You scan your loyalty card. You get a discount. Everyone’s happy.

But that card also records everything you buy. Every week. For years.

What if your grocery store used that history to set your own personal prices?

Not the same price for everyone. A price just for you, based on what it thinks you’re willing to pay.

Economists have now run the numbers on exactly that scenario.

The result is one of the strangest twists in economics: most shoppers would pay less, and consumers as a whole would still lose.

Economists modelled prices set from loyalty-card histories

Grocery loyalty programs already collect detailed purchase histories.

Right now, according to the researchers, retailers don’t use them to give each customer an individual price.

So economists Isis Durrmeyer, Jean-François Fournel and Mario Samano asked: what would happen if they did?

They built an economic model of grocery shopping in which the store learns each customer’s preferences from their past purchases, then sets prices tailored to them.

The more you buy, the better the store gets at guessing what you’d be willing to pay.

One year of purchase data would raise store profits by 7%

With just one year of purchase history, the model predicts store profits would rise by 7.1%.

That’s a meaningful gain in grocery retail, a business known for thin margins.

And one year of data is enough to capture about two-thirds of the extra profit the store could make if it knew exactly what every customer was willing to pay.

In other words: your loyalty card history alone tells the store most of what it would ever want to know.

84% of shoppers would benefit

You might expect personalized pricing to mean everyone pays more.

Not in this model.

84.1% of consumers would benefit.

How? Under a single price, some shoppers find things too expensive and buy less, or not at all. With personalized pricing, the store can lower prices for price-sensitive shoppers to win their business.

So for most people, personalized prices would actually be cheaper.

The other 16% would lose more than everyone else gained

Because the remaining 16% would get hit hard.

These are shoppers the store identifies as willing to pay more. Their prices go up, and their losses are big enough to outweigh all the gains of the majority combined.

Add it all up, and total consumer welfare falls. Meanwhile, the store’s profits go up.

It’s like a restaurant bill where most people at the table pay a little less, a few people pay much more, and the restaurant pockets the difference.

Staying out of the loyalty program would signal a willingness to pay more

There’s another surprising finding.

The researchers worked out the store’s ideal loyalty program. It would actually charge a membership fee.

Normally, you’d expect people to skip a program that costs money. But in the model, most consumers still sign up.

Why? Because refusing to join sends a signal.

If you don’t hand over your data, the store may assume you’re the kind of shopper who doesn’t care much about price. And it can price you accordingly.

So people pay to join just to avoid looking like they’d pay more.

Counting winners isn’t enough

This study shows something that applies far beyond groceries.

A policy, product or technology can make most people better off and still leave society worse off overall, if the losses are concentrated on a smaller group and are large enough.

That’s why counting winners isn’t enough. You also have to ask how much each group gains or loses, and where the money ends up.

For personalized pricing, the answer in this model is clear: many small winners, fewer big losers, and a store that comes out ahead.

What the study doesn’t show

This is a model, not a real-world experiment.

No store actually introduced personalized pricing in this study. The numbers are predictions from an economic model built on assumptions about how shoppers behave, how stores compete and how prices would be set.

Real-world results could be very different, especially if competing stores responded, regulators stepped in or shoppers changed their behavior.

The study is a CEPR discussion paper that has not yet been peer reviewed.

And it does not show that skipping a loyalty program would save any individual shopper money.

The real question is who pays more

Stores are collecting more data about shoppers than ever. This study shows how valuable that data could become if it were used to set individual prices.

It also gives regulators and consumers a sharper question to ask about personalized pricing. Not just “do most people pay less?” but “who pays more, how much more, and who keeps the difference?”

A deal that’s good for most shoppers can still be a bad deal for consumers.