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What Amazon says it uses
Amazon describes personalization as a way to help customers find products they may want or need. In a May 13, 2026 announcement about its About You feature, the company named purchase history, searches, product reviews, Lists, and conversations with Alexa for Shopping as information used to personalize the shopping experience. These are Amazon’s own descriptions of its practices, not a complete public inventory of every signal used by every recommendation feature.
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A separate Amazon profiling report, identified as a 2025 annex, describes a broader set of information associated with store profiling. It distinguishes information customers provide from activity and device data observed during use. The report says store profiling uses customer engagement to show content related to shopping interests.
| Information category | Examples Amazon identifies | What the disclosure supports |
|---|---|---|
| Shopping activity | Orders, purchase history, returns | Amazon names these as information associated with shopping profiles or personalization; it does not say each one affects every product suggestion. |
| Browsing and discovery | Search history, product pages viewed | These activities can indicate what a customer is looking for or considering. |
| Customer-provided information | Account details, wishlist items, Lists, product reviews | Some information comes directly from choices and details customers provide. |
| Other Amazon use | Prime Video or Kindle content usage | The profiling report lists content usage among its examples; it does not establish that this data is used for every shopping recommendation. |
| Device interaction | Device configuration, permissions, identifiers | The report identifies device-related information, without specifying its role in a particular recommendation. |
| Alexa for Shopping | Conversations with Alexa for Shopping | Amazon’s 2026 announcement names these conversations as a personalization input. |
The useful distinction is between disclosed categories and a guaranteed rule. Amazon has named kinds of information it may use, but the disclosures do not show that every listed category is connected to every recommendation or used in the same way for all customers.
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Some signals are deliberate expressions of interest: a customer searches for an item, writes a review, or saves a product to a List. Other examples in Amazon’s profiling report are activity observed while using the store, such as viewing product pages, placing orders, or returning items. Amazon’s May 2026 announcement says choices in shopping history are useful because they come directly from customers’ choices. That supports a distinction between information a shopper actively supplies and behavior that may provide context; it does not establish exactly how Amazon interprets either kind.
How activity can turn into a product suggestion
At a basic level, shopping and browsing activity can provide clues about what a customer wants to find. A purchase is one clue; a search, a product-page view, or an item saved to a List can provide a different kind of clue. A recommendation surface can then show products Amazon considers related or potentially relevant.
Amazon’s example is straightforward: a customer who recently bought a comforter might see matching sheets and pillows. The connection is between a past purchase and complementary products. It is an illustration, not a promise that a comforter purchase will always produce those particular suggestions.
Amazon also says its homepage may surface trends, new releases, best sellers, and deals according to interests and preferences. A displayed item therefore need not be a direct match for one recent action; the company describes a personalized shopping experience that can include several kinds of product discovery.
That range matters when trying to understand why an item appeared. A recommendation might be complementary to something bought earlier, connected to a product searched for, or part of a broader discovery area such as new releases or deals. Amazon’s public descriptions identify these kinds of inputs and homepage content, but do not provide a way to trace an individual recommendation back to a specific signal. A shopper therefore cannot reliably infer from one tile which activity triggered it.
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Why one signal does not explain every result
Different activities can point in different directions. A search may reflect a specific need, a page view may show consideration, and a purchase may indicate that the need has already been met—or that related items could be useful. The public descriptions do not say how Amazon resolves these possibilities, how long an activity remains relevant, or how signals are combined.
For that reason, a recommendation should not be treated as proof that Amazon has inferred a definitive personal trait or intention. It is better understood as a product suggestion generated in the context of information Amazon says it uses for personalization.
What Amazon has not disclosed
The public sources cited here do not provide the complete production ranking formula for Amazon’s retail recommendations. They do not reveal the relative weight of purchases, searches, page views, reviews, Lists, returns, or other data; nor do they establish that a particular action will cause a particular product to appear.
AWS publishes documentation for Amazon Personalize, a separate cloud service that businesses can use to build recommendation systems. Its documentation describes concepts such as scoring items using interaction data and metadata, adapting recommendations as new events are recorded in some use cases, and e-commerce patterns including “Recommended for you,” “Frequently bought together,” and “Customers who viewed X also viewed.” Those are examples of a service offered to developers. They do not establish that Amazon’s retail store uses that service or disclose how its own recommendation system works.
The distinction is important because familiar labels such as “Frequently bought together” can describe common recommender-system patterns without telling a shopper which one is active on a particular Amazon page. AWS documentation explains what customers building their own systems can do with Amazon Personalize; it is not a technical description of Amazon’s internal retail ranking. Claims about specific model types, signal scores, or timing would go beyond what these public descriptions establish.
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How to review or edit shopping personalization details
Amazon’s May 2026 announcement says About You lets customers view and edit information used for personalization. It says shoppers can provide preferences, correct details, or remove information they do not want used. The announcement gives these routes:
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- Open the Amazon Shopping app and go to Me.
- Tap your name.
- Choose About You.
- Review the details shown and use the available controls to provide preferences, correct details, or remove information you do not want used for personalization.
On desktop
- On Amazon’s website, open the customer-name menu above Account & Lists.
- Choose About You.
- Review the information and make any changes offered on the page.
Amazon also lists mobile web as an access point, although its announcement’s step-by-step routes specifically describe the app and desktop. Menu labels and locations can change as Amazon updates its interface, so the route may not look identical in every account or marketplace.
When reviewing the page, look at the specific details and preference controls it presents rather than assuming it is a complete activity log. Amazon describes About You as a way to view, edit, or remove details used for personalization; it does not say that this feature removes every record associated with an account or changes all other Amazon settings. If the information shown or the control’s effect is unclear, use the explanation Amazon provides on that page and distinguish a personalization choice from broader privacy or account controls.
About You is described as a place to manage details used for shopping personalization. It should not be assumed to be a universal control for every record Amazon holds or for all data processing. Check the control’s own explanation before treating a change as broader than its stated scope.
Recommendations, ads, and cookies are different controls
Product recommendations are not the same thing as interest-based advertising or browser cookie preferences. Amazon’s 2024 EU Digital Services Act risk assessment discusses product recommendations, advertising disclosures, cookie preferences, and privacy information in separate contexts. A control aimed at one purpose should not be presumed to control the others.
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For EU Store customers, the report describes information about data used for advertising and related controls, and references an option to opt out of product recommendations through Your Account. That is a regional disclosure. The report does not establish that the same option, wording, or route is available in every country or marketplace. Customers should look for the privacy and recommendation controls presented for their own Amazon Store.
In practical terms, a shopper looking to change recommendations should not assume that changing browser cookie preferences will also change product suggestions in an account, or that an advertising choice automatically removes shopping-personalization details. Amazon’s EU report treats these as separate subjects. Outside the EU-specific disclosure, the exact control names and availability should be checked in the customer’s local Store rather than presumed to match the EU route.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to keep in mind when interpreting a recommendation
- It may reflect several kinds of activity. Amazon names shopping, search, review, List, Alexa, browsing, and other data categories across its disclosures, but does not map each suggested item to a specific input.
- A related item is not necessarily an ad. Recommendations and interest-based advertising are discussed as distinct topics in Amazon’s EU disclosure.
- A suggestion is not a guaranteed prediction. The comforter example illustrates one possible connection, not a rule that applies to every shopper.
- Account controls have defined scopes. About You is for details Amazon says are used in shopping personalization; regional ad, cookie, and recommendation settings may be separate.
- Public descriptions are not the full algorithm. No complete ranking formula or signal weighting is disclosed in the sources cited here.
Sources and scope
The named disclosures are Amazon’s May 13, 2026 About You announcement, Amazon’s profiling report Annex 1 (identified as a 2025 annex, with no more precise publication date established here), Amazon’s article about its redesigned homepage, and Amazon’s 2024 EU Digital Services Act Risk Assessment Report. AWS Amazon Personalize documentation is relevant only as an explanation of recommendation-system concepts, not as evidence about Amazon’s retail implementation.
Amazon’s 2026 announcement says that nearly every shopping experience across Amazon is personalized to help “hundreds of millions of customers” find products. That is Amazon’s rounded characterization, not an independently verified count or a precise statistic.
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What shopping and browsing information does Amazon say it uses for recommendations?
Amazon’s May 13, 2026 About You announcement names purchase history, searches, product reviews, Lists, and conversations with Alexa for Shopping. Its profiling report also lists orders, viewed pages, search and returns history, content usage, account details, and device interaction data. These are disclosed examples; Amazon does not say every category affects every recommendation.
Can I find out why Amazon showed me a particular product?
Amazon’s public descriptions do not provide a signal-by-signal explanation for each recommendation. A suggestion may be related to shopping or browsing activity, or appear as part of homepage discovery such as trends, new releases, best sellers, or deals. The comforter-to-sheets-and-pillows example is illustrative, not a guaranteed rule.
How do I change information used for shopping personalization?
Amazon says About You is available in the Shopping app, mobile web, and desktop. In the app, its May 2026 instructions say to go to Me, tap your name, and select About You. On desktop, open the customer-name menu above Account & Lists and choose About You. Amazon says customers can provide preferences, correct details, or remove information they do not want used; menu routes may change.
Does turning off interest-based ads also turn off product recommendations?
Not necessarily. Amazon’s 2024 EU Digital Services Act risk assessment discusses interest-based advertising, cookie preferences, and product recommendations separately, and references an EU Store option to opt out of product recommendations through Your Account. The report does not establish identical controls or routes for every marketplace.
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Is Amazon Personalize the system that powers Amazon’s own recommendations?
AWS describes Amazon Personalize as a cloud service businesses can use to build recommendation systems. Its documentation is useful for understanding recommender concepts, but does not establish that Amazon’s retail store uses that service or reveal the retail system’s formula.
The Bottom Line
Amazon says purchases, searches, page views, reviews, Lists, and Alexa for Shopping conversations can inform personalized shopping experiences, but it does not publish the full recommendation formula or explain each individual suggestion. Use About You to review the personalization details Amazon makes available, and treat ad, cookie, and recommendation controls as potentially separate—especially across different marketplaces.
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