Click Spamming is probably (and unfortunately) the easiest way to commit attribution fraud. 

Over $1.6bn is wasted on Fraud, based on Appsflyer “State of Mobile Ad Fraud” and making it a lucrative business for fraudsters. Cannibalizing rather than creating incrementality.

Mobile app marketing requires marketers to use 3rd party tracking platforms to track the performance of their campaigns. Mobile tracking platforms attribute installs to the vendor generating the last click in what is called: “Last click attribution”. 

Fraudsters learned that if they could spam these services with clicks - they would “win” an attribution match if the user goes and installs the app for which clicks were being generated. 

How Do They Do It ?

Using DSPs

The most common way for click spamming is using a demand side platform (DSP), buying inventory for cents, while calling an attribution service click URL for each impression bought. 

This method is such cunning that it allows fraudsters to provide Advertisers with reports showing that traffic has been acquired, sometimes using known publishers, to make the reports seem legitimate.

Javascript Click Storm

The caveat of click spamming is that it depends on the user actually downloading the specific app the fraudster is spamming clicks for. Fraudsters are too malicious to take a risk. If you’re a fraudster - you would think: why trigger a click for one app, when I can trigger clicks for dozens of apps at the same time ?

Fraudsters use a javascript tag, buying inventories through DSPs, allowing them to serve the script with impressions (thus triggering dozens of clicks for each impression) - or - by triggering the javascript upon a user click, where instead of causing 1 click url to be called, the user appears to have clicked on a dozen ads - hence, increasing the chances of winning the attribution claim.

Ways to Spot Click Spamming:

Luckily for Advertisers - Click Spamming is probably the easiest method of fraud to catch. 

As Fraudsters rely on blasting users with click triggers, relying on one of these clicks being the last before an app install - any marketer, powered with excel and a pair of eyes can spot click spam.

Here is an example of normal distribution click to install time:

Relying on a large amount of clicks, click spam distribution is almost flat:

We created a free excel template for you, found here: Click Spam Template

INCRMNTAL is an incrementality platform helping marketers measure the value of their marketing spend. Fraud has no value to Advertisers. 

If you want to learn more, visit INCRMNTAL or book a demo today!