You no longer need separate reports on every hardware metric to dispute traffic quality with your advertising partner – instead, just build and show an integrated report on the number of bots. If necessary, you can always go back to reports on any specific hardware metric for a more in-depth analysis.
Emulators and bot and click farms are virtual or physical devices used to imitate a real user’s in-app behavior. One of the simplest and most common fraud tactics, it aims to drain marketing budgets by having advertisers to pay for bots as if they were newly acquired users of the apps.
How bots and device farms are used:
Detecting bots with the naked eye is very difficult. They are similar to active app users and sometimes may even meet your engagement criteria. This is where an anti-fraud system might come in handy. One such system is MyTracker’s Fraud Scanner, which uses hardware fraud metrics to spot bots.
Hardware metrics check device parameters, such as manufacturer, model, screen resolution, and more. For example, that’s how a device that says it’s manufactured by Apple while having the OS or screen resolution of a Xiaomi phone, or belonging to a Xiaomi model range can be uncovered and identified as a bot.
For your convenience, we have merged all hardware metrics into a single one called Bots and Device Farms. It detects fraud using hardware sensors and markers of suspicious and emulated devices.
From now on, you can build an integrated report on the number of bots within the incoming traffic and use it to challenge the budget your advertising partner has come up with. To do this, navigate to Report Builder → Fraud Scanner → Combined Metrics → Bots and Device Farms.
You can still generate a separate report for any metric and export these data using segments.
The new Bots and Device Farms metric is available to premium users of MyTracker. To learn more about our Premium plan, request a free demo here.
The Fraud Scanner team has introduced one more device check for better protection against hardware fraud: a check of the device’s sensors.
For devices acquired through an advertising campaign, Fraud Scanner now analyzes readings from their sensors. So if many devices indicate the same readings from their respective light sensors, the traffic is likely coming from a device farm where they lie next to one another without moving.
Want to learn more about the types of ad fraud and how anti-fraud systems can help you detect them? Check out our ultimate guide to detecting and preventing mobile ad fraud for marketers.