The Federal Trade Commission (FTC) has issued orders to nine major companies—including Delta Air Lines, United Airlines, JetBlue, Lyft, Uber, DoorDash, Instacart, Target, and Walmart—requiring them to disclose how they set consumer prices and, in some cases, worker compensation using personal data.
The FTC’s market study, conducted under Section 6(b) of the FTC Act, marks an information-gathering inquiry and does not allege any legal violations. The agency seeks details on whether prices or pay vary based on factors such as loyalty program participation, web browsing habits, or device usage. Companies have 45 days to respond, with the FTC reserving the right to seek court enforcement for non-compliance.
Airlines, gig platforms, and retailers targeted
The inquiry spans three industries:
- Airlines: Delta Air Lines, United Airlines, and JetBlue.
- Gig platforms: Lyft, Uber, DoorDash, and Instacart.
- Retailers: Target and Walmart.
For ride-share and delivery services, the FTC is examining whether driver compensation is determined by opaque formulas that may consider factors like phone usage or acceptance history. The agency has requested documentation of the inputs, tools, and procedures used to adjust prices or pay.
What is personalized pricing?
Personalized pricing refers to setting different prices for different customers based on personal data or behavior. The FTC’s study aims to assess whether such practices disproportionately affect certain consumers or workers, particularly in sectors where pricing transparency is limited.
The commission has not yet commented on potential outcomes, and the companies named have not publicly responded to requests for details. The FTC’s authority under Section 6(b) allows it to conduct broad market studies without a specific law enforcement purpose, though findings could inform future regulations or enforcement actions.
Next steps
The FTC will review the responses and determine whether further action—such as rulemaking, investigations, or legal challenges—is warranted. The study’s findings could influence consumer protection policies and labor practices in industries reliant on algorithmic pricing and compensation models.