Smooth scrolling is a great example. The native API allows a user to interrupt at any point. Most JS implementations are janky as all hell and users suffer.

Scold design choices all you like but don’t expect to be listened to. Especially when you’re not providing any actual reasons why “carousels are still a bad idea”.

It’s widely understood and documented that carousels are a bad idea, and plenty has been written about it.

(I should clarify that the problems are with carousels as a way of presenting diverse widgets; as a way of presenting a collection of pictures about a single item, it can be acceptable.)

If your goal is user friendliness, it would behoove you to use a design which is user friendly.

Using a design which is user unfriendly and asking "how can I make this unfriendly design seem friendly" seems to be approaching the problem from the wrong direction: the design choice itself is the biggest contributor to user friendliness.

Either you care more about yourself and your design choices than user friendliness, or vice versa, and both are totally valid options, but don't pick the former and claim the latter.

I too dislike carousels… But at the same time the Amazon homepage prominently features a carousel, and I know that Amazon ruthlessly A/B tests homepage variants so the carousel presumably tests well… so I’m not sure that they’re actually “bad” in some sort of universal objective way.

No, it doesn't. It tests which one is more positive, not which is is positive.

> Like the A/B test that repeatedly demonstrated that after you buy a blender, your most likely purchase is another blender... (which Amazon still hasn't fixed nearly a decade later)

That isn't an A/B test.

"positive" in the sense of "always answering questions with 'yes'", not in the sense of "positive numbers". Turns out when you start linking people's compensation to their datascience results, the results start to lean in whatever direction optimises for compensation...

> That isn't an A/B test.

A series of A/B tests. All the alternatives failed to produce better metrics than the status quo, so everyone became satisfied that their local minima was optimal

1. Maybe you didn't like it so returned it, but are still in the market.

2. Maybe it was a gift and you now want one yourself (or vice versa)

For something relatively expensive it may be the best expected value add even if the chance of repurchase is only 1%. Maybe the repurchase rate is 1% while the base purchase rate is 0.1%.

I'm not sure it is, but it seems entirely possible that this is actually a smart move by the ad engine.