Fraud metrics show key indicators of fraudulent attacks, for example, short click to install times, clicks from suspicious IPs, etc.
Metrics are organized into the following groups:
Based on these groups, we built Combined metrics comes in handy when you first analyze to detect strict, confident and soft fraud.
All indicators are available under the Basic or Premium plan the next day after the user has installed an app or visited your website. See the most accurate data on the third day.
Combined metrics are convenient at the initial stage of fraud-monitoring, allow to estimate indicators in general and, if necessary, proceed to the analysis of specific metrics.
Combined metrics include the following:
A detailed description of these metrics is given in the Selectors section
The type of combined metrics (strict, confident, soft) depends on the detected fraud indicators. Strict fraud is devices with precise fraud indicators, for example, Suspicious Devices. While Confident and Soft fraud will get more devices, including those metrics that do not always guarantee 100% frauds.
Combined fraud for mobile apps
Combined fraud for websites
Metrics, that allow you to detect fraud from the hardware properties:
Hardware fraud includes the following metrics:
A detailed description of these metrics is given in the Selectors section (Premium metrics description is not available for the Basic plan)
Metrics that indicate fraud in the stage of user interaction with ads and until the app install. Based on the abnormal arrangement of clicks and impressions, we can conclude that we are dealing with a fraudulent device, or that the advertising partner is trying to cheat.
Click metrics are strongly intercorrelated, and abnormal indicators for one of the metrics lead to aggravation of the others.
Click metrics include the following:
A detailed description of these metrics is given in the Selectors section (Premium metrics description is not available for the Basic plan)
Metrics that allow you to recognize a fraud by user behavior after installs, based on abnormal behavior at launches, purchases and other in-app events. Besides, you can track the number of mobile devices with fake data acquired during ad campaigns.
In-app fraud metrics include the following:
A detailed description of these metrics is given in the Selectors section ( only for users with premium access to Fraud Scanner)
Metrics that allow you to detect fraud that's typical for websites: active use of proxy, abnormal size of the viewport, or suspicious browsing behavior.
Web fraud metrics include the following:
A detailed description of these metrics is given in the Selectors section ( only for users with premium access to Fraud Scanner)
