, making it more challenging for marketers to justify budgets and plan strategies effectively.
Detecting and preventing fake users
To combat this issue, advertisers and MMPs rely on fraud detection solutions that analyze behavioral patterns, device data, install velocity, and post install activity. Signals such as rapid, identical actions, impossible device characteristics, or abnormal geographic clustering often reveal fraudulent behavior. Monitoring these patterns helps ensure that marketing spend goes toward real users who contribute genuine value to the app or platform.