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Now that I’m back into the swing of things again I wanted to continue the series that I began last year on risk. Towards the end of last year I covered the different business models that are evident in the domain industry. This article will begin to explore the risks associated with the traffic model and how those risks can be minimized.
 The fundamental business model underpinning traffic is made up of two parts:
Traffic – people viewing a web page.
Advertisers – who pay for clicks on their links
The domainer earns money through the following forumla:
Traffic x Click Through Rate (CTR) x Earnings per Click
During the next few articles I'm going to pull apart this formula from a risk perspective and outline some of the challenges that the traffic domain business model presents. The above definition of traffic is actually not what is used in the domain industry. In fact, one of the problems that the domain industry has is that there is no clear definition of what exactly is traffic.
The reason for this is that there has been an enormous economic incentive for unscrupulous business people to fraudulently generate traffic. In their efforts to combat this fraud the domain industry has developed a large variety of definitions around traffic.
To outline the problem a little further if a “piece of traffic” visits a domain is that “piece of traffic” a genuine human, a robot (ie. software application) or a user farm (ie. people in India paid to create traffic). This is to just three of the possibilities that may or may not generate traffic.
If you’re a domain parking company that takes in traffic and helps match that traffic to advertisers then you want to ensure that your traffic is genuine, real humans that are really surfing the net. The problem is that unless they can spy on a person in their living room or work place then they can’t really know if the traffic is real.
To combat the fraud and to way the odds towards genuine traffic parking companies have defined traffic as an IP address visiting a parked page once every 18-24 hours. This is the really simple version of the definition as there is also a lot of sophisticated algorithms that help determine genuine versus fraudulent traffic.
This also means that a lot of traffic is not being credited as being genuine. For example, many government institutions, schools, businesses etc use what is known as network address translation and route all their traffic via single gateway IP addresses. Even though there may be a great number of users behind a single IP address they are still regarded as one as far as many of the anti-fraud systems are concerned.
So how does this all relate to risk? If you purchase a domain on the basis of a certain level of traffic you need to ensure that the traffic is real and also acknowledged as being real by one of the parking providers. A domain with 3000 uniques per day from a few IP address can very quickly diminish to just a few uniques thereby leaving you way out of pocket!
The next article will explore additional aspects of traffic that can potentially increase the levels of risk for the unwary.
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