It sounded great until I realized that:
1) I would still have to think of variations and create them myself.
2) Even after that, this would only be useful if things like location and time of day really did have a significant effect on conversion rates.
3) And even after that, this would only be _worth it_ if those effects were not obvious to me and could only be discovered with ML. For instance, it doesn't take ML to hypothesis that a visitor who came from an ad link (&utm_campaign=dogs) is more interested in seeing a page about Dogs. And that hypothesis can be tested for free with Optimizely.
In other words, ML is cool and all but I don't see what value this adds to conversion optimization.
Maybe my assumptions are wrong and I'm missing something, in which case I hope this is useful feedback.