Getting your test read and making a rollout decision was the relatively easy part. How do you ensure you are spending your testing resources on the best experiments that are going to derive meaningful insights? Can you multi-purpose your experiments with machine learning and data science analysis?
In this interactive workshop, led by Krissy Tripp, Director of Decision Science at Evolytics, we will look at methods to further analyze experiments through applied statistical and machine learning methods that drive results.
Krissy will cover:
- Using Evolytics’ Data Science Decision Tree to determine which advanced statistical methods will best serve your post-test analysis
- How to balance the likelihood of actionable insights with data analytic resources
- Introduction to using data science for experimentation programs
Krissy will walk you through a structured learning approach to experiment takeaways. You will come away with an experimental learning roadmap with prioritized experiments and quick wins for the data science team.