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.
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.
I don't have the industry expertise to know how true it is, but I've seen it stated numerous times in threads like this that this is entirely intentional. Supposedly the data shows that a person who just bought a rowing machine is actually quite likely to buy another one (because they aren't satisfied with the first one, because they collect rowing machines, etc) compared to most other demographics.
Sampling methodology. Every ad impression in your sample was shown to the same person, but the ad industry is interested in billions of people.
But for the sake of argument let's say there is some small increment. What is the cost we are willing to pay for that? Databases that know exactly how much time we spend on the toilet? Political disinformation campaigns? Insurrection attempts?
It's like making baby monitors a little bit more convenient, but in the process opening the door for pedo hackers to speak directly to your children's cribs. Tiny conveniences aren't worth sacrificing everything we have.
It doesn't matter to Facebook/Amazon whether or not they show you ads you are interested in (or that might impress you with how deep they understand you as a person). It only matters if advertisers get better results than they would get by spending their ad money on TV, Newspapers, Magazines, Radio, etc.
Maybe it is the best we can currently do and maybe it isn't objectively great. But the real question: is it better? I mean, better than the random shotgun approach that was TV, magazines, bus wraps, billboards, etc. Is it better than the spam flyers or "yellow pages" the post office delivered to every single household in some geographic area?
Rather than compare to some idealized perfect, we should compare to the practical alternatives. Maybe this is legitimately the best we can currently do given the state of AI and machine learning. If that is the case, the right question for both advertisers and consumers is whether or not it beats the available alternatives. Because if it does, and advertisers seem to think it does, then that explains why Google and Facebook are worth what they are worth and how they can afford to pay what they pay.