On October 18, the Associated Press published a lengthy piece on growing discomfort among US shoppers with "smart" retail pricing. This isn't just the familiar dynamic pricing (think Uber or airlines, where the price climbs with demand), but also the digital shelf labels that Walmart and Whole Foods are rolling out in place of paper tags, and "algorithmic" or "personalized" pricing — also called surveillance pricing — set using a shopper's location, income, or purchase history. According to the National Conference of State Legislatures, lawmakers in at least 30 states considered bills on these practices in 2026, and Maryland, New Jersey, and Connecticut have already passed restrictions on using shoppers' personal data to set what they pay.
The technology is outrunning shopper trust
The central paradox here is that digital shelf-tag technology is, on its own, almost neutral: per the AP, one retailer researchers looked at saw little surge-style price spiking after switching to electronic tags — prices there still update on a fixed, usually weekly, schedule. The problem isn't the tags themselves; it's that shoppers no longer understand the logic behind a price and tend to assume the worst. The AP gives a telling example: social media posts claimed Walmart's electronic tags scan customers' faces or phones — never confirmed, but serious enough that the company had to publicly deny it on CEO John Furner's blog, where he wrote that prices don't change "based on the weather, time of day, or who is shopping." Kearney's Katie Thomas describes the moment as a "major tension" over who ultimately controls pricing — the company or the shopper.
Where the legal line sits after the Target and Amazon cases
There's a hard legal backdrop here too. Target settled a $5 million lawsuit in 2022 over allegations that its app showed different prices inside versus outside its stores using geofencing, and now states officially that it does not personalize prices. The FTC is suing Amazon over its internal "Project Nessie" algorithm, which the regulator alleges helped predict when competitors would follow a price increase, generating over $1 billion in excess profit — Amazon calls the allegations a "gross mischaracterization" and says the tool didn't work as intended and was scrapped. In parallel, the FTC itself has proposed a policy under which failing to disclose that a price was set using a shopper's personal data could, on its own, violate consumer protection law.
Picture a small three-store grocery chain in the Lisbon area considering dynamic pricing on perishables — fresh bread, fish — to cut end-of-day waste. On paper, it's a sensible idea: the price drops near closing, less food gets thrown out. But if customers find out the store's app is using their loyalty data or purchase history, rather than just the time of day, to calculate that discount, the reputational hit can wipe out the entire savings from reduced waste — especially in Portugal, where GDPR and sensitivity around data surveillance run higher than the US average. The gap between "the price changes with the time of day" and "the price changes based on who you are" is the gap between a routine promotion and a potential reputational and legal crisis.
Honestly, there's no simple "automate your pricing and win" answer here. The upside of dynamic pricing is real — less waste, tighter margins — but it scales non-linearly with how transparently a business explains its pricing logic to customers, and with the specific regulations in its country. A business thinking about automating prices should plan the communication in advance — what changes, why, and whether it's the same for everyone — rather than simply flipping on the algorithm and waiting for complaints.
At Dayava, we help businesses roll out automation — dynamic pricing and personalization included — in a way that stays transparent to the customer and secure on data, rather than turning into a source of reputational risk.
If a similar solution interests you for your business, leave a request at dayava.pt/contactos/.