Nice post, Sergey. We've been using Thompson Sampling to deal with delayed feedback, as we're dealing with data coming from mobile applications which are not always connected. The results have been pretty good, here's a breakdown of how it works if you're interested: https://splitforce.com/resources/auto-optimization/
Have you thought about how to deal with changes in environmental factors over relatively longer periods of time? For example, seasonality or changes in popular taste.
