ClickMoat

The platform monitors incoming clicks in real time, analyzing traffic patterns, device signatures, behavioral signals, and IP characteristics to identify and block fraudulent clicks before they consume advertising budget.

The detection engine uses machine learning models trained on large-scale click fraud pattern data to identify sophisticated fraud that evades rule-based blocking systems, catching bot traffic that attempts to mimic legitimate user behavior and invalid clicks originating from residential IP addresses that simple IP blacklists would miss.

Real-time blocking is implemented at the campaign level, adding IP exclusions directly to connected advertising accounts when fraud is detected to prevent continued spend on fraudulent traffic sources.

ClickMoat provides advertisers with detailed reporting on blocked fraud by type, source, and magnitude, quantifying the budget protection value delivered and revealing patterns in the fraud activity targeting their campaigns.

This transparency helps advertisers understand the scale of the invalid traffic problem in their specific campaigns and markets, supporting informed decisions about fraud prevention investment and providing evidence for refund claims from advertising platforms that offer invalid click credit policies.