Every time you make a modification to on-site optimization of any of your webpages, make an annotation in Google analytics.Create an excel spreadsheet that records the same information for Top 100 keywords that have generated traffic to your site.Create correlation vs causation worksheet with a list of every single keyword you want to target, next to the page on which you’re using these keywords.In the section below, I’ve explained 3-Steps of generating meaningful data by tracking a few metrics. If you want a bigger and better perspective, you’d need to review tons of data. But, after a proper analysis, you’ll be able to distinguish it as a causality.Īs you continue working more within this field, you’ll be able to assess and distinguish both these situations better.ģ Steps of generating meaningful data by tracking a few metrics. You might think that there is a correlation between higher rankings and a large amounts of links. While studying the SEO factors, develop more understanding about the relationships between events.
The difference between these two terms must be taken into consideration during SEO analysis, especially when trying to find causality among different factors.īefore judging the events, try to view them from different perspectives.
#Define causality how to
How to use correlation and causation for SEO?
Re-evaluation of site against new standards. This allows us to review whether or not two different factors are changing in the same direction, at the same time, and also understand the influence level they have on each other.Ī change in your website’s SERPs ranking could be due to causation or correlation with any of these factors: We do this analysis for a high number of factors, as we try to identify a correlation between those factors. At Troop Messenger, we run an SEO analysis before writing any blog post. We can apply the same distinction to SEO results. Hence the Z & Y variable has a causation relationship between them. If we introduce a Variable Z (Summer Weather), then we can see the cause-and-effect relationship between Variable Y (Drowning Deaths) and Variable Z (Summer Weather). Hence X&Y has a correlation between them. In this example, Variable X (Ice-Cream Consumption) did not cause the manifestation of Variable Y (Drowning Deaths). In warm weather, people tend to consume more ice-cream and also swim more often, which leads to an increase in the number of drowning deaths. In fact 'Summer Weather’ is the third variable, which is the causative agent in this scenario. Now, I’d sound ridiculous if I say that ice-cream consumption causes drowning, wouldn’t I? Let’s begin this section with Correlation vs Causation Graph:Īs you can see in the graph above, there is a correlation between the amount of ice-cream consumed and the number of people who died because of drowning. It means that the existence of one variable causes the manifestation of another.īottom Line: Causation answers why 2 things or events will happen at the same time. We are saying that X causes Y, or vice versa. Unlike Correlation, the relationship is not because of a coincidence. It implies that X & Y have a cause-and-effect relationship with each other. Sometimes, correlation can be referred to as a coincidence.Ĭausation is the principle of a connection or a relationship between effect and its causes. 
Any change in X leads to no change in Y, or vice versa.īottom Line: Correlation answers whether or not 2 things will happen at the same time.
When variable X increases, variable Y decreases, or vice versa. Example: the more subscribers on your website, the more traffic it has generated. Similarly, if X decreases, Y correspondingly decreases. When variable X increases, variable Y also increases. You cannot say X caused Y, you will simply say that when X and Y are observed together. If X and Y, two variables, tend to be observed at the same time, there’s a correlation between them. This term, used most often in statistics, refers to the degree of connection between any random variables. This relationship is not caused by chance. 
Let’s dive right in as I review correlation vs causation psychology and describe the main differences between these two common terms.Ĭorrelation is a relationship or connection between two or more objects. These two words appear deceptively similar but identifying the difference between both can either make or break the process of creating a high-value product for your customers. Distinguishing correlation from causation is one of the most frequent mistakes made in reasoning.
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