Tracking with Deep Analysis

[Graybeard]

It's always been a problem understanding the data that you get every day and figuring out whether it's going up or down or sideways.

Well let me introduce you to Quadratic Regression Analysis and why this mouth full of words can be important to you.

Anyone who has studied any type of web analytics knows that there is a standard deviation that needs to be taken into account. What I mean by this is that one day you get 100 referrals and the next day you get 50 referrals.

To find some sort of a median or average you need to follow the law of large numbers and have enough hits or clicks to show a meaningful population of data allowing you get a better overall picture.

That said, here is an image of a new python charting program that I created to study keywords and the number of "clicks (CPC_PPC)" then to find a quadratic regression r2 Factor to sort out the trend of each keyword or key phrase.

What an r2 factor means is that it shows the relationship of the trend within the group of data (the keyword group in the analysis).
The r2 doesn't necessarily mean this keyword is the best, what it means is the data points and the quadratic curve rendered is most or least accurate. So, when you have four keywords and you have r2 two values between 20 and 75 the r2 value that is 75 is just telling you that curve is more accurate.

This is NOT "awesome perfect" but it does give you a starting point to decide; should I keep spending my money on this keyword or should I spend more money on the keyword that shows a better curve --that's the point of the whole program.

 

[Graybeard]

Here's another example of how you can use regression forecasting.
A redditor made a post today and he listed 51 trending items. After I went through about 10 or 15 of those supposedly trending keywords I did find a few.

You know what I modified my previous program for analyzing Google Trends and this version only shows the regression lines for much cleaner look :

Hey, you can look up this keywords on your own and do some searching and find out what they're about.

The idea of mushroom coffee kind of turns my stomach but it seems to be a popular trend. Soju, as it turns out is a lightweight vodka-like liquor that is the national drink in South Korea. I guess it's a Korean wine cooler of sorts, with a little more oomph in it alcohol content; more like a brandy rice wine or something of that nature. I never heard of it before but look at the way it's trending.

So there are two factors in this chart:

• First of all you have the search volume, and;
• secondly you have the quadratic regression which shows the stability or trending of that keyword respectively.

When the r2 value of the regression is above 0.40, the regression trend line that you are seeing is most likely reliable.

Higher regression values like 80+ may be meaningful. However, you should consider that these trends are derived from back-testing data and are no assurance of future events --just a reasonable chance,

Reliable going up or reliable going down --or reliable in a static mode.

 

[Graybeard]

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[peerclicksupport]

It's easier to use trackers rather than Excel tables

 

[azgold]

It's easier to use trackers rather than Excel tables

You don't know Graybeard. When he does deep analysis, he does DEEP analysis. He has mad analytical skills.

 

[peerclicksupport]

You don't know Graybeard. When he does deep analysis, he does DEEP analysis. He has mad analytical skills.

Well, it seems to me that the point should be that somehow this case could be used by people with less analytical abilities