As analysts, we are often called upon to see how website metrics have improved or declined over time. This is easy enough when looking at trends, but if you are looking to break down over other dimensions, it can involve a lot of ETL to get to what you need.
I’ve written previously about how to get RStudio Server running on Google Compute Engine: the first in July 2014 gave you a snapshot to download then customise, the second in April 2016 launched via a Docker container.
There are now several packages built upon the
googleAuthR framework which are helpful to a digital analyst who uses R, so this post looks to demonstrate how they all work together. If you’re new to R, and would like to know how it helps with your digital analytics, Tim Wilson and I ran a workshop last month aimed at getting a digital analyst up and running. The course material is online at www.dartistics.com.
Avoiding sampling is one of the most common reasons people start using the Google Analytics API. This blog lays out some pseudo-code to do so in an efficient manner, avoiding too many unnecessary API calls. The approach is used in the v4 calls for the R package
In this blog we look at a method to estimate where to prioritise your SEO resources, estimating which keywords will give the greatest increase in revenue if you could improve their Google rank.
edit 20th November, 2016 - now everything in this post is abstracted away and available in the googleComputeEngineR package - I would say its a lot easier to use that. Here is a post on getting started with it. http://code.markedmondson.me/launch-rstudio-server-google-cloud-in-two-lines-r/
googleAuthR is now on CRAN version 0.2.0.