Avoiding Bot Installations in Google App Ads
Relying solely on install counts as a goal for Google App Ads often leads to wasted budget because bot farms can easily spoof installations to trigger payouts. These bots mimic user behavior by downloading old app versions from unofficial sources while claiming the Play Store as the installer. To combat this, developers should switch their conversion goals to deeper, harder-to-fake in-app actions. This shift makes the app more expensive for bot farms to target, effectively deterring fraudulent traffic.
key points
Bot farms exploit Google's optimization algorithms by quickly installing apps from saved files and opening them once to count as a conversion. This creates a positive feedback loop where Google sends more ads to the bots because they appear to be highly effective at driving installs.
Discrepancies between ad platform reporting and internal admin panels often reveal fraud, such as multiple installs using outdated app versions that the Play Store no longer serves.
Changing the campaign goal from a simple app open to a specific user achievement, such as winning a puzzle, forces bots to perform complex tasks that are too costly to automate.
community discussion
4 Cautious[consensus]
Commenters generally agree that Google's ad ecosystem is plagued by bot traffic and invalid traffic (IVT), often creating a predatory loop where developers pay for ads that attract bots, only to be banned by AdMob for that same traffic. There is a strong sentiment that Google's internal incentives may prioritize ad spend over fraud prevention, despite claims of world-class anti-spam teams. The discussion highlights a systemic failure where small developers are disproportionately harmed by these automated systems.
top insight
The rise of residential proxy networks—often disguised as free VPNs, movie streaming services, or 'AI' startups—allows bot traffic to bypass traditional IP exclusions by routing through home internet connections. This creates a 'grey market' where unsuspecting users' home networks are used for click fraud and scraping, making it significantly harder for advertisers to filter out invalid traffic using data center ranges.