In this blog post, I evaluate several of the numerous (and potentially overwhelming) options for the processing and reporting of Google Analytics data. The default Google Analytics web interface is great for quick ad hoc data exploration, but limited for deeper analysis and the development of automated reports.
Whether we’re mining for hidden trends or trying to report on hard-to-extract dimensions, there are a number of third-party tools out there can that help ease the burden.
In the first half of this article, I explain the difference between the two types of Google Analytics data: what’s available from the standard interface and what’s available through the BigQuery export.
The second half of this article is an evaluation of three different solutions for processing, visualizing, and reporting on Google Analytics/GA BigQuery data. I evaluate these three solutions (ShufflePoint, Tableau, and R) based on objective features and my subjective scoring of performance.
I only evaluate three data processing solutions in this article. Think I missed a good one? Let me know!! We all have a different background in data analysis tools, and I would love this conversation to continue in the comments section.
Big Query and Big Query Export for Google Analytics give us the power to visualize and explore virtually any trend in our GA data. It’s really quite powerful stuff. Because this tool is still very new, I want to get the conversation started on how advanced reporting can augment our digital analytics.
In this post I discuss data mining and the advanced reporting of Google Analytics data. I provide an R script for generating an E-commerce report with visualizations that are not possible within Google Analytics.
Note: This article contains updates to the previous article “Statistical Significance Script for Google Analytics”, which has been redirected to this article. See the changelog for details.
In March I wrote a script for the statistical evaluation of time-frame comparisons in Google Analytics. The idea seemed well received, but who wants to have to hit F12, open their developer console, and then come back to my blog post for the code… every time you want to run the script?
So, I converted the script into a Chrome Extension (click below)!
GWT Pages Export 1.0
And below is an updated Bookmarklet with a progress count:
GWT Pages Export 1.1
In order to save this Bookmarklet, drag and drop this link onto your Bookmarks Toolbar. Alternatively, right-click it and copy its link address. Then, create a new bookmark and paste your copied address as the Bookmark address.
When comparing two time periods in Google Analytics, we are given a percentage increase or decrease. In situations where there is a dramatic difference (as is often the case for year-over-year comparisons), we can safely assume that the result is statistically significant.
For example, in the below chart, every data point (day) is lower in the second period than in the first. We can reasonably conclude that there has been an increase in visits in our month-over-month comparison.
Not All Bounces are Created Equal
Interaction Events and Bounce Rate
The great customizability of Google Analytics implementations can at times be a double-edged sword. We are living in the golden age of analytics and we of course we want to collect as much metadata associated with our traffic as possible. The caveat is that, with each added layer of complexity to our GA tracking, we must ensure consistency across our website. We must be especially careful that our KPIs are comparable for cross-sectional and longitudinal analysis. (more…)
Note: The code provided in this article has been updated, and is now provided as a bookmarklet at the link below. This article has not been redirected, because it includes analysis not provided in the new article. Click here for the bookmarklet
My reaction to the GWT New Year’s Update
I couldn’t believe it when I saw the January 7, 2014th Webmaster Tools update,
“data in the search queries feature will no longer be rounded / bucketed.”
At first I thought, why would Google go through all that trouble to obfuscate keyword data in Google Analytics, when they planned on handing all that data back through the search query reports in Webmaster Tools? And of course, they didn’t plan on anything of the sort. The relatively minor update only removes bucketing, and does not address the big issue, that they display only 20% to 25% of search query data. I held out hope that, as it appears in the before and after pictures, the sampling rate had been increased from around 20% to around 35%. But while I’ve noticed small changes in some accounts, it does not appear they’ve made this improvement. (more…)