In this week’s MashMetrics Analytics Jam, we will cover how to perform more advanced analytics with Google Analytics by exporting it within R.

SCENARIO:

Thanks to the economic downturn, the marketing team needs to work in an extremely lean manner. They have decided to revive their blog in order to obtain more organic search traffic rather than rely upon PPC traffic alone.

PROBLEM:

With over 200 posts in the last year or so, redoing all of the blogs does not seem to be a good use of time. Considering we want to raise the awareness of our blog, we also do not necessarily need to focus on the blogs already getting a good amount of traffic. Also making this analysis difficult is the fact that each post has “been live” for a different amount of days making it difficult to compare against each other.

SOLUTION:

By ranking each post by the first time it occurs and looking simply at the cumulative growth we can quickly visualize which posts were fairly engaging, but stopped generating traffic. Conversely, the posts that never really took off are (lucky for us) hidden and the ones that are already in good shape just spike up and to the right (clap for those!)

In this demo, we extract the data with R, clean it up, rank the data by first occurrence, and then visualize with Google Data Studio as well as our favorite, DOMO.

• Download over 400 days worth of landing page behavior data from Google Analytics (with R)
• Parse through the data to only contain data within the blog
• Rank the data by the first day we see traffic for it
• Visualize the time series data with Google Data Studio and DOMO