- Solutions
Click Fraud ProtectionBlock invalid clicks across every ad channel.
Smart Bidding ProtectionFeed Google clean, human-only signals.
Clean Remarketing AudiencesExclude suspicious traffic from your lists.
All FeaturesEvery ClickPatrol feature in one place.
E-commerce & RetailProtect shopping campaigns and product feeds.
Service ProvidersStop wasted spend on local & lead-gen ads.
Mobile App ProvidersProtect app install and in-app ad campaigns.
Marketing AgenciesShow clients real, reportable media savings.
All IndustriesBrowse click fraud protection by industry.
Small BusinessAffordable protection that pays for itself.
EnterprisesScale protection across brands & accounts.
Regional CompaniesKeep local budgets on real, nearby buyers.
MultinationalsConsistent protection across every market.
- Resources
- What is Click Fraud?
Learn what fake PPC clicks are and why they matter.
Bot TrafficDetect and block non-human clicks.
Competitor FraudStop rivals draining your budget.
Sophisticated FraudCatch SIVT that native filters miss.
Click FarmsStop coordinated low-quality click operations.
Invalid TrafficBlock every click that never converts.
FAQAnswers to the most common questions.
BlogArticles and guides from our expert team.
ComparisonsClickPatrol vs ClickCease and other tools.
ToolsFree tools by ClickPatrol & Friends.
About ClickPatrol™Who we are and our mission.
Case StudiesWhy agencies and businesses use ClickPatrol.
Customer ReviewsReviews and success stories from customers.
Partner ProgramJoin our affiliate & partner program.
Contact usTalk to our team about your ad traffic.
- Pricing
Early results · Alpha test
29% of ad spend saved by blocking 8% of traffic
In Alpha testing, ClickPatrol screened 18,311 clicks and showed how blocking a small share of high-risk traffic can reclaim a much larger share of spend.
Alpha testing cohort
During early Alpha testing, ClickPatrol screened every click against hundreds of behavioural and technical signals, then estimated savings from blocked high-risk traffic.
This page explains the method and the headline result from that test cohort. It is an early results study, not a named customer story.
The challenge
Advertisers needed a clear way to see how much budget was lost to fraudulent and unwanted clicks, and what recovering that spend looked like in practice, without guessing from incomplete block lists.
The approach
Each click was scored and placed into a risk category: Safe, Low, Medium or High. High-risk IPs were blocked automatically. Savings used blocked clicks, predicted repeat-click behaviour by risk level, and effective CPC.
- Screened clicks across hundreds of characteristics
- Classified traffic by threat level
- Blocked high-risk sources automatically
- Estimated savings as blocked clicks × predicted repeats × eCPC
The results
In the Alpha phase, 18,311 clicks were screened. With an eCPC of €0.10, blocking only 8% of unwanted and fraudulent traffic saved about 29% of ad spend in the test set (around €209 of €1,830).
- 29%Ad spend saved
- 8%Traffic blocked
- €209Saved in test
- 18,311Clicks screened
