  Adaptive experimental design (AED) methods are increasingly being used in
industry as a tool to boost testing throughput or reduce experimentation cost
relative to traditional A/B/N testing methods. However, the behavior and
guarantees of such methods are not well-understood beyond idealized stationary
settings. This paper shares lessons learned regarding the challenges of naively
using AED systems in industrial settings where non-stationarity is prevalent,
while also providing perspectives on the proper objectives and system
specifications in such settings. We developed an AED framework for
counterfactual inference based on these experiences, and tested it in a
commercial environment.
