Tatvic, a up and coming startup founded by an ex-Trilogy colleague, has helped with the R for Google Analytics package. While Tatvic is into heavy duty web analytics, they are betting big on R, and using it for Web Analytics. David Smith, most excellent blogger-de-chief in R universe has blogged on them before here http://blog.revolutionanalytics.com/2013/02/analyze-web-traffic-data-with-google-analytics-and-r.html
Here is an upcoming seminar on R in Web Analytics.
From this webinar, you will get to know:
- What is R and why should you use this tool? How to extract your Web Analytics data into R?
- How to build a predictive model using web analytics data with the help of R?
- How predictive modelling can take your analysis to the next level?
- How to carry out insightful analysis through visualization?
Who should attend: Every web analyst who wants to take his analysis to the next level.
ps- Hat tip to Caroline A
Due to changes in Google APIs my earlier post on using Google Analytics in R is deprecated. Unfortunately it is still on top 10 results for Google results for Using Google Analytics with R.
That post is here http://decisionstats.com/2012/03/20/using-google-analytics-with-r/
A more updated R package on Google Analytics and R is here . https://github.com/skardhamar/rga
A better updated post on an easy to use tutorial on using Google Analytics with R using OAuth 2 playground is here.
- Set the Google analytics query parameters for preparing the request URI
- Get the access token from Oauth 2.0 Playground
- Retrieve and select the Profile
- Retrieving GA data
Note it is excellent for learning to use RJSON method as well. You can see the details on the Tatvic blog above.
Hat tip- Vignesh Prajapati
The Analytics (or stats) dashboard at WordPress.com continues to disappoint, and is a major reason for people to move out of WordPress.com hosting (since they need better analytics like that by Google Analytics which cant be enabled on the default mode)
Its not really beautiful unlike the rest of WordPress Universe!
It can be made better if people try harder! Analytics matters
Here are some points
1) Bar charts and Histograms are not really the best way to visualize trends across time
2) Location Analytics is limited to just country level analysis and the heatmap (?) is aweful in terms of distinguishing gradients
3) Referrers Tab needs to do a better job on distinguishing between mobile and non mobile traffic, social and non social traffic (and there are better ways to visualize than just a simple list)!
4) I cant even export my traffic stats (and forget an api !) so I am stuck with the bad data viz here