Calling All Shoppers: On Grocery Store Loyalty Cards

By Deborah Pierce, Seattle Press. Posted July 25, 2002.

Grocery store loyalty cards ask consumers to trade away extremely detailed personal information in return for the promise of savings -- a promise that a few informal studies imply is inflated or even mythical. In this article, I want to focus on loyalty cards as part of a broader context: the profiling increasingly being introduced in grocery stores and other retailers. While there are certainly potential benefits to these technologies, I believe that the tradeoffs that you have to make for the convenience and claimed lower prices aren't worth it.

Deals?

The usual rationale for loyalty cards is that it makes stores more efficient at stocking their shelves with products you want, and allows them to pass the savings on to you.

If you think about this for a moment, it doesn't make sense. If all the grocery stores want is to improve their efficiency, they just need to know what items are being sold and what items are bought at the same time. There's no reason for them to need loyalty cards for this. They can record all of this information without knowing who was making the purchases.

Unsurprisingly, then, the few informal studies that have been done so far have shown that claims of savings by supermarkets may be largely inflated. For example, some stores appear to raise their base prices after introducing a card, and simply have the "discount" from the card reduce the price to its pre-card level. If you have a card, you're saving compared to the people who don't have cards -- but not when compared against the prices before cards were introduced.

In fact, the reason that stores introduce cards is so that they can profile and target their customers more accurately -- not to give you savings, but to increase their bottom line. Additionally, your personal information can be sold or traded to third parties.

One way that grocery stores create profiles is by the use of data mining. Data mining is a process that is used to predict future behaviors and trends by discerning patterns and relationships from large amounts of warehoused raw (from disparate sources) data through the use of statistics and other mathematical techniques*.

There are positive aspects to data mining such as fraud detection and identification of items that are commonly bought together. But there is a darker side to data mining too.

Use the address information from your loyalty card application to match up your shopping history with data from other databases or public records (income, how much you paid for your house), and now the grocery store knows what kinds of "specials" to offer you -- or not offer you, as the case may be. Price discrimination is thus one consequence of data mining and profiling.

Even worse, information about your shopping habits can be accessed with a subpoena or warrant and used against you in court proceedings. In a well-publicized "trip-and-fall" case in California, a man shopping at a Southern California grocery store sued after falling in one of the aisles. It was reported (although the store has since denied it) that the store threatened to use his shopping history -- which included large amounts of alcohol -- against him in the proceedings.

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