Mar 29, 2015

R Stats + Digital Analytics: 8 Blogs you should Follow


Are you interested in using R for your digital analytics projects? Do you need to perform prediction modelling and visualizations on your digital data and Excel can´t just do the job as you wanted?

Or, you simply have no idea how R could help you in your digital analytics problems and you would like to see some real working examples first?

Well, there are 2 good news for you.

The first one is that you are not alone. There is a quite vibrant community out there, sharing more and more examples on how to get real value from using R in digital analytics. They often post/tweet around the #rstats hashtag.

The second news is that I decided to write a post on this. I am going to list here the main blogs (and people) that might be useful to add to your "R Stats + Digital Analytics" reading list.

Jan 27, 2015

Google Analytics Dashboards with R & Shiny


Google Analytics Dashboards with R & Shiny
One of the key activities of any web or digital analyst is to design and create dashboards. The main objective of a web analytics dashboard is to display the current status of your key web metrics and arrange them on a single view, so that information can be monitored at a glance. Great dashboards should allow you/your boss or client to take action quickly and spot trends in data.

There are plenty of tools for creating dashboard out there. You can decide to create your dashboard directly in Google Analytics, using a spreadsheets (e.g. Excel or Google Sheets) or you might decide to go for an ad hoc dashboarding solution such as Tableau, or Klipfolio (I am a heavy user of the latter).

In this blogpost I aim to move away a bit from traditional dashboarding tools, and I wil show you an example of Google Analytics dashboard I've built using the R programming language and the Shiny package. Finally, I will also summarize the main benefits of using such tools for creating dashboards and perform data analysis in a digital analytics context.

Nov 23, 2014

Drawbacks of Using Time Metrics to Measure Blogs

When it comes to blogging, we all know that CONTENT is king. We also understand that SOCIAL interactions and readers ENGAGEMENT play a primary role for making the blog successful.

So far, so good.

But then it's time to analyse data and make decisions...and that's where we often fail.

We usually take a web analytics tool like Google Analytics, install basic tracking code on pages, and analyze the blog like any other website. We look at most common metrics and take them as standard references to evaluate future performance. But we forget about the unique features that differentiate blogs from other digital properties: content consumption and social interactions.

This post will help you understand one of the most misused metrics to measure blogs performance: I am talking about time on page and time on site. Most bloggers don't understand what time metrics actually measure. So, first of all I will try to explain how they are calculated in a typical web analytics tool (it might be different from what you think!).

I will then discuss some of the drawbacks of using time metrics to measure blog performance and finally suggest a couple of more solid KPI's to better measure content engagement.

After reading this post, I am sure you will start looking at time metrics with a bit more critical thinking than before. And perhaps shift your blog analytics focus to other more powerful metrics.

Let's go!