16. Custom dimensions
Supercharging websites with a real-time R API http://code.markedmondson.me/predictClickOpenCPU/supercharge.html#1
Improve Data Collection With Four Custom Dimensions https://www.simoahava.com/analytics/improve-data-collection-with-four-custom-dimensions/
E.g. Cust ID + Timestamp
18. 6. Model & Communicate the data
https://github.com/papageorgiou/dublinR-talk-analytics http://www.alex-papageo.com/research.html
E.g. Decision tree & variable importance for conversion prediction
19. Some ideas
● Decision tree for conversion prediction (rpart)
● Clickstream analysis to predict next page (clickstream)
● Clustering for customer segmentation (base R)
● Association Rules for pages/products frequently visited together (arules)
Enrich data: Look for opportunities to join with internal data/ external api data
20. Wrapping up
DS with GA not straightforward but possible
Take advantage of GA API
Open source R/Python libraries
Get familiar with 2-3 algos and apply them on your data.