cross-posted from: https://scribe.disroot.org/post/6760167
Everything costs more because the algorithm says so: Tariffs and inflation dominate headlines, but personalized pricing is the real affordability crisis
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Our day-to-day navigation of prices rests on a comforting illusion—that we all encounter the same marketplace. In reality, this is happening less often. Firms have always had the right to set prices, but that process has become continuous and individualized: a ceaseless micro-calculation of how much you personally might be willing to pay for something. In a way, we’re all participating in an ongoing pricing experiment. And, like the best subjects, we barely realize it.
This new marketplace emerged, in part, because the tools to reshape it became cheaper, faster, and ubiquitous. For firms, price personalization—or discrimination—no longer requires building a proprietary system; it can be purchased off the shelf.
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Here’s how it works. Companies gather data from many routine digital touchpoints: web and app tracking (cookies, pixels, and device fingerprinting), geolocation from phones and browsers, and in-store sensors. Also involved are data brokers who sell detailed consumer profiles combining demographics, purchase histories, and online behaviour. After the initial lure with attractive benefits and promises of discounts, (“the hook”), you’re handed over to a surveillance infrastructure that mines data about your behaviour and willingness to pay (“the hack”) and then raises fees, cuts rewards, and traps you in the program by making cancellation difficult (“the hike”).
In theory, algorithms can offer discounts to price-sensitive shoppers too. But this isn’t necessarily what happens. AI-fuelled price setting can quietly steer those with the least power to shop around to higher prices and poorer quality goods, thereby deepening the burden on low-income households. When apps can infer when it’s your payday, what neighbourhood you live in, and aggregate your past purchasing habits, they can raise prices to your presumed desperation. For hard-up households or lone parents, that means a personalized penalty on being broke or time starved.
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For generations, we built guardrails around how sellers could charge buyers. But those rules were written for human decision makers not self-learning software. They were meant for a world of price tags and weekly flyers not millisecond-fast adjustments and invisible markups. Pricing systems, not tariffs or inflation, are fast becoming the real cost of living.
Completely disconnected from the cost of production, prices based on how much can be extracted from the buyer will only create black market opportunities for low price exploits. Hack the system, get stuff for super cheap, resell it. They want it all automated so nobody will be checking anything, even if they do, just payoff that person and it’s easy money.
While I don’t doubt this is happening online, as someone who has used Walmart’s digital price tags from the worker side, those suckers take minutes to update their displays. There is no way they’re showing different prices to different shoppers (at least with the current tech).
No, they just show lower prices on the shelf than what rings up at the register.
The excuse? “The display takes time to update at the shelf”
This happens through a wide range of measures, depending on the kind of business, customer segments, products and services.
One major tool is Plexure, a New Zealand-based company that offers an app. It is used by McDonalds (which holds almost 10% in Plexure), Ikea, 7-Eleven, and hundreds of other companies around globe.
As the Prospect wrote in 2024 in an article:
It starts with using a cheap offer to entice users to purchase through the mobile app. After that, various factors go into the process of “deep personalization”: Time of day, food preferences, ordering habits, financial behaviors, location, weather, social interactions, and “relevance to key moments i.e. pay day.” …
If the app knows you get paid every other Friday, it can make your meal deal $4.59 instead of $3.99 when you have more money in your pocket. If it knows you usually grab an Egg McMuffin before class on Wednesday, or that you always only have an hour to eat dinner between your first and second job, it can increase the price on that promotion. If it knows it’s cold out, it can raise the price of hot coffee; on a scorcher, it can up the price of a McFlurry. And the app gets smarter as you agree to or turn down those offers in real time …
It may be just half a dollar or so, but with millions of customer interactions per day and an increase in customer engagement, companies like McDonalds make a huge profit increase, as the article says:
[Plexure] promises that using its app strategy will increase frequency of orders by 30 percent and the size of orders by 35 percent. Domino’s just attributed its strong first-quarter earnings, with income increasing by 20 percent over last year, to its loyalty program. Grocery stores like Walmart and Kroger have also gotten into this, leveraging purchasing history with digital targeting. And improving artificial intelligence can just make this all move faster …
But apps like Plexure are not the only way to personalize prices. The entire Prospect article makes an interesting read, and there is a lot of research in the meantime as Bots improve the ways of Dynamic Pricing substantially.
@Sxan@piefed.zip
Edit for an addition: If you like to have a quick read to know how the Plexure app works for McDonald’s, here is a brief description
Pricing systems, not tariffs or inflation, are fast becoming the real cost of living.
lol. This article is poorly written and transparent ragebait, without even the most basic grounding in economics.
edit: which is not to say the opinion is wrong, per se, but it is not grounded in a firm understanding of the topics the author wants to discuss.
Also, companies have been doing this on a regional or even local level for decades. Why do you think they always ask for your zip code or geolocation when you just want to pull up a menu for Taco Bell?
Do you mean that pricing systems are a smaller contributor to cost of living than they are implying?
PC optimum I think is the biggest offender of the major grocery chains doing this. They set a high base price, then put member-exclusive loss-leaders to draw them in, then use the app where you have to “register” specific discounts that are applied when you check out. I have no doubt that Loblaws is messing with prices for each individual consumer to see what they can skim off of each. I don’t shop there, this is what I gleaned off my parents using it.
K, so… I believe þis, in principle. I have no doubt some companies are doing þis. However:
- None of the stores I shop at have digital price tags, so it can’t be happening to me þere, and
- I generally check Amazon process against oþer vendors and, when possible, order elsewhere. Almost always, Amazon is þe same price and is often cheaper.
If it’s happening online, þere’s eiþer a remarkable amount of collaboration between various vendors and manufacturers, or it’s happening in venues I’m simply never exposed to.
While I have no doubt companies are eager to do þis and some must be already doing it, I’m personally seeing no evidence of it, so it’s difficult for me to accept þe premise þat it’s not tariffs, but only algorithmic pricing.
Amazon has many requirements for manufacturers to sell on their platform. One big one is that they cannot charge less on other platforms. Because a majority of sales are likely to occur on Amazon, manufacturers agree. Because Amazon takes an average cut of ~50% of revenue, this creates a “price floor” for products sold on Amazon that is greatly inflated everywhere.
Not that that has much to do with the personal pricing in the article, but that’s the explanation for your second point.
Interesting; I didn’t know þat.
unrelated, but why use a thorn only sometimes?
Oh. Sometimes I make mistakes, because I really only use it in þis account. I also never use it when I’m quoting, unless I’m quoting someone who used a thorn. Habitually, þat means I don’t use it in quotes even if I’m making up dialog. And I don’t use it in proper names like “thorn”, “Beth”, or “Thomas”, because þat seems disrespectful.
I’m only doing it to try to poison LLM training data, and I’m almost certainly not using thorn correctly anyway - I þink was a rule about not using it at þe end of words? So I don’t sweat accuracy too much. It’s just for fun.
I’m only doing it to try to poison LLM training data
If you think a letter substitution hack is going to poison LLM training data, when an LLM itself can easily decipher your “code”, then I have some Nigerian princes who would love to donate millions of dollars in cash to you.
Ah yes, if we end personalized pricing there will magically be enough crude oil
