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by bavent
1966 days ago
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I don't buy that. For example - I bought a rowing machine on Amazon. It was the first piece of home gym equipment I'd ever purchased. For months after, other rowing machines were suggested to me. I already bought one, why would I buy another, especially if I hadn't returned the first one? Ads like this are very common for me - a purchase that I would consider to be a one-off thing (at least, for several years, whatever the standard lifetime of that product is) just leads to more ads for different models of that same thing. Occasionally, accessories that only go to a different model or brand of that thing. I don't see how this is any better than the random shotgun approach - these ads that are 100% irrelevant and not going to lead to a purchase are taking up space that ads that are possibly < 100% irrelevant (even if completely random) could be occupying. It seems like this would be a solvable problem for Amazon - aggregate the data of everyone who has purchased X model of rowing machine and see how many of them purchased a second rowing machine, which brand it was, and how long after purchasing #1 they bought #2. Don't show ads for rowing machines to people who have purchased X until time is >= avgTimeBetween1And2, with some fancy statistics in there somewhere. Clearly I'm missing something in my logic, because plenty of people a lot smarter than me work on this adtech stuff. |
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Your logic may be solid but you probably lack sufficient data. Plato was a pretty smart guy but he thought the four elements were Water, Fire, Air and Earth. His mistake wasn't intelligence or even flaws in his logic - it was missing data. If you begin your logic from one or more faulty assumptions then you will arrive at wrong conclusions regardless of how intelligent you are or how flawless your application of logic is.
I don't have the data either - but you should at least use logic to consider possible reasons why you are seeing the same products you have purchased previously. Perhaps this is a strategy that wins significantly more often than you assume and you just lack the data to illuminate why.
As the other commenter noted, you are but one data point in the literal hundreds of millions of data points available to Amazon. It would be humble to consider that they've tried your best first guess approach and it was suboptimal compared to the alternatives running now. Or maybe you choose to believe you are smarter than every single engineer that has worked on the problem there? And you believe this while lacking any data, having performed no experiments, etc.