This report will help you detect the fraud activities and events that are occurring in your application in terms of fraud installs or fraud In-App events.
- The below picture depicts the fraudulent installs that have been blocked for the time being. Realtime shows the data that have been immediately registered. In real-time, before attribution, the installation is identified as coming from a fraudulent media source and is blocked from attribution.
- Post-analysis shows the count after doing some analysis at the backend. For example, there might have been some mistake and the installation that we thought was fraud actually turns out to be genuine so in that case this number will be changed. 0 currently depicts that the analysis so far is true and we have 31 fraud installs. The same goes for Fraudulent costs.
- Fraud identified after attribution is referred to as post-attribution fraud. Post-attribution fraud can be identified on the day of the install, and up to 7 days after (8 days total). Once attributed, an install can't be erased. For this reason, post-attribution fraud is handled differently than real-time fraud.
- We have the above-explained results shown in the trends graph as well.
- Below trend, chart depicts the installs that showed app version mismatch i.e when the specified app version requested for the installation doesn't match the one installed by the user. Blacklist IP is that Trackier has a list at the backend which has some blacklisted IPs and when the same is being used it shows up in the reports. There is another one named Untrusted Device which shows illegitimate installs as they might be from an anonymous IP or carrying an invalid SDK signature.
- The fraud Report table shows the rejected installs and the rejected amount (Cost) for each day of the selected date range.
For In-App Events
- For In-App events, the same gadgets are being displayed as that for installs except they are events.
- You can filter out the data of the report based on geolocation, agency, partner, and campaign and can have additional attributes for grouping data.