Taking the shopping cart example: "In a former life, I used to write SQL to extract customer of the week. Basically, select from orders table where basket size is the biggest."
The author decided that 'customer of the week' will be selected by 'biggest basket size'. Not by 'biggest $ amount spent', 'fastest time from add-to-cart to checkout' (and numerous other attributes or combination of them). This decision (the "best attribute") was taken by a human, leaving a field open where a combination of attributes could've resulted in overall better business outcome (how much did 99% of these retained customers shop for, in $ value over lifetime?, etc)
This is possibly what the parent commenter is hinting at - this human decision leaves a lot of optimization scope, where ML could have helped.