Full Breakdown
Amazon’s “About You” Feature Reveals Detailed Shopper Profiles
By Drooid · · How we work
How the Feature Works and What It Reveals
Amazon introduced the “About You” feature in May, allowing customers to view and edit a consolidated list of inferred preferences. By tapping the “Me” tab in the Amazon Shopping app (or hovering over the user’s name on a computer), shoppers can see attributes the platform has deduced from purchase history, Whole Foods visits, and shared-account activity. Reported examples include ownership of a Shark robot vacuum, preparation for a Bluey-themed birthday, a family member’s lawn mower and vegetable garden, coworkers’ cocktail-making habits, and a colleague’s consistent chicken purchases at Whole Foods. The system also generates more personal descriptors such as “flat buttocks,” which sparked a viral reaction on Threads.
User Reactions and Viral Threads
A Threads user shared the “flat buttocks” inference, describing the label as “literally speechless” and questioning why Amazon would highlight such a detail. The post quickly went viral, prompting other users to compare their own profiles. Many reported accurate predictions about plant-based milk consumption, coffee intake, favorite foods (e.g., French fries), number of children, and types of pets. Several commenters noted that the feature’s accuracy felt “pretty spot on,” especially when it aligned with known household habits.
Official Statement from Amazon
Amazon has framed the feature as a tool for improving recommendation relevance. The company explained that understanding shopper preferences is essential for delivering high-quality, personalized suggestions.
“Understanding your preferences is fundamental to providing you with high-quality, relevant recommendations,” — Amazon
What This Means for Consumer Privacy
The detailed inferences demonstrate Amazon’s capacity to analyze purchasing patterns across its e-commerce and grocery divisions to generate granular personal profiles. While the company offers users the ability to edit or delete individual attributes, the viral response highlights growing public awareness of how algorithmic inference can surface unexpected personal details. The episode underscores the tension between personalized shopping experiences and the desire for greater transparency and control over data-driven profiling.