--- title: I wish tech companies knew more about me | daily.dev description: Despite fears that tech companies know everything about users, this author argues the opposite: targeting and personalization are often clumsy and wrong.... canonical: https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: I wish tech companies knew more about me | daily.dev og:description: Despite fears that tech companies know everything about users, this author argues the opposite: targeting and personalization are often clumsy and wrong.... og:url: https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg og:image: https://api.daily.dev/og/posts/gxO3X4arG.png og:image:alt: I wish tech companies knew more about me og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # I wish tech companies knew more about me **[Hacker News](https://daily.dev/sources/hn)** · 4 min read · 0 upvotes · 0 comments ## Summary Despite fears that tech companies know everything about users, this author argues the opposite: targeting and personalization are often clumsy and wrong. Google Chrome shows them a Finnish landing page even though every setting is in English. Spotify and YouTube Music never learn they skip every vocal track in years of listening. Their bank advertises car insurance they already hold with that same bank, and Netflix on Apple TV still asks them to pick a user after 15+ years with only one profile. The author concludes the data is being collected and sold, but rarely used well. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Community take How the wider developer community reacted, aggregated from 1 discussion and 167 comments across hackernews (as of 2026-11-05). **TL;DR:** The discussion largely agrees with the post's framing that personalization is clumsy, but argues this isn't a knowledge gap — targeting is often 'good enough' for advertisers' purposes even when it feels dumb or invasive to users, and the real issue is misaligned incentives rather than insufficient data. **Sentiment:** 10% positive · 35% mixed · 55% skeptical **The case for** - Some say well-targeted ads (e.g. on Instagram) have introduced them to products they genuinely wanted and bought. - A few argue repeat-purchase ads (like showing the same mattress again) are a rational heuristic since buyer's remorse and gift-buying create real repeat-purchase signal. - One person working in ads targeting argues the systems are sophisticated machine-learning stacks, not simplistic, and poor targeting actually hurts advertisers and platforms alike. **The pushback** - Many argue ad systems don't need to be precise because advertisers lose little by showing irrelevant ads, so there's no strong incentive to improve. - Several say the real purpose of data collection is manipulation, price discrimination, and profit extraction rather than helping users, regardless of how sophisticated the models are. - Commenters note which ad gets shown depends heavily on advertiser budget, not relevance, so even perfect targeting can't fix generic brand-spend dominance. - Some find it unsettling that ad-targeting work amounts to building psychological profiling systems at scale, comparing it to propaganda. - Multiple people cite the 'ads for something you just bought' pattern as evidence the systems are often clumsy or poorly incentivized to fix obvious misses. **By community** - hackernews (mixed): A long, multi-threaded argument weighing whether bad targeting stems from technical limits, misaligned incentives, or that it's simply 'good enough' for advertisers' purposes, with real disagreement over how sophisticated and benevolent (or not) ad systems actually are. **Hottest debate:** Whether poor ad targeting (like repeat-purchase ads) reflects genuine algorithmic incompetence or a rational, if unintuitive, statistical heuristic that works well enough for advertisers. **Open questions** - Why don't advertisers fix obviously wasteful patterns like repeatedly advertising something a user just bought, if it would improve revenue? - How much of ad spend effectiveness is actually measurable or justified versus being an industry-wide act of faith? **Highlights** > I worked for Google for 10 years. All of my personal email and all of my work email (back then, Google, now CMU) goes through Gmail. They know basically everything that's ever been sent as a receipt in an email. They know what I watch on YouTube, what I search for Google, and Android's little Google rootkit knows everywhere I go, and by extension, everyone I hang out with. They know I install an adblocker everywhere I can. I rail against advertising and tracking on the internet (this site) all the time. Yet they don't freaking get it. Google has not discovered that I do not like ads. Advertising (mostly) doesn't work on me. I don't buy the shit that is advertised to me. Sometimes, it's the absolute opposite. ...and yet, on the one device I haven't got an ad blocker on, they insist on showing me ads for stuff I WILL NOT BUY. (one specific insurance ad I have been seen for 4+ years--no, no no). I just don't get it. They expect me to pay for YouTube premium or something, I don't know. I won't pay them. Google bought my 30s and now they just can't help but nickle-and-dime my mind from here to eternity. It's kind of infuriating. They don't need to know more about me. What they do know about me should be enough! > — [titzer on hackernews · 3 comments](https://news.ycombinator.com/item?id=50379925) > I work in ads targeting > Google is doing McDonalds a disservice as their advertiser by showing you the ad (and won't be doing the user any useful service either). yes this is right and why the parent is totally off base > That said, these algorithms are simple presumably because they work "well enough". This is totally wrong. Ads targeting "algorithms" are some of the most complicated systems on earth. First of all, it is completely done by machine learning models now not simple algorithms, and within companies who are doing ads targeting well (ie, Google, Meta, Tiktok, and if you want to go down the list to the less competent companies then you can include X and Reddit and others) there is massive internal pressure and competition to get any edge by either improving models or other parts of the ads targeting stack. The top dogs as in Tiktok, Google Search, and Meta have been posting 10+% yoy ads revenue numbers for many years now with a much smaller increase or even flatlining user counts. It's all due to improvements in the ads stack making them more effective and more useful for advertisers (and they and the article in the post would say users as well but HN mostly doesn't subscribe to this viewpoint) driving more total ads spend and a growing economy. > — [Anon1096 on hackernews · 1 comments](https://news.ycombinator.com/item?id=50381913) > Let me ask you this directly, I'd love to hear your takes as somebody working in ad targeting: Don't you think what you're building is kinda... creepy? My perception is that your job is to build a model to psychologically profile people at scale to manipulate them into buying stuff they wouldn't buy otherwise. Now, first of all, that seems incredibly unsettling to me in its own right already. But where it gets really unsettling is if you think even a little bit past the immediate usecase: Once you have this sort of model, who knows what sort of other stuff you can manipulate people into? Should people like Zuckerberg really have the power to do this? And if you trust Zuckerberg, what about other players? Say an authoritarian state somehow managed to get control over these models. Doesn't it seem like you're building an incredibly dangerous thing here? Wonder how you feel about these things and if you've ever had similar concerns. Like, I get that there's probably all sorts of interesting engineering problems involved. But one could say the same thing about von Braun building the V2 - these things aren't just puzzles in isolation! > — [vrganj on hackernews · 1 comments](https://news.ycombinator.com/item?id=50382301) > > Amazon (or whoever) showing you the same stuff you just bought is kind of a separate issue, because it obviously isn't useful to anyone (including Amazon) and surely is so easy to avoid I find it bizarre that it still happens in this day and age. I've asked people at Amazon on the recommendation algorithm side about this, since it comes up so often in discussions. Their answer is that, surprisingly, it is a good heuristic. If you just bought something, you've shown intent, and there's a small probability that you're going to be unhappy with your initial purchase and back on the market soon, for whatever reason. Is the posterior probability that you'll buy a mattress again shortly after buying one, a small chance? Yes, undoubtedly. But is it smaller than the prior probability of a random person who hasn't bought any mattress at all recently, suddenly being on the market for a mattress? Apparently not. Weird things can happen with joint probabilities when both sides of the condition are very unlikely. Sort of like how your chance of having some rare cancer after testing positive on a ~99% accurate cancer screening test is still quite tiny. > — [apetresc on hackernews · 1 comments](https://news.ycombinator.com/item?id=50383127) > I don't think people assume there is literally zero signal. I think their intuition is that the repurchase rate is low. Low enough that that if the advertiser knew the purchase was made, then the advertiser would serve something else with a higher predicted chance of getting a click. It's easy to assign a straw-man a belief there is zero signal and talk down to it. The more nuanced idea that is less obvious goes like this: advertising is such a boondoggle that the aforementioned weak signal actually does represent a higher click-through than everything else in their ad inventory. Advertisers working in predictive targeting like to tell tall tails about their analytical genius. That story about the Target ad campaign predicting someone was pregnant is their ur myth. The basis for their big swinging statistical analysis prowess. Imagine how embarrassing it would be to their carefully crafted image if they had to admit the peak of their profession is hoping people need a 2nd of something that's usually a less-than-once-a-year purchase. > — [dogleash on hackernews](https://news.ycombinator.com/item?id=50381997) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50378942) · 163 points · 167 comments ## Similar posts on daily.dev - [Your Data Knows You Better Than You Think](https://daily.dev/posts/your-data-knows-you-better-than-you-think-uxa2ly9ni) · Medium · 0 upvotes · 0 comments - [EU Financial Institutions Leak Data Through Cookie Trackers](https://daily.dev/posts/eu-financial-institutions-leak-data-through-cookie-trackers-wdfsj6qmq) · Dark Reading · 1 upvotes · 0 comments --- Tags: [#privacy](https://daily.dev/tags/privacy), [#recommendation-systems](https://daily.dev/tags/recommendation-systems) [View this post on daily.dev](https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"I wish tech companies knew more about me","url":"https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg"},"datePublished":"2026-11-05T17:09:56.411Z","dateModified":"2026-11-05T19:54:50.833Z","description":"Despite fears that tech companies know everything about users, this author argues the opposite: targeting and personalization are often clumsy and wrong....","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/6a73cb257b54431679037a3804307292?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/6a73cb257b54431679037a3804307292?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Hacker News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Hacker News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/hn","url":"https://daily.dev/sources/hn"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/i-wish-tech-companies-knew-more-about-me-gxo3x4arg","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"privacy,recommendation-systems","timeRequired":"PT4M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Hacker News","item":"https://daily.dev/sources/hn"},{"@type":"ListItem","position":3,"name":"I wish tech companies knew more about me"}]} ```