You either don't understand statistics or are missing my point. Your example about a Christmas domain is perfect.....I'm not looking to compare the CTR between services. That's the fundamental part you aren't seeing for some reason. I am only looking at "portfolios" or collections of domains. You did explain how you thought CTR was not as important as I think, and if we were looking at domains singly I would agree. But i'm not. I am looking at a very generic metric that may or may not suggest a difference in parking companies. There are many assumptions ,made in general about parking, but very little if any data to confirm any claims. Because I use metrics and quantitative analysis in my professional career, I look for a robust experimental design that can start to build a platform on which other theory's can be tested and confirmed or rejected. People are very sensitive about their specific earnings or niches and rightfully so. So I am starting with something very basic. Could there be other ways to accomplish this? You bet. Honestly, you could have just entered the number and been far more helpful lol, but whatever. So let me try another way.
My CTR is 2.48 across 500 domains more or less, and I use Parking crew. I have three other data points given to me in PM. Lets say that we end up with this imaginary data set: 2.48,1.87, 2.02, 2.67, 2.89 and 3.12. There could be all kinds of reasons for the differences; parking company, domain quality etc. This data set would be meaningless. But lets say we add in another variable, parking company and our data set is PC, GD, GD, GD, PC, PC, respectfully. So the GoDaddy parking people had 1.87, 2.02 & 2,67, Parking Crew had 2.48, 2.89 and 3.12.. We can immediately see that the PC average CTR was higher (2.83) than the GD average (2.19). Assuming 500 domains per entry, that's 3000 domains which is not so impressive, but you get the idea. With a larger sample size I could also calculate standard deviations and see if that was a meaningful difference or a statistical anomaly. Assume it was significant and with a much larger data set, would you want to try PC or GD first? Of course without any other data, you would want to try PC and that makes CTR important. Of course there will be cases where GD is better and that is where the next level of analysis would come in. But as the sample size gets larger, representing dozens or hundreds of data points, that in turn represents thousands or tens of thousands of domains, it would build a pretty compelling case that there is some overall difference between companies. Then you could set about asking why through a new set of theories and metrics.You could, for example, devise a metric(s) for domain quality and then look at the individual domains to see if there were any relationships between say domain length for example. Rinse and repeat, but that data is much harder to get so that's why I started where I did, CTR. It is also possible that even with a large data set that we could not find any significant differences across lots of domains and parking companies. But no correlation is almost as valuable as having one. Maybe the difference lies in your definition of valuable compared to mine, but IMO being able to look at a statistically valuable set of data analysis from a LARGE sampling of CTR's associated with different companies would be valuable to me, especially if I were a beginner just starting to look at parking and not really knowing any way to differentiate between the companies, other than the subjective opinions and experiences that are all qualitative, not quantitative.
Now, what was your number?