Yesterday, I reported that One of Uber’s Lawsuits Against Ad Fraud Has Come Full Circle – They Won. In the court documents, the following detail was noted “Defendants engaged in similar mobile advertising fraud with at least three other nationally known companies.” It should be clear that ad fraud didn’t just impact Uber; it continues to affect all advertisers spending money on digital ads. The fact that ad fraud exists and that it is large is not the subject of this article. The purpose of this article is to arm marketers with the knowledge of where to look and what to look for so they can determine for themselves whether they’ve been harmed by fraud.
I am not a lawyer, and this is not legal advice. But I have studied the problem of ad fraud for a long time, its parallels with many other forms of crime, and the successful and ongoing lawsuits against fraud. The fact that there are no specific laws against digital ad fraud means plaintiffs must bring suit on the basis of other laws that do exist. What follows is a collection of examples and publicly documented cases that marketers can learn from and take action on their own.
Where to Start to Look for Fraud
If you’re getting monthly or quarterly excel spreadsheets as reporting from your media buying agency, you’re not going to be able to find fraud. They are simply not detailed enough, and fraud hides easily in averages. Many marketers do not get, or do not use, detailed placement reports of where their ads ran [1]. So they cannot see the fraudulent sites and apps that are eating up their programmatic impressions. Even if the marketer pays for fraud verification technologies, those spreadsheets usually report numbers — like 15% IVT (invalid traffic) — and not the domains and apps that caused the fraud; so the marketer cannot take any action, except to try to get a refund. Getting refunds is problematic in and of itself [2]. And finally, note that even if you get placement reports, they might have been falsified or fabricated. The details from the several Uber lawsuits against mobile exchanges accused the ad tech vendors for 1) falsifying the reports to make it appear that ads ran on legitimate sites, when the ads ran on porn sites or long tail sites instead, or 2) fabricating placement reports to make it appear that ads ran, when no ads were served at all.
Look for Discrepancies Between Data Sets
Assuming you get detailed reports for various programmatic things you pay for, you can do the following analyses yourself — look for discrepancies. These are just a few simple-to-explain examples; there are many more not discussed here. If you take your DSP report which tells you the number of bids won, by domain, you can compare that to your ad server report, which tells you the number of ads served, by domain. Normally, when an advertiser wins a bid, they get to serve an ad — it’s supposed to be 1:1. A 1-5% discrepancy is acceptable; but if you see a 10%, 20%, or even 100% discrepancy, you should dig in. The 100% discrepancy means there were no ads served for all the bids won, and you paid for. Whether it was fraud or not, your ads were not served, so you should try to get that fixed.
Next, if you compare your ad server reports to reports from verification tags, by domain, those numbers should match up too, if the ad was served from the ad server and the ad arrived in the user’s device and was rendered on-screen for the user to see. You’d be surprised at how many ads are served, but never arrive in the device to be displayed. This problem is particularly bad in mobile, both because wireless bandwidth is smaller, and because the user already scrolled past the ad slot by the time the ad is displayed/rendered. Another common place to look for discrepancies is in the number of clicks the campaign dashboard reports to you versus the number of clicks that actually arrived on your site, as reported by Google Analytics on the site. If there are large discrepancies between these two things, something’s wrong and you should look into it. More details and sample charts in this article: Look For Drop-Offs In Your Digital Campaigns.
If They Keep Telling You They’re Transparent
You can also look for discrepancies in…
