How to use RStudio to create traffic forecasting models - Search Engine Land

There is a lot of fervor in the SEO industry for Python right now.

It is a comparably easier programming language to learn and has become accessible to the SEO community through guides and blogs.

But if you want to learn a new language for analyzing and visualizing your search data, consider looking into R.

This article covers the basics of how you can produce time series forecasts in RStudio from your Google Search Console click data.

But first, what is R?

R is “a language and environment for statistical computing and graphics,” according to The R Project for Statistical Computing.

R isn’t new and has been around since 1993. Still, learning some of the basics of R – including how to interact with Google’s various APIs – can be advantageous for SEOs.

If you want to pick up R as a new language, good courses to learn from are:

But if you grasp the basics and want to learn data visualization fundamentals in R, I recommend Coursera’s guided project, Application of Data Analysis in Business with R Programming.

And then you also need to install:

• Posit’s RStudio integrated development environment (IDE) – which is to R as PyCharm is to Python.

What follows are the steps for creating traffic forecasting models in RStudio using click data.

Step 1: Prepare the data

The first step is to export your Google Search Console data. You can either do this through the user interface and exporting data as a CSV:

Or, if you want to pull your data via RStudio directly from the Google Search...

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