Distinguishing between user inventories vs infected device inventories for ad-fraud estimation.
If you have been working in the ad-tech space, you would often hear people talk about segmented user inventories through which companies in ad-tech space run digital campaigns. You can easily target customers by various segments i.e age, sex, income, geographic making reach of such inventories highly effective and revenue generating.
Often such DMP's are build on years of work, partnerships and running 3rd party campaigns. The art of targeting users based in device ID, GAID's is become very popular among marketers providing ease and scale easily. But often, such device's ID's and GAID's become a problem for consumers as mobile applications which form the end point of publishers to gain new users, often get rigged and consumers are constantly monitored over new app installs, events on various app and even get monitored on call logs.
These user inventories are more of inventories that have incent apps installs, which track these devices for any new activity, and in case of performance based activity, it often gets re-attributed by click injection feeding the top point as in an ad-network for conversions.
Have you ever wondered how a click can be injected just before the install, all this is possible if the device is infected with a malicious app that is serving the purpose to fill clicks for organic traffic or hijack a paid marketing click and replace with a misattributed one.
Data analytics have helped understand the anomalous behaviour, but is often reverse engineered from behind to evade fraud. Our patent pending algorithms are first of the kind, which detects changes in programmatic sequence making it a robust and reliable method to detect any kind of foul play.