How Companies Charge You More Based on Your Shopping Data

Your shopping history may be doing more than helping companies recommend what to buy. As consumers spend more of their lives shopping online, companies have access to an enormous amount of information about their behavior. Every search, click, purchase, abandoned shopping cart and browsing session can potentially become another piece of data used to understand what a customer wants and how much that customer might be willing to pay.

This practice is often referred to as surveillance pricing or personalized pricing. It involves using information about individual consumers to influence the prices, discounts or promotions they receive.

What Is Personalized Pricing?

Personalized pricing occurs when a company uses information about an individual consumer to determine the price, discount or offer presented to that person.

That is different from traditional dynamic pricing, where prices can change because of factors such as demand, inventory, timing or supply. Personalized pricing adds information about the customer into the equation.

Companies can potentially use information such as a person’s location, previous purchases, browsing behavior and shopping history when determining which prices or promotions to display.

For example, a retailer could determine that someone frequently purchases a particular product and is unlikely to shop around. That information could potentially influence the promotion offered to that customer.

Your Shopping History Can Reveal A Lot

Your purchase history can tell companies far more than simply what you bought.

A retailer may be able to determine how frequently you purchase certain products, what brands you prefer, how much you typically spend and which promotions encourage you to make a purchase.

Online behavior can provide an even broader picture. Companies can collect information about searches, clicks, browsing patterns and transactions to create detailed profiles of consumer behavior.

Some systems can also use information from outside sources or make predictions about a shopper based on their previous activity.

Location Can Also Matter

Where you shop can become another important piece of information.

Location data can reveal where someone lives, works or regularly shops. In some circumstances, that information can be incorporated into systems designed to personalize offers or prices.

That does not mean that every retailer is charging customers different prices based on where they live. However, location can be one of many data points available to companies attempting to understand individual shoppers.

The Difference Between A Discount And A Higher Price

Personalized pricing does not necessarily mean that one person is always shown a higher price.

A company could use consumer information to give one shopper a targeted discount while another customer receives the standard price.

In another situation, a retailer could determine that a particular shopper is already likely to purchase an item and decide not to offer that person a discount.

That means personalization can affect consumers even when the listed price itself does not change.

Companies Can Use More Than What You Tell Them

The information used to build a consumer profile does not necessarily come directly from a checkout form.

Retailers can collect information through their own websites, loyalty programs and shopping platforms. Other companies can also provide data, technology and analytical tools that help businesses understand consumer behavior.

This can create a complicated chain between the shopper and the final price.

A retailer might have information about a customer’s previous purchases while another technology provider could analyze browsing activity or other consumer data. Those pieces of information can potentially be combined to create a more detailed picture of a shopper.

Artificial Intelligence Can Make It Easier

The growing use of artificial intelligence and automated algorithms has also made it easier for companies to analyze enormous amounts of consumer information.

Instead of manually examining individual shoppers, automated systems can process large amounts of data and identify patterns.

These systems can potentially help companies predict which customers are likely to buy a product, respond to a discount or continue shopping even if the price changes.

That does not automatically mean the technology is being used improperly. The concern comes from how much personal information is being used, how transparent companies are about that practice and whether consumers understand how their data affects the shopping experience.

What Consumers Can Do

Consumers cannot always determine whether a particular price has been personalized because companies generally do not explain every factor behind their pricing systems.

Shoppers can still compare prices across multiple retailers and check whether prices change over time. It can also be useful to look at whether a discount requires a membership, account or loyalty program.

Seeing different prices does not automatically prove that a company is using personal data to charge someone more. Prices can change for ordinary reasons, including inventory, demand, timing and promotions.

The bigger issue is how much personal information companies collect and whether that information is being used to influence what individual consumers pay.

As shopping becomes increasingly digital, consumer data has become valuable for far more than advertising and product recommendations. It can potentially help companies understand what shoppers want, how likely they are to buy and how much they may be willing to spend.