Your web analytics data is trapped! Google Analytics provides you with a handful of built-in reports and features, but your data has so much more potential. Fortunately, the data-oriented programming language, R, can easily connect to Google Analytics and produce results that go far beyond the features of GA. Furthermore, R provides operational benefits to analytics teams who wish to collaborate on reproduceable analyses.
- Quantifying the impact of events on time series data using the CausalImpact library: Tutorial / Code
- Google Analytics audits via scripted R Markdown file: Output / Code
- Recreating the Google Analytics explorer graph & table in R: Output / Code
- Exploring GA segment overlap with Venn diagrams: Output / Code
- Running Market Basket Analysis with GA data: Blog Post / Code
- Revese Path Analysis: Demo / Code
- Pulling Google's web vital metrics from GA: Output / Code. Assumes that these metrics exist in GA using the process described in this blog post
- Slide output to automate monthly reporting
- Google Cloud Runner demonstration to automate processing
- Basic statistical tests
- Joining data from multiple sources
- Advanced segments + comparing greater than 4 segments at a time
- Anomaly detection
- Offline A/B testing
- Working with unsampled data
- Working with GA in R Studio Cloud