5 additional data blending examples for smarter SEO insights

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As I covered in my previous article, data blending can uncover really powerful insights that you would not be able to see otherwise.

When you start shifting your SEO work to be more data-driven, you will naturally look at all the data sources in your hands and might find it challenging to come up with new data blending ideas. Here is a simple shortcut that I often use: I don’t start with the data sources I have (bottoms up), but with the questions I need to answer and then I compile the data I need (top-bottom).

In this article, we will explore 5 additional SEO questions that we can answer with data blending, but before we dive in, I want to address some of the challenges you will face when putting this technique to practice.

Tony McCreath raised a very important frustration you can experience when data blending:

When you join separate datasets, the common columns need to be formatted in the same way for this technique to work. However, this is hardly the case. You often need to preprocess the columns ahead of the join operation.

It is relatively easy to perform advanced data joins in Tableau, Power BI and similar business intelligence tools, but when you need to preprocess the columns is where learning a little bit of Python pays off.

Here are some of the most common preprocessing issues you will often see and how you can address them in Python.

URLs

Absolute or relative. You will often find absolute and relative URLs. For example, Google Analytics URLs are relative, while URLs from SEO spider crawls are absolute. You can convert both to relative or absolute.

Here is how to convert relative URLs to absolute:

Here is how to convert absolute URLs to relative:

Case sensitivity. Most URLs are case sensitive, but If the site is hosted on a Windows Server, you will often find URLs…

 

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