[wmt]

Implementing more complex machine learning methods isn't free, and neither is bying one, so the system should bring in dramatically more money just to cover its costs.

The company whose ad this post was is not showing much data about the difference between the solution it's selling and A/B testing. I wonder if there isn't any or if it is not supporting it's price?

[feral]

I'm a cofounder of the early 2-person startup whose blog post this is.

Yes, it's currently difficult and expensive to bring complex ML to bear on this problem; we are trying to make that easy and cheap. The reason people adopted AB-testing was that it has a positive impact on the metrics they care about; we think the workflow can be easier and more valuable than AB testing. If its easy to use, the extra value should cover the cost.

We're currently focused on trying to communicate that this approach can create value - this blog post, written for a technical audience, is to give some intuition around how the approach works - does that make sense?

We genuinely believe in making it easy to use ML optimisation in this context - that's why we're working on this.