How to Use Click and Touch Charts in FouAnalytics

Over the years, I have published examples of how to use FouAnaytics to check clicks and touch events and see if they were real (from humans) or bots. The slide below shows three screen resolutions (1920x1080, 1366x768, and 1440x900) in landscape and two in portrait (360x640, 375x667). These were desktop monitors and laptop screens vs smartphone screens, respectively. By plotting the x,y coordinates of the clicks you can see what appears to be normal human clicks as they navigate the page. On the lower right, in red, you will see what appears to be bot clicks -- repeated clicks on the same x,y coordinates result in larger red circles (overlapping clicks). It's hard to get a whole bunch of humans to coordinate their behavior and click on the exact same pixel location on screen, right? So having detailed click patterns gives you an additional level of detail not available in Google Analytics or Adobe Analytics, so you can determine if clicks are real and troubleshoot issues as they arise.

Clicks and touch events in ads should make sense too. In the example to the right, a standard 300x250 ad has touch events. Note where the [x] to close the ad is located (upper right). Note where many of the touch events occurred -- right side, tended to be upper right corner. Does this detail give you some indication of whether the user was trying to click the ad or trying to close it? Right. Having this level of detail allows you to use common sense to tell you if things are working as they should. Another example below shows touch events (left) and clicks (right, in green) on a 300x250 ad unit. These are scattered across the entire 300x250 pixel area of the ad, which indicates the users were trying to click on the ad, not trying to close it.

By combining the techniques above to get a sense of whether clicks are real, and the blue and red labeling from FouAnlaytics -- humans vs bots, respectively -- you can determine whether your digital ads are delivering humans or bots to your site. In the two examples below, you can compare the relative quality of the clicks arriving from your various paid channels, and the relative quantity of clicks too. Obviously you want less red (bots) and more blue (humans). With FouAnalytics data, even if you don't have closed-loop data on sales and business outcomes, you can still optimize your ad spending by allocating more budget to channels that are sending more blue clicks and away from channels sending more red clicks. The second chart below shows you how three paid display sources compare to each other, two paid search, two paid social, and a native provider.

As I have said before, FouAnalytics is analytics, not just fraud detection. It gives you the details you need to see and understand what is going on and to troubleshoot any problems yourself. Fraud detection tech that just gives you a single number like -- 9% IVT -- does not give you enough details to understand what is happening let alone troubleshoot anything.

You are welcome to us FouAnalytics to "see fou yourself" and find the fraud that other detection vendors missed. You did the best you could with those tools that you had previously. With better tools, you can take more control of your analytics and your digital marketing.

With FouAnalytics, you can even tell which hand users were holding their smartphones in. See the charts below. Which hand do you think most people were using?