It should come as little surprise that Amazon collects a vast amount of data about its users based on their purchasing habits. If a customer frequently buys heavy bags of cat litter, the e-commerce giant will reasonably infer that they own cats. Similarly, a steady stream of anti-acne skin products might lead Amazon to guess that the buyer is prone to breakouts. Even though most consumers are acutely aware that algorithms customize their online shopping experiences based on past orders, it remains an unsettling experience to see those personal details laid out in a plain, convenient list—especially when those algorithmic deductions cross the line into uncomfortably intimate territory.
The modern internet is built on data collection, but the transparency tools provided by major tech companies often catch users off guard. This reality was highlighted recently when a Threads user came across a specific section of her Amazon account settings designed to reveal who the shopping giant believes she is. Alongside relatively benign marketing assumptions like "Shops from women’s departments" and "Probably owns a Shark robot vacuum," she discovered that Amazon had deduced she "has flat buttocks."
The discovery quickly struck a chord across social media. "I stumbled upon a page of assumptions that Amazon has made about me based on my purchases and I’m literally speechless," the Amazon customer, posting under the handle @fangirlinmegan, wrote 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 garnered over a million views, quickly attracting a wave of curiosity from other users eager to check what their own Amazon profiles might secretly reveal about them. The viral moment underscored a broader cultural fascination—and underlying unease—with the degree to which automated systems analyze consumer behavior to build psychological and physical profiles of everyday shoppers.
For those curious about what the retail giant has inferred, the information is accessible through standard account settings, though navigating to the specific page requires a few clicks. On desktop computers, users can find the page by hovering over the greeting in the upper right corner, clicking account settings, and locating the shopping preferences section. While this menu allows customers to manually input information such as shoe size, personal interests, and dietary preferences, scrolling to the bottom of the page reveals a hyperlinked option to manage stored information and view the automated profile generated by the platform’s algorithms. Mobile app users can navigate to the same profile data by accessing the menu bar, opening account settings, and reviewing their shopping preferences and personal profile details.
Checking these profiles often yields a mix of accurate predictions, flattering assessments, and uncanny observations. For many users, the system successfully pinpoints niche hobbies and lifestyle habits. One observer noted that Amazon correctly deduced they practice photography, play collectible card games, and are deeply invested in a specific consumer electronics ecosystem. The platform even offered a flattering psychological assessment by noting an affinity for diverse non-fiction reading material, prompting a reflection on being an open-minded intellectual with a thirst for knowledge.
Other reviewers discovered that the retail platform accurately cataloged interests in vinyl records and ceramics, alongside a distinct preference for natural materials in home decor and clothing that prioritizes comfort. While most profiles do not feature anything quite as blunt or startling as the assumption regarding flat buttocks, the viral Threads user later noted that her specific entry was likely the result of purchasing a very particular style of apparel known as "butt scrunch leggings."
The incident highlights a broader conversation about digital privacy and the sheer volume of data accumulated by major technology companies. Tech corporations possess deep wells of information about consumer habits, and it can be jarring for everyday users to realize just how closely automated systems pay attention to the subtle details of how people interact with online platforms. Living in an era defined by pervasive digital tracking and widespread data collection can often feel overwhelming, but discovering a hyper-specific, algorithmically generated physical trait tucked away in an online shopping profile serves as a uniquely humorous and unsettling reminder of the digital footprints people leave behind every day.
