Post by account_disabled on Feb 13, 2024 22:09:21 GMT -8
The SEOs listened to Googlers read Google patents and I found that a lot of the disagreement comes not from what Google EAT is we have a pretty good understanding what Google EAT actually does but how we define ranking factors. Three ways to define ranking factors I found that how we define ranking factors falls into roughly three different schools of thought. . Level Directly measurably directly impact rankings Now the first school of thought this is the traditional view of rankingfactors. People in this camp say that ranking factors are things that are directly measurable and they directly impact rankings or they can directly impact rankings.
These are signals that were very familiar with such as PageRank URLs Iceland Email List canonicalization things that we can see and measure and influence and directly impact Googles algorithm. Now in this case we can say Google EAT probably isnt a ranking factor under this definition. There is no EAT score. Theres no single EAT algorithm. As Gary Illyes of Google says its millions of little algorithms. So in this school or camp where things are directly measurable and impactful Google EAT is not a ranking factor.
Level Modeled or rewarded indirect effects Then theres a second school of thought almost equal to the first school of thought that says Googles algorithm is sufficiently complex that we dont really know all the direct measurements and in these days its a little more useful to think of ranking factors in terms of what is modeled or rewarded things with effects that are possibly indirect. Now this really came about during the days of the Panda algorithm in when Google started using much more machine learning and eventual neural networks in its algorithm. grossly oversimplify Panda was an algorithm designed to reduce lowquality and spammy results in Google search results. To do this instead of using directly measurable signals.
These are signals that were very familiar with such as PageRank URLs Iceland Email List canonicalization things that we can see and measure and influence and directly impact Googles algorithm. Now in this case we can say Google EAT probably isnt a ranking factor under this definition. There is no EAT score. Theres no single EAT algorithm. As Gary Illyes of Google says its millions of little algorithms. So in this school or camp where things are directly measurable and impactful Google EAT is not a ranking factor.
Level Modeled or rewarded indirect effects Then theres a second school of thought almost equal to the first school of thought that says Googles algorithm is sufficiently complex that we dont really know all the direct measurements and in these days its a little more useful to think of ranking factors in terms of what is modeled or rewarded things with effects that are possibly indirect. Now this really came about during the days of the Panda algorithm in when Google started using much more machine learning and eventual neural networks in its algorithm. grossly oversimplify Panda was an algorithm designed to reduce lowquality and spammy results in Google search results. To do this instead of using directly measurable signals.