Identifying fraudulent display ad traffic to improve ROI
Enbrite.ly's Fraud detection for display ads detects and uncovers fraud & non-human traffic (NHT) that negatively affects the composition of your visitors and your dvertising ROI.
You name any KPI - there is a way to artificially manipulate it, and there are thousands of people making a living out of doing exactly that.
The first step towards a well spent digital budget is making sure that you actually reach the target audience you pay for.
What we detect
One in 20 web users infected with ad injection software. We’re able to spot ad injection coming from toolbars, adware, and malware. A troubling phenomenon for users and publishers alike, and advertisers can also count on damage to their brand as users associate it with cybercriminals.
61.5% of all web traffic actually consists of automated bots according to figures put together by Incapsula. We're able to detect compromised computers that masquerade as real users. They steal your ad budget and inflate your KPI’s as they interact with your ads in invisible browser windows.
Specially crafted ads and iFrames let fraudulent publishers serve invisible ads that artificially inflate their impression numbers. How useful can your ad be a score of other ads?
Arbitrage is impression laundering writ large. The savvier fraudsters we observe buy cheap, low quality traffic, mask its origin, and use it to serve higher paying ads to uninterested users. We’re able to catch this so you can get the traffic quality you actually pay for.
How it works
Using our proprietary methodology, we identify and filter out site traffic that is not useful and carries no business potential. Based on different signals we determine whether a site visit or banner impression comes from an actual human or from fraudulent activity carried out by organized human or bot actions. While the former can be nurtured and nudged towards actions carrying financial benefits, the latter should be eliminated from your system.
Our tracking code measures user interactions at the session level. We track and analyze mouse movements, clicks, and other metrics with an ever-evolving ruleset. We then pit each session (with utmost respect for privacy) against other sessions in the same campaign to reveal outliers: user sessions that deviate from the patterns we identify as normal. These statistics let us pinpoint fraudulent traffic sources: publishers, ad placements, ad zones, or affiliate partners with large amounts of traffic or clicks that we suspect are artificial. We look for many artificial traffic and click generation practices, ranging from arbitrage and cookie stuffing to adware and botnets.