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In recent articles I’ve touched briefly on Click Through Rate (CTR) but in reflection I haven’t done CTR justice. Considering that it’s a major component of the formula that contributes to our revenue line it is definitely worth looking at further.
So what is Click Through Rate and how does it impact our income? For a start CTR is defined as the total number of clicks divided by total traffic for the domains. For example, if I had 10 clicks and 100 uniques viewing a domain then the average CTR is 10%.
 This sounds quite obvious but we need to unpack a few things here. For a start CTR is measured across time and this means that for some domains they may get a 50% CTR on Monday but only 10% on Friday. To truly exploit the potential of CTR we need to be aware of these trends and spikes. It also means that whenever we view CTR we are actually looking at an average click through rate across time and not a CTR at a particular point in time.
The next thing we need to examine is who counts the clicks and are they reporting them all? In most cases clicks are counted and reported by the parking company. What happens if Google/Yahoo don’t count the click is there then negative clicks that need to be clawed back? This is a distinct possibility.
One of the first things that a domainer needs to find out from their parking partners is the definition for what is a click. You’ll soon discover that the a click has very little to do with a user actually clicking on a link and more about how to best interpret this activity.
To illustrate a little of the problem, how does a parking company determine the difference between a robot click and a human click? Normally this is done with a combination of an IP address look-up with a cookie. Across what point of time are IP addresses renewed so that humans aren’t falsely identified as robots? What happens if a user has their privacy settings set high for their browser and cookies are rejected? All these questions create major headaches for parking companies and in their sophisticated traffic filtering algorithms mistakes sometimes happen.
I remember about 3 years ago I was analysing my stats at a particular provider and I found that they were dropping in almost a linear fashion. Due to the shape of the graph I came to the conclusion that something had changed in the parking system. After about 3 weeks of going back and forth the parking company found the bug in their system. Due to a mistake in their traffic counting filter they were progressively firewalling out one IP address after another around the world. This was a potentially multi-million dollar mistake.....not good!
This brings up another point. When you have a critical mass of traffic it is very difficult to dramatically change either upwards or downwards the CTR for that traffic. If you see the CTR for a large amount of traffic that is spread across thousands of domains dropping then give me a call as it’s more likely to be a systemic problem rather than user behaviour.
It’s quite often the defence used by parking account customer service staff to indicate that the reason why a portfolio has had a decrease in CTR is due to “user behaviour”. One day I got fed up with hearing this as an answer and for a particular portfolio of mine I calculated the percentage likelihood that user behaviour could change for only 100 domains with reasonable levels of traffic. It ended up being less than 0.01%. In other words, for the CTR to drop by 20% there had to be the equivalent of an Internet ice-age....which is not very likely at all.
Just to make things a little more confusing, if you are parking your domains with a parking company that uses a Yahoo feed then it’s likely you can achieve CTRs of over 100% (ie. a person clicking twice on two different links). If you are parking with a Google provided parking company then they will often aggregate clicks so that if there were two clicks worth 10 cents each then they report back 1 click for 20 cents. This inflates the EPC and decreases the CTR. I’m really not sure why they do this so feel free to enlighten me if you know.
All of these points illustrate the risk associated with CTR (remember that we covered definitions of traffic in a previous article). It also means that you cannot compare the CTR from one company to the CTR of another company. For a start you would be measuring the CTR at different points in time and also as we’ve discussed each company counts clicks and traffic differently.
From an investment perspective all that CTR does is indicate that it is likely that are humans clicking. Comparing the CTR for a domain within a parking company potentially does allow you to measure the results of the increased or decreased relevancy for individual key phrases.
What this also may mean is that through optimisation you may elect to sacrifice a little CTR to use a higher EPC relevant keyword. For example, if a domain is receiving games related traffic then you may select “games” as the keyword that is receiving a 10% CTR by a 20 cent EPC over “online games” that is receiving a 20% CTR and 0.02 EPC. The challenge for optimising like this is that it’s very likely that the very next week the keyword behaviours will flip. The days of setting a keyword and forgetting the domain are long gone.
In the next article in this series I'll continue to look at the topic of financial Risk in purchasing traffic domains.
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