When it comes to SEO every single specialist knows that data analysis is really important. As the days pass you get data about anything and everything from the number of…

Jumping To Conclusions – A Common SEO Data Analysis Mistake

Jumping To Conclusions – A Common SEO Data Analysis Mistake

When it comes to SEO every single specialist knows that data analysis is really important. As the days pass you get data about anything and everything from the number of backlinks you have to how old a domain is. All this is analyzed in order to build a better SEO campaign, one that is going to rank the website higher for specific keywords.

The problem is that SEO data analysis is not as simple as we might think. The very first conclusion you have may not be the correct one as you might be missing some data that would completely change your mind. It is really important that you do not jump to conclusions.

There are various things you need to take into account before you jump to any conclusion. When these things do not make enough sense, a problem might exist and your conclusion might be a bad one.

Basically, before you formulate any conclusion as you analyze SEO data, be sure that you check the following facts:

  • Coincidence – In some cases you analyze many different datasets so some might just be similar. Coincidence is something to take into account when you analyze data coming from different sources.
  • Reverse Causation – Maybe your understanding of the data was not correct. As an example, let’s say you analyze a large group of women that eat a lot of chocolate and you think sales are going to increase. In reality, it might be that this was caused by some life events that were not mentioned in the official data gathering report.
  • Joint Causation – Always think about the possible presence of another factor that is behind the data results you look at. Let’s say you eat a lot of cheese these days and you think that this is the case simply because it makes you feel comfortable. Is that really the case or is there another reason you did not consider?
  • Linearity – Do you compare 2 trends that are linear? The linear trend is a rate of decline or growth that is steady. Two linear statistics are going to be correlated. If you notice that some trends you analyze are not linear, it is possible that something else influences them and your conclusion might be incorrect.
  • Broad Applicability – Finally, in an attempt to find a solution or something that works to rank websites we can make the mistake of thinking something applies in all scenarios. We might think, for instance, that a strategy that was really effective in one industry is going to be equally effective in another.

Case studies are very important and should be taken into account as you devise an SEO strategy but you have to be sure that you do not blindly trust results as being 100% correct simply because this is what you want to see. Do try to rule out all the factors that are not relevant to your campaign. Was website traffic increased because of a specific SEO move or did something else happen? Did the SEO strategy work because of a unique circumstance that is particular to the project? These are the types of questions you need to ask yourself at all times.

SEO Marketer with over 5 years experience, editor for Blog For Web. Get in touch if you want to talk SEO, marketing, design or other topics.

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