[levbrie]

> They may arrived at the guidelines using ML, but it's possible that their guidelines wouldn't be right for the types of emails you are sending out.

This is a great point, and it's something that users ought to consider with nearly every application of machine learning that ends with a definite recommendation to the user. Machine learning can be used to solve many many different types of problems - when it comes to solving problems related to human interaction, the insights that it has will tend to function more like the rules for running an effective business-focused popularity contest than the rules for crafting meaningful emails to every possible audience. That said, if you happen to be sending a business email and want nothing more than to improve the likelihood of response, this seems like a great tool for the job.

[baydinalex]

Sort of true, in the sense that the product isn't separately trained for sales emails vs personal emails vs internal business emails, etc.

But the calculations we chose don't provide a lot of constraints, and the variances were not as high as you'd likely expect. So I'd be comfortable saying that the recommendations generalize well to a vast majority of situations.