It should not come as a massive surprise that Amazon collects a vast amount of data about you based on what you buy. If you purchase a high volume of cat litter, the e-commerce giant will probably infer that you own cats. If you routinely buy anti-acne skin products, Amazon might easily guess that you are prone to breakouts. Even if everyday consumers are generally aware that platforms customize shopping experiences based on purchase history, it still comes as a jarring surprise to see all of those personal details laid out in a convenient list—especially when those invisible data points get uncomfortably intimate.
A recent viral post on Threads brought this reality back into the spotlight when a user stumbled across a specific section of her Amazon settings where the retail conglomerate lists the assumptions it has made about her identity, lifestyle, and preferences. Alongside more benign, everyday assumptions like "Shops from women’s departments" and "Probably owns a Shark robot vacuum," she found that Amazon had concluded 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," an 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, sparking widespread amusement and alarm across social media. It also sent countless curious users scrambling to check their own Amazon profiles to see what kind of digital dossier the algorithm had compiled on them.
The mechanism to find this hidden page of consumer profiling is embedded within standard account settings, though it is rarely visited by the average shopper. On a desktop web browser, users can locate the page by hovering over the navigation menu where Amazon displays "Hello, [your name]" in the upper right corner, then clicking "Account" under the "Your Account" section. From there, navigating down to the "Ordering and shopping preferences" section leads to "Your Shopping preferences." This area allows customers to manually add information about themselves, such as shoe sizes, personal interests, and dietary preferences. However, the true revelation lies further down the page. Scrolling to the bottom reveals a blue hyperlinked option that reads "Manage your information," which opens the vault of algorithmic assumptions Amazon holds on the account holder.
For mobile app users, the path is similarly hidden within the interface. Shoppers can tap the hamburger icon on the bottom menu bar, then navigate through Account, Shopping preferences, and finally to the "About you" section.
Investigating these profiles reveals a fascinating, if sometimes eerie, cross-section of how modern machine learning models interpret consumer habits. For some users, Amazon accurately gleans details such as practicing photography, playing collectible card games, and being deeply invested in the Apple ecosystem. In other instances, the algorithm attempts flattery, noting that a customer reads diverse non-fiction, prompting reflections on open-minded intellectualism and a thirst for knowledge.
Other observations from colleagues and online commentators show that Amazon regularly notes niche interests in vinyl records, ceramics, a penchant for natural materials in home decor, and clothing that prioritizes comfort. While most users do not encounter anything quite as blunt or personal as an algorithmic assessment of their physical anatomy, those who do can often trace the logic directly back to their shopping carts. In the case of the viral Threads post, the user astutely noted that the assumption about her physical form was likely the direct result of purchasing "butt scrunch leggings."
The viral moment highlights a broader, ongoing cultural conversation about the state of modern digital privacy and data aggregation. Major technology companies and retail platforms inevitably know an immense amount about their users, and it remains jarring to realize just how closely algorithms are paying attention to the minutiae of daily platform usage. In an era defined by alarming surveillance infrastructure and ubiquitous data tracking across digital ecosystems, discovering that an online store has generated a psychological and physical profile based entirely on cardboard box deliveries serves as a stark reminder of the digital footprints people leave behind every day—even if it occasionally results in an unexpected laugh at the algorithm’s expense.
