It should come as little surprise to modern consumers that Amazon collects vast amounts of data based on purchasing habits. When someone consistently buys cat litter, the e-commerce giant reasonably infers that they own a cat. If a customer frequently purchases anti-acne skin products, Amazon’s algorithmic engines might deduce that they are prone to breakouts. Even though digital shoppers are well aware that their online experiences are continuously customized according to past purchases, it still manages to catch people off guard when all of those personal assumptions are laid out in a convenient, neatly organized list—especially when those digital inferences veer into territory that feels uncomfortably intimate.
This digital reality recently came to light for a Threads user who stumbled upon a specific section of her Amazon account settings. This is the area where the shopping behemoth displays what it believes it knows about an individual customer. Alongside relatively benign assumptions like "Shops from women’s departments" and "Probably owns a Shark robot vacuum," she discovered an algorithmically generated conclusion that left her utterly stunned: Amazon had deduced that she "has flat buttocks."
"I stumbled upon a page of assumptions that Amazon has made about me based on my purchases and I’m literally speechless," wrote the Amazon customer, known online as @fangirlinmegan, in a viral post on Threads. "I mean it ain’t wrong, but damn did you have to call me out like that?"
In less than a day, the post exploded across the platform, garnering over a million views and sparking widespread curiosity. Thousands of users flooded to their own accounts, eager to discover what kind of psychological and lifestyle profile the retail giant had quietly built behind the scenes.
The mechanism for uncovering this hidden data profile is embedded deep within Amazon’s account architecture. On a desktop web browser, users can navigate to the page by hovering over the greeting in the upper right corner, selecting the account dashboard under the primary management section, and locating the shopping preferences settings. While this menu is traditionally used by customers to manually input personal details—such as shoe sizes, specific lifestyle interests, and dietary restrictions to tailor product recommendations—scrolling to the bottom of the page reveals a hyperlinked option labeled to manage personal information. Clicking that link unveils the full extent of the algorithmic profile that Amazon has quietly compiled. On the mobile application, users can find the same information by accessing the main menu, navigating through account settings to shopping preferences, and opening the profile overview.
For many users, the profiles offer a mildly amusing reflection of their hobbies and consumption patterns. For instance, tech journalists and casual shoppers alike have found that Amazon’s automated profiling accurately gleans that an individual "practices photography," "plays collectible card games," or is deeply "invested in the Apple ecosystem." In some cases, the algorithms even manage a subtle compliment, noting that a customer "reads diverse non-fiction," prompting witty reflections on being an open-minded intellectual with an insatiable thirst for knowledge.
Other common discoveries among shoppers include accurate interest markers for vinyl records, specialized ceramics, a distinct penchant for natural materials in home decor, and clothing preferences that prioritize comfort above all else. While most shoppers find relatively mundane markers detailing their consumer habits, the viral Threads user noted that her uniquely personal and blunt profiling was almost certainly the direct result of purchasing a specific wardrobe item: butt-scrunch leggings.
Incidents like this highlight a broader, more pervasive reality of the modern digital landscape. Major technology companies possess staggering amounts of data about ordinary people, and it can be jarring to realize just how closely automated systems pay attention to the granular ways consumers interact with digital platforms. In an era increasingly defined by alarming surveillance mechanisms and ubiquitous data tracking across both the web and the physical world, discovering that a retail algorithm has quantified your physical attributes serves as a stark reminder of the invisible digital footprint left behind by everyday online shopping.
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