Jafo, Frankly, I don't really care whether you find statistical modeling or my model accurate or not. The article clearly explains why the summer and winter results were "fudge factored". It even explains why they are to the level they are.
My article is offered for what it is. I am not terribly concerned whether you feel that statistical modeling is something useful or not nor whether you find this particular example to be sufficiently accurate or not.
I am not here to convince anyone of anything. I am merely sharing a tool I have successfully used to help generate millions of dollars in multiple, and very different, markets over the past decade.
Crae: I am "Assuming" that people download more in the Winter because they do download more skins in the Winter. I am applying several years of experience in monitoring monthly downloads of skins overall. If I was willing to sit down and try to convince you of this, I could also show the bandwidth traffic over a given year.
Similarly, I know that peek traffic hours are between 1pm and 6pm EST. And that Friday is the least busy day of the week despite what seems intuitive on that.
These are all facts that any statistical model would ahve to bias. But what is important, in any profession, is knowing where to draw the line. When the model is sufficiently accurate to serve the purpose it intends.
Perfect is the enemy of good enough. If, in this example, WindowBlinds was losing popularity, it would only be detectable if it was a pretty significant drop.
Using these models, we have been able to track the rise and fall of NeXTStart and ICQ Plus over the years. In our software, our goal is to see whether outside factors are affecting the overall user base and the market as a whole so we can plan for the future.
