Motion and Orientation in FouAnalytics
Advanced FouAnalytics practitioners know that humans can't hold a phone perfectly still when using it. So motion and orientation data from mobile devices are captured and analyzed (see a few sample 3D plots below). I'm not going to give away what we specifically look for in this data to tell apart humans and bots. But I can see you, bots.
Bots DO fake motion and orientation, just like they fake page scrolling, mouse movement, and touch events. But historical data allows me to tell apart what is faked and what is real. It's hard for botmakers to fake motion and orientation correctly to fool FouAnalytics.
Let me re-emphasize that this data alone is not sufficient to label bot or not. But it sure is helpful as supporting data so we can understand why something was marked "invalid" or not invalid, just like the click patterns we showed previously -- https://www.dhirubhai.net/pulse/how-use-fouanalytics-scrutinize-clicks-from-programmatic-fou
Does your legacy fraud verification vendor provide you with details like this, so you can understand why something was marked invalid or valid? I don't think so. Happy bot-hunting y'all ... and more importantly, happy optimizing your campaigns with better analytics... hint, hint ;-)
Further reading: 614 more articles on digital marketing, ad fraud, and analytics
Ad-Fraud Investigator & Media Expert, member of Digital Forensic Research Lab cohort "Digital Sherlocks" - Adding some fun when asking unexpected questions you were not prepared to hear
1 年We always recommend a deep dive into the data stream. Why? Because humans see more than tools. With #fouanalytics we have been able to identify ad-slot issues on publisher's side and help him fix these issues. Otherwise legacy fraud verification would have blocked legit and good publishers, while marked MFA sites as safe.