Filters | Web Traffic Fraud.com

There are several companies who are working on developing products that can easily identify web traffic fraud or Click Fraud. Some of these solutions essentially need the co-operation of the advertising networks, and so these firms are trying to develop a good rapport with these networks but are met with resistance for obvious reasons. Broadly solutions are available that tackle web traffic fraud. They can be classified into two groups:

1. Forensic Analysis: These rely on an analysis of the log files in the web server of the advertiser. This will give a detailed idea about factors such as where the traffic originated from and what was the subsequent behavior of the traffic after reaching the landing pages. Since these tools use the normal industry wide log files, advertising network companies such as Google can independently verify the data that comes up from this analysis. The flip side of this method is that the people who actually do the forensic analysis should be reliable and have a high degree of professional ethics and honesty.

But realize that short of a court order you will never see a Google traffic log file. So the burden of proof lies on the shoulders of the advertisers with no real leverage to enforce the findings of fraud.

2. Third party Tools: There are web-based solutions that can be used to tag the ads. This involves the use of a JavaScript or a tiny single pixel image on the landing page of the advertiser. Cookies can be used to collect information about the visitor into a third party storage location and while doing an analysis of web traffic fraud this can be downloaded and analyzed. These products range from simple raw data of traffic to be further analyzed to higher end scrapers and filters, which highlight clicks that seem to not originate from a genuine buyer. It is very easy to add false information to the log files (user agents, IP addresses etc.) of the advertiser’s web server and therefore a third party storage of data (third party fraud auditing service) is more reliable and acceptable to an advertising network. However caveat is that if the fraud originates from or is directed against a publisher then these solutions may not be easily able to trace the pattern as they are focused on a single advertiser alone and see only a small part of the entire traffic volume.

Thus these solutions reach conclusions based on a snapshot of data thereby increasing the possibility of a wrong diagnosis and false positives.

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