How to Use Python to Forecast Demand, Traffic, And More For SEO

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Over the years, you’ve probably done a lot of SEO work on the HVAC company that you work for. Given enough time, you will, more than likely, have to deliver a forecast to the higher ups.

But what exactly is a forecast you might ask?

SEO forecasting allows you to use data to make predictions, including future traffic levels and the value of that traffic.

In a column on Search Engine Journal, Andreas Voniatis will show us how to get data-driven answers about some potential trends by using Python.

The article will talk about some of the following:

  • Pull and plot your data.
  • Use automated methods to estimate the best fit model parameters.
  • Apply the Augmented Dickey-Fuller method (ADF) to statistically test a time series.
  • And more!

Check out the full article here!

Scott Davenport

Scott Davenport is the content writer and social media man of Thrive Business Marketing and Thrive HVAC in Portland Oregon. Writing about the current events of the SEO world, as well as tips and advice that fellow SEOs could use to improve their own SEO campaigns and shares it for the whole world to see!

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