It should not come as a surprise that Amazon collects data about you based on what you buy. If you purchase a high volume of cat litter, Amazon will probably infer that you share your home with felines. If you routinely buy anti-acne skin products, the retail giant might guess that you are prone to breakouts. Even though most consumers understand that modern e-commerce platforms customize shopping experiences based on past purchase history, it still comes as a shock to see all of those personal assumptions laid out in a convenient list—especially when those details get uncomfortably intimate.
That realization hit home for one user on Meta’s Threads platform recently, sparking widespread curiosity, amusement, and a renewed conversation about corporate data collection. The user stumbled across a specific section of her Amazon settings where the retail giant outlines its psychological and lifestyle profile of the shopper. Alongside relatively benign assumptions such as "Shops from women’s departments" and "Probably owns a Shark robot vacuum," she found that Amazon had concluded she "has flat buttocks."
The candid and startling 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, drawing reactions from thousands of users who were suddenly eager to check what their own Amazon profiles might secretly reveal about them. The viral moment opened a window into the inner workings of corporate profiling, reminding consumers just how granular automated data inference can be when algorithms comb through years of order history.
For those curious enough to investigate their own digital dossiers, finding the page requires navigating a few layers of account settings. On desktop computers, users can locate the information by hovering over the greeting in the upper right corner where Amazon displays the account holder’s name, then clicking "Account" under the primary account management section. Under the "Ordering and shopping preferences" heading, selecting "Your shopping preferences" brings up a page where customers can manually add information such as shoe sizes, personal interests, and dietary restrictions.
However, the real goal for curious shoppers is not to update dietary preferences or inform Amazon that they have stopped eating meat, but rather to see what automated profiling has already generated. Scrolling to the bottom of that preferences page reveals a blue hyperlinked option reading "Manage your information." Clicking that link pulls back the curtain on the specific demographic and behavioral categories the platform has assigned to the user profile.
Mobile app users can access the same data by tapping the menu icon from the bottom navigation bar, then navigating successively through Account, Shopping preferences, and finally the "About you" section.
Exploring these profiles often yields a mix of accurate predictions, amusing coincidences, and occasionally uncanny psychological insights. For instance, checks on various personal accounts reveal that Amazon has successfully gleaned that certain shoppers practice photography, play collectible card games, and remain deeply invested in the Apple ecosystem. In some cases, the algorithms even offer flattering summaries, such as noting that a customer reads diverse non-fiction—prompting the reasonable reaction of appreciating the platform’s recognition of intellectual curiosity and open-mindedness.
Other reporters and colleagues investigating their own profiles found that Amazon correctly noted their distinct interests in vinyl records and ceramics, alongside a clear penchant for natural materials in home decor and clothing that prioritizes comfort. None of those discoveries approached the deeply personal and somewhat startling specificity of "has flat buttocks," but social media context quickly provided a logical explanation. The Threads user who posted the viral screenshot noted that the assumption was almost certainly the result of purchasing "butt scrunch leggings," demonstrating how specific product categories feed directly into blunt algorithmic labels.
Incidents like this highlight a broader, ongoing reality of the modern digital landscape. Tech companies know an immense amount of personal information about their users, and it can be jarring to realize just how closely automated systems pay attention to everyday platform usage. Consumers navigate a world defined by alarming levels of digital tracking and data aggregation, from targeted advertising networks to widespread public surveillance technologies. Yet, despite the pervasive nature of corporate data collection, there remains a uniquely jarring quality to seeing an algorithm summarize private physical traits or lifestyle habits in a plain text list. For now, millions of internet users are left checking their settings, laughing at the digital mirror held up by their shopping history, and wondering what else the algorithm thinks it knows.
