Generating numbers is easy; generating numbers you should trust is hard!

Emily Robinson is a data scientist at Etsy, an e-commerce website for handmade and vintage products. In the #rstats community, Emily is nearly as famous as her brother David Robinson, whom we know from the tidytext R-package.

Like any large tech company, Etsy relies heavily on statistics to improve their way of doing business. In their case, data from real-life experiments provide the business intelligence that allow effective decision-making. For instance, they experiment with the layout of their buttons, with the text shown near products, or with the suggestions made after a search query. To detect whether such changes have (ever so) small effects on Etsy’s KPI’s (e.g., conversion), data scientists such as Emily rely on traditional A/B testing.

In a 40-minute presentation, Emily explains how statistical issues such as skewed distributions, outliers, and power are dealt with at Etsy, among others using bootstrapping and simulations. Moreover, 30 minutes in Emily shares her lessons when it comes to working with (less stats-savvy) business stakeholders. For instance, how to help identify and transform business questions into data questions back into business solutions, or how to deal with the desire to peek at the results of experiments early.

Overall, I can the presentation below, the slides of which you find on Emily’s GitHub.