How Ecommerce Advertisers use FouAnalytics

More and more ecommerce sites are using FouAnalytics to check the quality of their ads and the quality of the visitors that arrive on their sites organically or from paid media sources. Here are some examples of how ecommerce advertisers use FouAnalytics by placing an on-site code on their pages, next to Google Analytics or Adobe Analytics.

Optimize among paid media sources

Once an ecommerce advertiser places the on-site FouAnalytics tag, they will be able to see the quality of the clicks arriving from various sources. Any url that contains UTM_SOURCE, UTM_CAMPAIGN, and UTM_MEDIUM will be automatically parsed into data grids like the following.

The percentage number at the top gives you a sense of what percentage of your pageviews have a UTM_SOURCE, which implies it came from paid media campaigns. In the example above, 28.8% had UTM_SOURCE. In that data grid, the rest of the numbers and rows are a breakdown of the values for example UTM_SOURCE=facebook, UTM_SOURCE=gclid, etc. "gclid" means "google click ID" which implies paid search. Under each row, you will see the color coding - dark blue versus dark red. This gives you a quick way to identify the sources that are problematic (have more dark red than others). This helps you drill down into which sources you need to investigate and take action on.

The action that can be taken is to allocate more budget to channels that are sending more dark blue clicks and less dark red clicks.

Below is a larger sample of paid media channels, where we can see the relative quality of clicks coming from ads on the main properties versus ads on the respective audience networks. Be sure to turn off audience networks and audience extension to minimize the obvious fraud.

Relative attentiveness of human visitors

If an advertiser has already optimized their campaigns away from fraud (dark red) and towards humans (dark blue), FouAnalytics on the ecommerce site can further help them assess the relative "attentiveness" of humans arriving on the site from direct, organic, or paid media. This is particularly useful for paid social where Facebook, TikTok, Twitter, YouTube, etc. don't allow any third party javascript tags to be used to measure the ads themselves. In most cases, if you turn off Facebook Audience Network for Facebook ads, Google Video Partners for YouTube ads, search partners for Google search ads, and Pangle for TikTok, you would have avoided 90% of the obvious fraud (from those respective audience networks). So the clicks you are getting are already highly dark blue (humans). The next question is whether those humans that arrived on your site are "attentive" -- i.e. they went on and did something on your ecommerce site.

For example, did they move the mouse, scroll the page, click something, etc. You can use the Clicks tab in FouAnalytics to assess this. The clicks are automatically color coded for you (dark blue, dark red, etc.). And they are grouped by screen resolution -- e.g. 1920x1080 for desktop, 360x800 for mobile, etc. The top 10 most prevalent screen resolutions are displayed. But you can isolate any screen resolution manually for inspection by using the following filter -- video:1920x1080, etc. Notice in the example below, there is mousemove in 99% of the pageviews, and clicks in 93% of the pageviews for the screen resolution 1920x1080. Since this is a desktop monitor, there are no touch events expected.

The percentages next to each screen resolution gives you a sense of the prevalence of clicks, mousemoves, and touch events (for mobile, mostly). These collectively tell you the attentiveness of the users that came to your site. More advanced FouAnalytics practitioners take these percentages and compare them to direct traffic (yellow highlight in the 5 examples below). This tells them if the visitors from paid channels over-index or under-index visitors that came directly to the ecommerce site. This way, the ecommerce advertiser can further optimize their budget allocations between different paid media channels to get the highest percentage of visitors that are human (dark blue) AND "attentive" -- i.e. went on and took some action on the ecommerce site.

Let me know if you have any questions and if I can help further.

Further reading: 613 other articles with screen shots and examples from FouAnalytics practitioners