Mobile Click Fraud

According to a new study by Trademob, online click fraud is a problem for advertisers, and click fraud on mobile ads is already quite well developed. The study, looking at six million mobile ad clicks, served across ten different ad networks, showed that 40% of mobile ad clicks are either accidental or fraudulent.

These paid-for clicks were found to be completely worthless showing a conversion rate from click-to-download of below 0.1%. Further analysis showed that 18% of these were highly indicative of click fraud and 22%

Click Category Based on After-Click Conversion Rates


% of Mobile Ad Clicks



Useless (click to install 0.1%)


Source: Trademob, September 2012

About half of those clicks show patterns that are symptomatic of click fraud, such as traffic that peaks at unusual times of day or a bulk of clicks coming from similar IP addresses. The rest appear to be accidental clicks, perhaps due to the “fat fingers” syndrome or poor user interface design, says the report.

With 40% of clicks, the study found that the conversion rate of clicks-to-installs was less than 0.1%. These clicks, it concluded, were accidental or fraudulent.

The report suggests that publishers who generate a large number accidental clicks could be poorly designed. And, regarding outright click fraud, the researchers found that both simple techniques, where publishers report clicks that never happened, as well as more sophisticated techniques, are being used on mobile ads. The more complex techniques include botnets, in which fraudsters marshall an army of zombie computers, modified to look like mobile devices to ad servers, to click on ads.

Sources of The 40% Useless Mobile Ad Clicks


% of Clicks

Server-side fraud (plain)


Botnets & client-side fraud (sophisticated)


Accidental clicks


Source: Trademob, September 2012

Client-side fraud is another other type of more sophisticated technique, says the report, involving deceptive banners, perhaps hidden behind another element on the website, utilized to trick users into clicking on them.

The report concludes by noting that all of those types of fraud can be detected, though, by analyzing traffic patterns such as lots of clicks at odd times, or a bulk of clicks from similar IP addresses, or lots of clicks coming from geographies that aren’t targeted in the ads. Currently, fraudsters aren’t employing sophisticated evasive maneuvers, because few advertisers or networks are aggressively blacklisting publishers.

To access the Whitepaper from Trademob, please visit here.



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