In May 2026 Amazon rolled out a new section called About You. Unlike the usual recommendation widgets that simply suggest related items, this area displays a list of characteristics Amazon believes describe the shopper based on every interaction – from purchases and product reviews to voice commands given to Alexa. The company markets the feature as a way to make suggestions more precise, but the public response has turned it into a cultural moment, with users posting screenshots that range from surprisingly accurate to downright bewildering.
Within days the internet was flooded with images of profiles that mentioned favorite hobbies, dietary preferences, and even speculative remarks about family members. The rapid spread sparked a broader conversation about how much data a retailer should be allowed to infer, and whether users truly control the narrative of their own digital personas.
How the “About You” engine creates a shopper profile
The algorithm behind About You pulls from three main data streams. First, it looks at the explicit information a customer provides—names, addresses, payment methods, and items saved to wish-lists. Second, it records behavioral signals such as search queries, clicks, and the timing of purchases, which are captured through cookies and device identifiers. Third, it incorporates input from Amazon’s AI-driven assistant; a casual remark to Alexa like “my cat prefers salmon” is logged and fed into the profiling logic. By cross-referencing these inputs, the system assigns tags like “dairy-free milk fan” or “minimalist traveler” that then surface on the About You page.
Amazon claims the resulting profile improves the relevance of product recommendations. For instance, a user who frequently orders gardening tools may begin seeing fertilizer options, while someone who buys high-end headphones could be shown premium audio accessories. The company also groups tags into broader categories—diet, hobbies, family, household electronics—allowing shoppers to see a summarized view of what the platform thinks they like.
What real users are saying: humor, surprise, and privacy alarm
Social media quickly turned the feature into a meme factory. One user posted a screenshot that listed “flat buttocks” as a characteristic, prompting a flood of amused comments. Another shared a profile that accurately captured an obsession with one-bag travel and a preference for Anker chargers, calling the insight “uncannily spot-on.” Yet other posts revealed bizarre or inaccurate tags, such as a description of a user as a “fifty-year-old man” or a claim that a shopper “has no friends.” These extremes highlight how the algorithm can over-interpret isolated purchases—buying a specialty cheese for a friend, for example, might be logged as a personal “cheese exploration”.
Beyond the humor, many commenters expressed unease about the depth of personal details displayed. One author noted that the profile referenced a negative hotel stay involving a family member—a piece of information the shopper never directly shared with Amazon. Such revelations have reignited the debate over data transparency: how much of a consumer’s life should be distilled into algorithmic guesses, and how easily can users correct or delete erroneous assumptions?
How to access, edit, and what you can (not) turn off
To view the page on a desktop, customers click the account icon, select “Account & Lists,” and then scroll to the “About You” link under the Shopping Preferences section. Mobile users follow a similar path through the app’s profile icon. Once on the page, Amazon presents a list of tags with toggles that let shoppers hide or delete specific entries. Although the platform does not offer a master switch to disable the feature, users can manually prune the profile, remove entire categories, or provide feedback indicating that a particular tag is inaccurate.
The company’s privacy notice explains that data used for About You falls into three buckets: information you actively provide, automatically collected signals (including cookies and device data), and updates received from third-party sources such as carrier delivery data. While Amazon states that the feature is optional in the sense that you can edit what appears, the underlying data collection continues as long as you remain an active customer. This nuance is why privacy advocates argue that the tool, even when edited, still reflects a broader surveillance model embedded within the retailer’s ecosystem.
