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I tend to agree regarding the home page content, but I’ve found the “customers also bought” sections quite helpful lately, especially when looking at industrial
by sbr464 8y ago
I tend to agree regarding the home page content, but I’ve found the “customers also bought” sections quite helpful lately, especially when looking at industrial/technical products.
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- goldenkey 8y agoUnfortunately the customers also bought section is not really "recommendations" as much as a table join.
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- cheeze 8y agoThat is a rather simplistic view of it
- goldenkey 8y agoIts not my view, that's what it is. No machine learning is necessary to generate that section. Just a lot of intersected purchases from a huge amount of customers, sorted by frequency.
- imustbeevil 8y agoDo you work at Amazon, so you know this is how it works? Or are you projecting how you imagine it works? Because if I'm an Amazon dev I'm 100% not just showing a 45 year old woman who buys a TV the same "other people bought" as a 25 year old man. I'd definitely run the same ML on each section, because the whole point is to understand the closeness of connections between personal traits and purchases, and it is impossible for a human to outperform in that task.
- goldenkey 8y agoI used to work at Amazon. Demographics aren't needed when you have a ton of customers for which to take the intersection, and sort by weighted (frequency, time of purchase.) Any non related purchases won't show up nearly as often or close in purchase date as related ones on a large sample of customers. This is just a consequence of having big data, which makes the noise floor insignificant. ML shouldn't be thrown at everything indiscriminately.
- harshaw 8y agoThis was the collaborative filtering of 15 years ago. It's likely they have made improvements since then.
- GrinningFool 8y agoI also find it a much more helpful section than 'recommendations'. Something simpler is more effective in this case, in that it gives me much more relevant results. Why is that unfortunate?