The point is that if you have multiple ad slots you can cover a wider range of buyers. For example, the chances that someone would click on a 5th grill accessory ad is probably pretty low if they didn’t click on any of the previous 4. But if they’re thinking of returning the grill they already purchased, they might be interested in a different model. Averaged over all buyers, the best strategy might well be to show a mix of accessories and other models.
Or, depending on the numbers, all grills or all accessories could also make sense. My broader point is that it’s perfectly possible the best strategy doesn’t line up with people’s intuition, which is why we use ML for recommendations in the first place.
I mean, sure, I don't have any scientific studies to back this up.
But I really don't feel like this is a case where "intuition might be completely wrong" applies—buying a $400 grill, and then just going back and buying 3 more $3-500 grills, just isn't something that people do on a regular basis. Same for vacuum cleaners, refrigerators, etc. And yet Amazon does regularly advertise these things to us after such large purchases.
The only logical conclusion is that it's cheaper for them (in the short term, at least) not to update their ad/recommendation algorithm to take into account the nature of large one-time purchases.
The question isn’t “do they do it on a regular basis” it’s “do people do it often enough that the expected value of showing that product is higher than something else.”
> The only logical conclusion is that it's cheaper for them (in the short term, at least) not to update their ad/recommendation algorithm to take into account the nature of large one-time purchases.
Is that really the only logical conclusion? I’d think that “I don’t know people’s buying behavior on Amazon well enough to understand why this happens” should at least be a possible explanation.
I'm trying to imagine a scenario where someone returns a single-purchase item and then purchases the same exact item as the result of seeing an ad for it. They're already aware of the item and if they want another one after return they're probably just going to exchange it because something is wrong with it. It's not even a sale and I'm skeptical that seeing the ad has a strong influence on whether a customer asks for a refund or a replacement.
ML is not some holy grail that always produces optimum algorithms. It depends heavily on inputs and on the assumptions, both explicit and implicit in the training data. My guess is Amazon does not have a "single-purchase item" model and it's not something the AI was trained to identify and so they aren't specifically excluded from groups of "similar-or-same" items.
I think it is far more likely that Amazon is optimizing the cost of development against the marginal benefit of not showing ads for single-purchase items than that this is somehow driving more sales.
1. Buy a large ticket item (e.g. furniture).
2. See an ad on Amazon for a different/nicer/better/faster shipped version.
3. Buy it.
4. Cancel the old order.
Is that a common pattern? No idea. But it’s not crazy to me that it happens often enough that it’s worth it to Amazon to show similar items to people who already bought them.
Or, depending on the numbers, all grills or all accessories could also make sense. My broader point is that it’s perfectly possible the best strategy doesn’t line up with people’s intuition, which is why we use ML for recommendations in the first place.