When A/B testing is not recommended because of regulatory requirements or technical limitations to setting up a controlled experiment, we can still quickly implement a new feature and measure its effects in a data-driven way.
Tag Archives: Causal Inference
Analyzing Switchback Experiments by Cluster Robust Standard Error to Prevent False Positive Results
Within the dispatch team of DoorDash, we are making decisions and iterations every day ranging from business strategies, products, machine learning algorithms, to optimizations.