Canadian shoppers already compare flyers, loyalty offers and unit prices, but a newer issue deserves a spot on the grocery watch list: surveillance pricing. Also called algorithmic personalized pricing, it means a retailer or pricing service may use data about a shopper to estimate what that person is willing to pay, then show a different price than another shopper sees for the same item. The topic became more visible this month after The Conversation and Canadian Grocer highlighted Canadian concerns, and after the Competition Bureau summarized public feedback on algorithmic pricing. This is not the same as a normal weekly sale or a store-wide price change. The consumer problem is opacity: if the shelf, app or website does not explain why a price appears, shoppers cannot easily tell whether they are seeing the market price, a loyalty discount, a targeted offer or a personalized markup.

The Competition Bureau’s 2025 discussion paper says algorithms and data analytics are increasingly used to set or recommend prices, and that more than 60 companies in Canada offer services claiming to optimize prices with algorithms. That does not mean every grocery chain is secretly charging every household a different price today. It does mean the technology and vendor market are already here, across sectors such as retail, hospitality, transportation and ticketing. For shoppers, the practical takeaway is to watch the places where prices are already most fluid: grocery apps, delivery platforms, personalized coupons, online marketplaces, third-party sellers and loyalty-account offers. A paper flyer is usually easy to compare. A logged-in digital price, delivered through an app that knows your buying habits, is harder to audit.

There is an important difference between dynamic pricing and surveillance pricing. Dynamic pricing changes with broad conditions, such as demand, time of day, inventory or weather, and generally applies the same rule to customers in the same situation. Surveillance pricing uses personal data, browsing history, location, device signals, loyalty behaviour or past purchases to tailor the price or offer to an individual. A personalized coupon can be helpful when it gives you money off an item you already buy. The risk is that the same data can also reduce your ability to compare, nudge you toward a higher-priced substitute, or make a “deal” look special when it is not the best available price. In grocery shopping, where households buy repeat items every week, small differences on staples can add up quickly.

Canadian consumers do not need to panic, but they should build a few low-effort habits. First, compare logged-in and logged-out prices when buying online, especially for pantry staples, baby products, pet food and household basics. Second, check a competitor’s app or public flyer before assuming a personalized offer is the lowest price. Third, use unit pricing, not just the headline discount, because algorithms and promotions can make package sizes harder to compare. Fourth, take screenshots of surprising price differences, including date, store, location setting and whether you were signed in. If a retailer advertises a price and then charges something different, that documentation matters. Finally, avoid giving every app unnecessary permissions; location, notification and tracking settings can often be limited without losing the ability to shop.

The Competition Bureau’s “What We Heard” report is useful because it shows the public concern is not only about prices going up. Respondents raised transparency, the “black box” nature of pricing tools, affordability of daily essentials, and the possibility that vulnerable shoppers could be harmed if algorithms identify urgency or limited ability to switch stores. The Bureau also noted competing views: some respondents want stronger oversight or bans, while others warn that rules should not block legitimate innovation. For a shopping site, the balanced point is simple: technology can help retailers manage inventory and can help shoppers find discounts, but the price must be understandable enough for a normal person to compare. If two shoppers see two different prices for the same product at the same time, the store should be clear about whether the difference is a loyalty reward, regional pricing, delivery fee, subscription benefit or something else.

The best budget defence is still a boring one: keep your own reference prices. Pick 15 to 25 repeat items your household buys often, such as milk, eggs, rice, pasta sauce, coffee, detergent, diapers or canned tomatoes, and note the usual good price in a simple phone note. When an app says “just for you,” compare it against your own number before adding to cart. For online orders, try building the cart before signing in, then after signing in, and check whether item prices, fees or substitutions change. For in-store shopping, scan receipts before leaving the parking lot, because personalized digital offers do not always apply cleanly at checkout. Surveillance pricing may sound technical, but the shopper response is practical: compare outside the algorithm, keep evidence, limit data where you can, and reward retailers that make prices clear.

Source trail: - The Conversation: “Your browsing history could soon set your grocery bill — and Canada isn’t ready for it” — https://theconversation.com/your-browsing-history-could-soon-set-your-grocery-bill-and-canada-isnt-ready-for-it-281618 - Canadian Grocer: “Your browsing history could soon set your grocery bill—and Canada isn’t ready for it” — https://canadiangrocer.com/your-browsing-history-could-soon-set-your-grocery-bill-and-canada-isnt-ready-it - Competition Bureau Canada: “Algorithmic pricing and competition: Discussion paper” — https://competition-bureau.canada.ca/en/how-we-foster-competition/education-and-outreach/publications/algorithmic-pricing-and-competition-discussion-paper - Competition Bureau Canada: “Consultation on Algorithmic Pricing and Competition: What We Heard” — https://competition-bureau.canada.ca/en/how-we-foster-competition/education-and-outreach/publications/consultation-algorithmic-pricing-and-competition-what-we-heard