When you’re going to compare two metrics of comparable sizes in a XY plane, it’s sometime useful to add a 45 degrees reference line (in geometrical terms, a bisecting line). This is extremely useful, among other cases, when you need to compare an above-the-line/below-the-line performance. A typical example, discussed here, is when you need to compare if the channels of incoming visitors to a website are more capable of attracting new rather than returning visitors.
Technically speaking, Tableau doesn’t allow to draw diagonal reference lines, but this could be done with a very simple trick I’m going to explain here. I tested on Tableau Professional 9.0, but it should work with other versions as well.
RStudio is a full-featured programming environment for coding in R and, as it comes for free, it’s totally in scope for our Open Analytics duties. The best known version of this nice piece of software is the desktop one, which is available for Windows, Mac and Linux platforms and it’s not uncommon to see as a personal analytics solution, especially where SAS is way to expensive. Sometimes, people use RStudio to work locally with R, for developing/prototyping/testing and then deploy .R files on a remote (heavy) server which runs it using stand-alone R for better performance.
The question is: why do that if one could use RStudio bigger brother, the RStudio server?
Before start exploring the deep cliffs of the quantitative marketing analysis, I would just like to share my personal set of best practices I always use for an effective dashboard design process. Altough these are focused to a typical marketing use case, these are totally generic as they provide a set of analytical starting points and some cooking recipes on how to approach the task of designing a visual reporting environment for your company.