Emily Robinson - Building an A/B Testing Analytics System with R and Shiny

Emily Robinson, DataCamp

Online experimentation, or A/B Testing, is the gold standard for measuring the effectiveness of changes to a website. While A/B testing is used at thousands of companies, results can seem difficult to parse without resorting to expensive end-to-end commercial options. But using DataCamp's system as an example, I'll illustrate how R is a great language for building powerful analytical and visualization experiment tools. We'll first see how Shiny dashboards can help people monitor and quickly analyze multiple A/B tests each week. We'll then dive into the open-source funneljoin package we've created using variations on dplyr's joining function, allowing you to analyze sequential actions using behavioral funnels.