Fighting the Algorithm: Can You Actually Beat Surveillance Pricing?

I've spent enough time with gadgets to know that a spec sheet rarely tells the whole story, and the same goes for the 'deals' popping up in your shopping apps. For over a century, we lived with the norm of the fixed price—a standard established by John Wanamaker in the late 1800s. But as I've seen in my own testing, that era is effectively over.

In a recent conversation with Wired, as first reported by the outlet, Lindsay Owens, CEO of the Groundwork Collaborative and author of *Gouged*, explains that big tech has essentially "reinvented the rip-off." She describes a shift toward "surveillance pricing," a term for personalized pricing where companies use personal data to estimate a specific individual's willingness to pay rather than relying on broad market conditions.

**The Loyalty Trap**

We've all downloaded the loyalty apps, thinking we're getting a bargain. In reality, Owens suggests these programs are sophisticated data harvesting operations. She points to a 2004 warning from Duke economist Curtis Taylor, who predicted that high-tech loyalty records would allow firms to identify their most eager customers and charge them more. Essentially, consumers are paying a premium for their own loyalty.

Owens shared a personal example of this data intensity: after requesting the data McDonald's held on her app interactions, she received a 515-page dossier. The company's estimation? There was a zero percent chance she would ever stop being a customer.

**The AI Escalation**

If you think current algorithms are aggressive, the arrival of generative AI and "agentic commerce" is making things worse. These tools are often marketed as assistants to automate shopping, but Owens warns they are being used to supercharge upselling.

According to Wired, the evidence is already appearing in cart totals. Walmart has reported that Sparky cart totals are 35 percent higher than those of non-Sparky carts.

**The Path Forward**

Owens argues that we are at an inflection point. While she has testified before Senator Josh Hawley and previously served as an economic policy adviser to Senator Elizabeth Warren, she notes that federal momentum is slow. The goal, according to Owens, should be regulating these AI agents to ensure they operate under a "best-interest" or fiduciary standard, similar to how lawyers or realtors are required to work on behalf of their clients.

Until the law catches up, the burden is on the consumer to navigate a landscape where the price tag is no longer a fact, but a variable based on how much the algorithm thinks you can stomach.