The tools and technology of Data SEO

Data SEO uses many tools and technologies drawn from different branches of data science. If you’re looking to use data science in order to automate, predict or visualize your SEO strategy, you may use some or all of the tools featured in this infographic. None are required, but the more tools in your toolbox, the better you will be at solving SEO problems and finding answers to SEO questions!

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APIs

APIs allow you direct access to the data, whether you are providing data or obtaining it. You can avoid having to manually copy, export, import, or interpret SEO data.
Data visualization platforms
Preparing, formatting, and feeding data to a visualization platform is an important step in Data SEO. Depending on your data visualization or business intelligence platform, this process can sometimes get a bit complex.

Data warehouses

Within a company, data warehouses bring together many types of data from different departments across the company, and make them all available to everyone.

Programming languages and libraries

There are an increasing number of Python or R libraries, or sets of pre-programmed functions, made available by the coding community that can be applied to SEO purposes.

Notebooks

Coding notebooks, like Jupyter Notebooks and Google CoLab Notebooks, have become a popular way to share code. They unite code, descriptions, and results in a runnable coding environment that is easy to share and use for demonstrations.

Machine learning technologies

As both websites and search engine algorithms become more complex, it becomes difficult to use pen-and-paper analysis to find patterns and predict future effects in SEO data. Machine learning works by training a model, or showing it the results for a series of inputs, and then allowing it to generate a mathematical model that best explains the relationship.

NLP models

At the heart of SEO today is how a search engine understands the goals behind a query, and how it determines which pages in its index are most pertinent to that goal. To do so, search engines rely on NLP: the study of how machines interpret and generate human language.