Retailers and their behind-the-scenes partners are increasingly able to gather detailed information about your location, search queries, purchases, and online behavior. According to the Federal Trade Commission (FTC), these pricing models can leverage personal data to gauge a consumer’s spending potential. This issue is now gaining traction in Washington. On August 19, 2026, the FTC released a proposed enforcement policy related to personalized pricing.
The FTC acknowledges that while they can’t prohibit personalized pricing altogether, companies that do not transparently inform consumers about how their personal data impacts the prices they see could be in violation of federal consumer protection laws. So, is the data being collected actually influencing the prices, discounts, or products you come across? Research provides some insights and offers steps you can take before making online purchases.
Maryland Aims to Ban Surveillance Pricing in Grocery Stores
The concept of dynamic pricing is something you’ve probably encountered. This model adjusts prices based on factors like supply and demand, inventory levels, time, or location. For instance, rideshare fares can surge when demand spikes, and hotel prices fluctuate based on availability. However, not every shopper will see the same price at all times. Personalized pricing diverges from this as it uses information tied to individual consumers to determine the specific offers they receive. Thus, two people searching for the same item might see different prices based on their unique data.
Additionally, there’s a practice called price steering. This involves retailers keeping actual prices unchanged but altering the order in which products are displayed, potentially promoting higher-priced items first. The FTC observed that while consumers expect prices to adjust with market trends, they might be caught off guard by the influence of their browsing patterns or purchase history on the prices they see.
What Companies Can Learn About You
The FTC has found that third-party pricing companies can utilize surprisingly detailed information to assist retailers in customizing prices, promotions, or product placements. This data can encompass:
- Your exact or approximate location
- Your browsing activity and history
- Your shopping and purchase records
- Items left in online shopping carts
- Demographic details
- Time and location of purchases
- Your website behavior and preferences
- Even your mouse movements on a page
The FTC’s research indicated that these pricing middlemen engage with at least 250 clients across various industries, from groceries to clothing. They can integrate first-party data with external data sources such as loyalty programs and data brokers. While this doesn’t prove that every client applies individualized pricing, it illustrates the capability to use extensive consumer data to impact prices, discounts, and product visibility.
A 2026 Rideshare Test Reveals Price Discrepancies
A recent investigation brought the Uber example into sharper focus. In June 2026, Consumer Reports released findings from a study involving 174 participants checking over 40 routes in the U.S. The analysis showed a median pricing gap of 42.4% between the lowest and highest prices across 30 selected routes.
Interestingly, individuals monitoring the same ride within minutes could see varied prices. Although Consumer Reports attempted to minimize time-related pricing effects during the study, they couldn’t account for all influencing factors within Uber’s and Lyft’s pricing mechanisms, such as driver availability and traffic conditions.
Both Uber and Lyft contested the findings, asserting they do not use personal data for base fare calculations and do not engage in behavioral pricing. Hence, while the study highlighted that riders could see significantly different rates for similar trips at similar times, it didn’t necessarily tie those price variations to personal data.
What Your Internet Provider, Websites, and Advertisers See
Different Grocery Prices for Online Shoppers
Online grocery shopping further showcases these issues. In December 2025, a collaborative report revealed that nearly three-quarters of grocery items tested on Instacart had different prices for various consumers. The study, which involved 437 shoppers in four U.S. cities, found some price differences as high as 23%. On average, the totals for identical shopping lists varied by about 7%. Researchers estimated this could equate to around $1,200 annually for a typical family of four. Instacart vehemently disagreed with this estimation, asserting that the price variations were due to randomized tests and did not rely on personal details.
Instacart has since discontinued the pricing tests and claims that customers shopping for the same item at the same store and time will now see uniform prices. This investigation demonstrated that shoppers could receive different prices during the tests, but it didn’t confirm that Instacart utilized personal data to determine pricing.
Historical Context of Online Price Personalization
Customized pricing has been observed long before the current surge in AI-driven systems. For example, in 2014, Northeastern University researchers found evidence of price discrimination on major retail and travel websites, with some sites offering exclusive discounts based on user membership. In another instance, ProPublica noted in 2015 that The Princeton Review charged varying prices for an online SAT prep package based on geographic ZIP codes, revealing how demographic data can influence pricing.
Thirteen Ways to Mitigate Personalized Tracking When Shopping
While there’s no failproof method for securing the lowest online prices, you can take steps to limit the information shared with retailers, data brokers, and tracking firms, thereby enhancing your ability to compare offers.
1) Check Prices Before Signing In
Look at a product while logged out before accessing your retailer account, then compare prices after signing in. Any price differences don’t necessarily indicate personalized pricing, as discounts for members can also affect this.
2) Choose Guest Checkout When Possible
If a retailer doesn’t require an account, checkout as a guest to prevent your purchase from being added to a logged-in shopping history. While not anonymous, this can limit your data footprint.
3) Decline Optional Tracking Cookies
When prompted, refuse optional cookies to minimize tracking, though essential cookies may still be needed for cart functionality and security.
4) Limit Data Brokers’ Access to Your Information
Data brokers gather information from various sources. Reducing their available data can help limit your overall digital footprint, although this doesn’t guarantee lower prices.
5) Browse in a Private Window
A private browsing mode usually restricts cookies and session data, providing a degree of separation from normal browsing activities. However, it does not offer complete anonymity.
6) Utilize Privacy Opt-Outs
Look for options to limit data sharing, depending on the retailer’s policies and regional privacy laws.
7) Control Location Access
Check which apps can access your exact location and change settings to approximate only if precise data isn’t necessary.
8) Manage App Tracking Permissions
Limit app tracking across your devices to reduce some data collection, although retailers can still access information you provide directly.
9) Clear Cookies and Site Data Regularly
Clearing cookies can help remove stored identifiers, but some tracking methods may still recognize your device.
10) Compare Prices Across Platforms
Before a significant purchase, assess the retailer’s app and website, then check prices against other retailers to ensure a comprehensive view.
11) Leverage Price History Tools
For products with price tracking services, verify that current prices are genuinely lower than those in recent history.
12) Read Discount Fine Print
Offers may come with conditions, such as membership requirements, so ensure that you understand all implications before committing.
13) Consider Using a VPN
A VPN can mask your public IP address, altering how retailers perceive your location. While it doesn’t eliminate your account details, it can provide an added layer of privacy.
Kurt’s Key Takeaways
It’s striking how much data influences your shopping experience online. While we lack concrete evidence that all retailers are setting individualized prices, it’s clear that advanced technologies can utilize location, behavior, and history to influence pricing structures. My recommendation: compare prices before making a purchase, limit unnecessary tracking, and don’t assume that the initial price you see is the best available. The less data you provide, the less there is for companies to create detailed profiles about your shopping tendencies.
