4 ms·
If you suspect some flag effects interact with each other (e.g. one flag increases button size by 10%, and the other decreases it by 10%) you can go one step fu
by phreeza 4y ago
If you suspect some flag effects interact with each other (e.g. one flag increases button size by 10%, and the other decreases it by 10%) you can go one step further and define feature groups and hash by user-id + group-id and then assign non overlapping ranges to the flags.
- marcosdumay 4y agoOr you can cut and redistribute the non-performing changes, increase the distribution of the well-performing ones, and let evolution take care of disentangle correlated behavior. But if need that kind of analysis for usability A/B testing, you most be doing something very wrong on a previous step.