Digital price tags replace traditional signs in grocery stores

Prices for everyday goods are being set by complex algorithms that use customer data and artificial intelligence tools to predict how people will respond.

Digital price tags are increasingly replacing traditional paper signs in grocery stores, sparking concerns about fairness and transparency. The shift has left consumers feeling uneasy and questioning whether prices are adjusted based on individual behavior or other factors.

Some critics have taken to social media to express their frustration with the high-tech pricing system, using terms like "surveillance pricing to describe what they see as an invasion of privacy. Others have pointed out that dynamic pricing is not a new concept, citing examples from the travel industry where prices change based on demand.

The use of algorithms and personal data has raised concerns about who ultimately has control in these transactions - the companies or the consumers. According to experts, there are ongoing debates about how to balance business needs with consumer expectations for fairness and transparency.

While some argue that digital price tags save time and ensure accurate pricing, others remain skeptical about the motivations behind this shift towards high-tech pricing.

The debate over high-tech pricing methods has sparked concerns about consumer data collection and transparency. Some critics argue that companies are not doing enough to inform customers about how their personal information is being used to set prices.

However, a closer look at the numbers suggests that dynamic pricing may be more nuanced than initially thought. According to Decodo, a web data company, price changes in the US have been recorded across various product categories, including electronics, clothing, and home improvement supplies. What's striking is that about half of these changes were actually decreases.

This finding contradicts consumer assumptions that dynamic pricing only leads to higher prices. It appears that companies are adjusting their prices in response to changing market conditions, rather than simply hiking prices for individual consumers. Dynamic pricing can involve a range of tactics, including surge pricing, which has been used by ride-hailing services like Uber during periods of high demand.

Legislators and regulators are taking notice of the growing trend towards dynamic pricing and algorithmic pricing. In response to consumer concerns about data collection and transparency, lawmakers in at least 30 states have proposed measures addressing these issues. The Federal Trade Commission has also weighed in, proposing an enforcement policy that warns businesses against failing to disclose their use of personal data for individualized pricing.

The spread of digital price labels to major US retailers like Walmart and Whole Foods has raised concerns among consumer advocates and labor unions. These electronic displays allow stores to update shelf prices quickly and easily without having to physically replace paper tags.

Retailers typically use these digital labels to make regular price updates, often on a weekly schedule, as shoppers value consistency in pricing. According to Asa Farquhar of Relex Solutions, a retail technology company, frequent changes are not necessarily linked to higher prices during peak demand periods.

A study of electronic shelf labels at an unnamed grocery chain found that there was virtually no surge pricing after their introduction. This suggests that retailers may not be using digital labels as a means to inflate prices during busy periods.

The use of digital price labels has also sparked concerns about personalized pricing, where customers are offered different prices and discounts based on their individual characteristics. Some advocacy groups have referred to this practice as surveillance pricing, highlighting the potential for businesses to collect and use personal data to customize prices.

An FTC staff report released in January 2025 highlighted the role of intermediaries that offer tools to help businesses tailor prices and promotions. These intermediaries worked with at least 250 clients, including grocery and clothing retailers, raising questions about the extent to which businesses are using personal information to customize prices.

Restrictions on using personal data for price setting have been implemented in several US states. In Maryland, New Jersey, and Connecticut, lawmakers have enacted legislation that limits the use of shoppers' information to determine their prices. The Maryland and New Jersey laws specifically target grocery stores, with exceptions made for certain loyalty discounts and promotional offers.

Connecticut's legislation takes a broader approach, covering a wider range of retail purchases. This move comes as concerns grow about the potential misuse of personal data in price setting. Critics argue that companies are using shoppers' information to charge different prices based on individual behavior or demographics.

A high-profile lawsuit against Target has also shed light on the issue. In 2022, California prosecutors sued the retailer over allegations that its app displayed lower prices before customers entered stores, only to raise them once they were inside. The company agreed to a $5 million settlement and ceased using geofencing technology to increase prices.

Target claimed that the app functionality in question was intended to provide shoppers with accurate pricing information, which can vary across different locations and channels. However, the retailer maintained that it did not use personal data or behavior to personalize prices. Despite this, critics argue that such practices can be misleading and unfair to consumers.

The issue of algorithmic pricing has also been explored in a recent investigation by Consumer Reports, Groundwork Collaborative, and More Perfect Union. The study found that Instacart shoppers were shown different prices for identical products at the same stores. In response, Instacart ended its testing of what it described as random assignment", assigning shoppers to groups rather than setting prices based on their personal information.

The use of artificial intelligence in setting prices is becoming increasingly widespread across various industries, according to recent research. A global consulting company surveyed over 2,200 business leaders from 28 countries and 39 different sectors, revealing that nearly half of respondents utilized AI software for market intelligence gathering.

Market intelligence typically includes tracking competitors' prices, which can inform pricing strategies. In fact, 41% of the survey participants reported using AI to gather this information. Meanwhile, a further 28% employed AI-powered real-time price optimization techniques, designed to achieve specific business objectives such as maximizing profits or clearing stock.

The National Retail Federation has weighed in on the matter, stating that algorithmic pricing is merely an advanced version of traditional retail practices. These involve monitoring and adjusting prices based on various factors including supply, demand, seasonality, competitors' prices, and more.

Some critics have accused companies of using pricing algorithms to stifle competition, leading to lawsuits against major retailers. The Federal Trade Commission (FTC) has been particularly active in this area, with a 2023 anti-monopoly lawsuit filed against Amazon highlighting concerns over the use of algorithmic tools to manipulate prices.

A trial is scheduled for next year to determine the fate of Project Nessie, an algorithmic tool developed by Amazon that was allegedly used to identify products whose prices could be raised without affecting competitors. The e-commerce giant claims the tool was intended to prevent unsustainably low prices but ultimately failed to achieve its objectives and was discontinued before the lawsuit was filed.

A recent consumer lawsuit against McDonald's alleged that its pricing system uses nonpublic sales data from competing locations to coordinate prices. However, the company claims this tool was intended to prevent unsustainably low prices but ultimately failed to achieve its objectives and was discontinued.

The lawsuit accused McDonald's of using this pricing strategy to set identical prices at different locations, a practice that could be seen as price-fixing. In response, the fast-food giant stated that the tool was made available to U.S. franchisees to help them set individual restaurant prices, but it was not used for coordinated price-setting.