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20 years and they still think I need more than one vacuum. ht: https://twitter.com/kibblesmith/status/724817086309142529 https://twitter.com/kibblesmith/status

• teej 9y ago
  Given that Amazon's system can be described as: "... for every item i1, we want every item i2 that was purchased with unusually high frequency by people who bought i1", I'd say it's completely rational that their system recommends you vacuum cleaners if you've already bought one.
• wlesieutre 9y ago
  Same experience. I ordered a pair of speaker stands from Amazon on Monday. This morning they sent me an email saying "Amazon.com has new recommendations for you based on your browsing history." It was a bunch of other speaker stands.
  • stult 9y ago
    Well, do you happen to know how many other people are repeat buyers of similar products? Maybe a large number of buyers end up buying a second set of speaker stands because they don't like the ones they just bought or because they're enthusiasts who gift them or have multiple audio setups. Just because it seems unlikely someone would be a repeat buyer in a given product category doesn't mean it isn't profitable to target every buyer as if they might be.
    • oh_sigh 9y ago
      It's an interesting point, but I would hope that they would factor in the negative impact on non-repeat-buyers. Some buyers(at the very least: me) feel remorse or regret over their purchase if they are presented with a bunch of other options which may be better or cheaper than whatever they chose to buy.
    • trowawee 9y ago
      Almost no one? Obvious anecdote alert, but I don't know a single person who shops on Amazon who hasn't made the exact same observation. Many/most big ticket items are, for most people, a once-every-X-years purchase, and yet Amazon's recommendation system can be counted upon to suggest another TV, another DSLR...it's remarkably terrible for a system that's been under active development for twenty years.
      • wlesieutre 9y ago
        Plus my speaker stands haven't even been delivered yet. Amazon knows this.
      • Godel_unicode 9y ago
        Annecdata ahoy: I bought a TV from Amazon and they stopped showing me more TV's after I rated it. Maybe they think you're still in the market and might send those stands/DSLRs back because you didn't rate them.
    • wlesieutre 9y ago
      If Amazon's default assumption is "The product we sold you was garbage, maybe you want buy a different one instead" then I think they have even bigger problems. EDIT: And if I liked it so much that I wanted to gift it to someone, why show me the 5 competing stands instead of the one I know is good from personal experience? A person who has multiple audio setups wouldn't need prompting to about it either. If they like the ones they got, they'll order it again. If they didn't like it, they'll look for something else without needing an email about it.
• saosebastiao 9y ago
  In some senses, their reasoning is rational. Some models work for some situations better than others...that recommender model might work exceptionally for someone trying out different brands of the same consumable product (like Natural Deodorants, for example). For other products, an accessory product recommender model might work better (like for Vacuums and vacuum attachments). And since the number of scenarios is infinite, you might as well try as many as possible and stick with all of the ones that show promise. Which is fine until 90% of your browsing consists of scrolling past different recommended product widgets, which seems to be the case at Amazon now. At some point, taking different working models and trying to work on converging their benefits into a more monolithic model would be a huge benefit.
  • boomzilla 9y ago
    Don't think there is much rationale behind all these models. It's more like P(would buy a vacuum | bought a vacuum) > P(would buy X | bought a vacuum) where X is a single product. Now P(would buy a vacuum | bought a vacuum) < sum(P (would buy X | bought a vacuum)) for X that is not a vacuum, but what would be the recommendation? Hey, you bought a vacuum, come back and buy some non-vacuum stuff? For most recommendation UIs, you would need a hero item that make people want to click on. It might turn out that another vacuum is probably the best item for some people to click on, and go on to buy other stuff once they are on the site.
    • saosebastiao 9y ago
      The reason you see such an obvious false positive in this case isn't because people who bought vacuums are likely to buy another, but rather that people who look at vacuums are likely to buy a vacuum, and the model hasn't accounted for whether you've already bought one. A different recommended might use different types of conditionals (items bought instead of items looked at, for example), and also have success in different areas (like recommending iPhone cases for iPhone owners). In order to converge the models in a Bayesian framework you'd have to deal with the combinatorial explosion of products and event conditionals which might be pretty gnarly. But some convergence work would be better than none, otherwise you end up with 20 different recommender widgets on a page. Overall I don't think amazon's approach to date has been bad...it's just time to clean up a bit.
• ryanworl 9y ago
  I can certainly imagine a world in which you, having just purchased a vacuum, are more likely to purchase a different vacuum than any random person they just chose to show that recommendation to. For example, you might return your first one and then want to buy a different one. Instead of letting you forget about it and then months later potentially buying elsewhere, they preempt you and offer new ones soon after. This is obviously speculation, but I think Amazon could come up with something better if they felt it pressing i.e. recommending the same product category was no better than random products.
  • blacksmith_tb 9y ago
    My instinct is that they are willing to live with showing some comparatively weak recommendations occasionally if that means not adding layers and layers of exceptions on top of their basic recommendation engine. And/or they have projected that the ROI isn't there for building in more sophisticated recommendations.
    • resu_nimda 9y ago
      At Amazon's scale, a very very small increase in the effectiveness of recommendations can represent millions in revenue. They probably do have layers of exceptions, and custom-built software used by teams of "editors" to manually manage these exceptions. Not to mention the experimentation system where they are simultaneously testing hundreds of things from CSS one-liners to new ranking algorithms. It's probably a pretty complex beast with the weight and inertia of a core system that's been continuously in production through 20 years of growth. They probably continue to invest heavily in it, the ROI is there, it's just a really hard problem for them at this point. Their engineers probably curse its limitations and would love to rewrite/replace old and outdated parts, and indeed there will be teams working on that, but those projects will either die out or spend so much time reaching feature parity with the bloated existing system that it ends up looking much the same.
    • baddox 9y ago
      Why would this be an "exception"? The basic item-based collaborative filtering described at the beginning of the article finds items that are likely to be purchased by someone who has purchased a specific item. I'm pretty sure that it's true that someone who buys a vacuum is much more likely to buy another vacuum. It may seem counterintuitive, and may not be true for you after you just bought a vacuum, but I see no reason to believe that Amazon's algorithm isn't working properly and giving Amazon a lot of value.
• linkmotif 9y ago
  Yep, this. I look at something and it recommends it to me for months. I buy something and same thing. It's quite obtuse. Maybe there's something to it, maybe it does a good job growing revenue, but there's noting elegant about it.
  • baddox 9y ago
    > Maybe there's something to it, maybe it does a good job growing revenue, but there's noting elegant about it. It almost certainly does a good job growing revenue, and they almost certainly care more about revenue than about the perception of "elegance." You say that as if it's unusual or unexpected.
    • linkmotif 9y ago
      > You say that as if it's unusual or unexpected. Absolutely not :P. Hey, whatever works. But I think many people on this subthread, including me, are wondering whether something more elegant would produce more revenue.
• fs111 9y ago
  I bought an expensive camera in March, they still insist I need 5 more from different vendors.
• hammock 9y ago
  We always had three vacuums in the house growing up: a main canister vacuum (kept in a closet), an upright for the hard kitchen floor (kept handy), and a dustbuster (also kept handy). Three tools with different uses.
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• dahdum 9y ago
  Reminds me of Netflix recommendations. They keep recommending I "continue watching" the ~45 seconds of credits I missed from the last dozen shows I watched. Most lists have movies/shows I've already seen at the top still. I'm sure there's some reason behind it all, whether technological, user behavior, or obscuring a small catalog. I wish I knew what it was.
  • bradjohnson 9y ago
    Or if I watch a couple episodes of a show and decide I don't like it and click the "Stop recommending this show" button, it'll still show up in the "Continue Watching" list. What's the point of the button?
    • Deimorz 9y ago
      You can go into your viewing activity (only available from your account page on the desktop site, I think) and delete the show from there, and then it should remove it from "Continue Watching". It's not an obvious or straightforward thing to need to do, but seems to work.
      • NoCoastCoder 9y ago
        That's definitely available in the app as well.
    • Cyphase 9y ago
      IIRC, "Continue Watching" shows things you haven't finished watching in most-to-least recent order. There isn't any aspect of "recommendation" to it beyond that; you could go find the worst rated, least recommended content on Netflix, play it for a minute, and it'll be first on your "Continue Watching" list. Have you ever seen something being _recommended_ after you clicked that button?
      • bradjohnson 9y ago
        It's a UX failure. There's no point in recommending something that I've seen and there is almost no way I can know that I don't want to watch something without seeing at least a little bit of it. For all intents and purposes, the "Continue Watching" list is a recommendation of things to watch. If I thumbs down or ask Netflix to stop recommending it, I shouldn't see it prominently displayed anywhere when I open the app.
• foobiekr 9y ago
  my personal ultimate example of this was I bought a lawnmower. and then for two months, all of my amazon advertisements, the ones following me around the web, were for lawn mowers. even a vacuum I could see some weird "yes, maybe I could buy one as a gift." but a lawnmower? no.
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  • arkitaip 9y ago
    Just for months? Amazon keeps recommending me the same 90s Radiohead albums based on stuff I bought a decade+ ago. Retargeting can be so on point these days so I don't get why Amazon's recommender systems have been horrible for years. All they have to do is to peek at my cart, which I use as a wishlist, to figure out what I'm currently interested in.
• surement 9y ago
  The suggestions are probably based on browsing history rather than on buying history. It's not that surprising; you likely browse for multiple items, which helps make inferences about what you might want to buy. You only buy a small fraction of the items you browse, much of them unrelated. Taking one of those points (your purchase) and guessing that it belongs to a cluster of points that shouldn't be suggestions is not obvious. Further, basing suggestions on purchases might give terrible results given that your purchases are mostly unrelated.
• DonaldFisk 9y ago
  That sucks. The problem is that the algorithm seems to be unable to distinguish interchangeable items (e.g. vacuum cleaners, lawnmowers, Swiss Army knives) which you need exactly one of, similar items (e.g. different death metal albums, or Hammer horror movies) which if you bought one of, you'll probably want some others, and connected items (e.g. different parts of a course) where you'll probably want all the others.
  • icebraining 9y ago
    It's weird, though; seems like an "average time between purchases" associated with each category would be an obvious metric to use in the algo.
    • TeMPOraL 9y ago
      A small problem might be that they're probably trying to optimize that metric, i.e. reduce your average time between purchases in each category...
  • andrewingram 9y ago
    Some fungibility factor attached to each product wouldn't be amiss here
• TheSpiceIsLife 9y ago
  Maybe they've worked out that showing people more of what they just bought makes people go on and on about Amazon's recommendation system all the time. And when people are complaining about something they endlessly repeat "Amazon Amazon Amazon Amazon". When you have nothing to complain about you're less likely to evangelise.
• biztos 9y ago
  To be fair, I myself have two vacuums. Maybe buy another and see what happens.
• roselan 9y ago
  Well, if you bought some particular brand I won't name, you will need one per year.
• dcminter 9y ago
  It's certainly an annoying behaviour - but my personal suspicion is that it arose from the system's origin as the recommender for a bookstore. I mean if I read a book by P.G.Wodehouse it in fact IS likely that I want to read another similar (but not identical) book by P.G.Wodehouse. Quite how they managed to hang onto this quirk is a different question that I can't even fathom the answer to (I don't believe they haven't noticed and I find it very hard to believe this is actually the optimum sales technique for vacuum cleaners!)