In the realm of online shopping, Ruby Szpeflicki, an accounting clerk from Greenwood, N.S., dedicates significant time each month scouring the web for discounts to share with fellow deal seekers. However, she has observed a concerning trend of prices constantly fluctuating, which she finds frustrating. This phenomenon, known as dynamic pricing, involves algorithms tracking users’ online activities, such as social media interactions, recipe searches, and product browsing, to adjust prices based on individual data.
According to Mark Daley, the chief AI officer at Western University, personalized pricing driven by online behavior has been ongoing for years. With the integration of artificial intelligence (AI), companies can rapidly gather and utilize even more detailed customer information to tailor pricing strategies. The extent of personalized pricing through AI remains largely undisclosed, as it operates within a complex system that experts refer to as a “black box.”
When individuals visit websites, they encounter pop-ups requesting consent for tracking cookies, which capture various data points including clicks, keystrokes, and purchase history. This information, as highlighted by Daley, can be shared with third parties or leveraged by businesses to create detailed customer profiles. Modern AI technologies like AI chatbots can further enhance data collection capabilities, transforming unstructured information into valuable insights about consumer preferences and behaviors.
Algorithmic pricing utilizes this wealth of data to determine the optimal price each individual is willing to pay for a product, leading to personalized offers rather than standardized pricing. As explained by David Dunbar, this approach results in a multitude of personalized pricing rules that are not transparent to consumers, potentially limiting their ability to compare prices across different vendors.
The legality and regulation of algorithmic pricing in Canada currently lack comprehensive oversight. The Competition Bureau initiated public consultations in 2025 to address concerns surrounding algorithmic pricing, particularly its impact on consumer vulnerabilities. While the consultations aim to inform future actions rather than immediate policy changes, they underscore the need for increased awareness and potential regulatory measures in the future.
Personalized pricing strategies are not confined to online platforms, as evidenced by longstanding practices in physical retail environments like car dealerships and grocery stores. With advancements such as electronic shelf labels facilitating rapid price adjustments, concerns have been raised about the potential expansion of dynamic pricing in traditional brick-and-mortar stores. While these developments are observable in physical spaces, online surveillance through algorithms remains a pervasive practice, influencing consumer purchasing decisions based on intricate behavioral analysis.
To mitigate algorithmic monitoring, individuals can clear browsing history and disable location tracking to limit data collection by algorithms. Practicing caution with AI interactions and opting for offline shopping with cash transactions and minimal data-sharing through loyalty programs can also safeguard privacy. Daley emphasizes the collective responsibility of Canadians in determining the balance between privacy rights and technological innovation in shaping the future landscape of consumer data protection.