Learning the search algorithms by scientific method

Sep 5, 2005 at 7:51 PM
Every day, I read well-educated people in the search engine optimization business talking about how to beat the algorithm with one magic trick or another perfect solution. What a ridiculous methodology. "The Search algorithm can be beaten with this doo dad..." "Try this trick to immediately beat out everyone else in the search engines", "Hire us and we'll apply our mysterious magic to get you into a guaranteed first place..." BLAH BLAH BLAH. These are alchemists and witch doctors. These are not experts, no matter what they say.

The simple definition of "algorithm" is the step-by-step procedure involved in problem solving. The search algorithms are just that. An attempt to solve the problem of "too much information out there" by culling it down to a few "perfect" results with finite rules. It is a science with set and understandable goals. Therefore, optimization -- real optimization -- could not be a simpler task.

Trying out new "tricks" to beat a methodically planned algorithm designed only for one purpose is madness. It is like trying to learn how to build a nuclear reactor by reading tarot cards.

The only way to properly build a system of management for an algorithm is to use scientific method.

Now, not everyone who is in SEO is a quack. But most are. If you're an SEO person reading this, simple statistics tell me that you are probably a quack.

However, the relative minority of us are scientific about it. Some of us must use carefully planned research tools, study our diagnostic machinery, carefully pull and test code, and run tests, both within the system and in live media.

Some of us are natural Einstiens in this science. Without ever having to scratch out the details in pen, we can often see right to the heart of it and quickly edit code in the fly, creating just the right result. That is not magic, it is science from web geniuses, and should not be mistaken for quackery. None of the SEO geniuses out there are remotely likely to win a nobel prize for it, but they are in demand none the less.

Those of us searching for the base point in our experiments can easily see already the apparent effects of the search algorithm, they are readily available to us in the form of our search results. The very "problem" of placement that we are trying to solve, is in fact the key to solving it. These are your measurable results. These are your petri dish.

There are a few differences. Because search is not a natural science, it's world varied somewhat from the natural world:

Time - in SEO, time is measured in crawls, not hours. How often does the engine crawl that page? That is 1 (one) SEO time unit.

Distance - In SEO, distance is measured in rank only.

Weight - in SEO, weight is measured in inbound links, or file size.

Velocity - In SEO, velocity is measured in how many code changes are made per unit of crawl.

We can easily define the levels of importance placed on each factor involved in SEO placement through a process of titration done within those results. Change one small factor only, and change it in the minimum even amount per crawl on your experimental page. See what the effect is on your rank. A change in rank is the known and predictable "reaction". Then you can calculate the exact effectiveness level of that form of optimization, per unit.

You can also learn to importance the algorithm of a particular SE places on certain factors by broadening your scope, study the code behind an entire test page of search results, or hundreds of such pages:

As an example, the difference of links from 1st place to 100th across 100 search terms should tell you how many more links you need to be first in your keyword. Apply that constant to your search term's variable (the inbound links from your competitor) and voila, you have a known. Of course, there are more variables and more considerations, but at least you have a starting point to work from.

Easily, deductions can be made doing this. Provable deductions.

Since the only constant in search engine ranking is the ranks themselves, I posit that the only statement so far that can be considered an absolute in the search optimization field is:

The variable is the only constant.


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