Using Heuristic Methods for AB Testing
I've just started reading about AB testing, as it pertains to optimizing website design. I find it interesting that most of the methods assume that changes to the layout and appearance are independent of each other. I understand that the most common method of optimization is the 'multi-armed bandit' procedure. While I grasp the concept of it, it seems to ignore the fact that changes (changes to the website in this case) are not independent to each other.
For example, if company is testing the placement and color of the logo on the website, they find the optimal color first then the optimal placement. Not that I'm some expert on human psychology, but shouldn't these be related? Can the multi-armed bandit method be efficiently used in this case or more complicated cases?
My first instinct is to say no. On that note, why haven't people used heuristic algorithms to optimize over complicated AB testing sample spaces? For an example, I thought someone might have used a genetic algorithm to optimize a website layout, but I can find no examples of something like this out there. This leads me to believe that I'm missing something important in my understanding of AB testing as it applies to website optimization.
Why isn't heuristic optimization used on more complicated websites?
Topic consumerweb optimization
Category Data Science