A9 vs ‘A10’ for KDP: What Changed, What Didn’t, and What Amazon Actually Says
Amazon never published an A9-to-A10 KDP formula. Here’s what really changed, what still matters, and which ranking claims remain guesswork.
Amazon has not published an official KDP A9-to-A10 transition
KDP lists four examples of influences on search results
KDP still gives authors up to seven keyword fields
What actually changed when KDP marketers started talking about “A10”? Less than the tidy A9-versus-A10 charts would have you believe. A9 has a real history inside Amazon, but Amazon has never published a KDP document that says one ranking formula was officially replaced by another on a particular date, complete with a new set of factor weights.
That matters because a lot of otherwise sensible publishing advice gets presented as though Amazon has confirmed the mechanism behind it. External traffic can bring buyers. Reviews can influence shoppers. Better conversion can produce more sales. None of those statements requires a secret algorithm theory. The problem begins when someone turns them into claims such as “external traffic now carries 30% of the A10 score.”
This guide separates the history from the mythology. It looks at what A9 actually was, why “A10” became popular shorthand, what Amazon currently tells KDP authors about search and discoverability, and which tactics still make sense without pretending we know a formula Amazon has never published.
The Quick Answer
Amazon search has changed substantially over the years. The shopping experience is more personalized, more conversational, and spread across more surfaces than the older keyword-and-results-page model suggests.
What authors do not have is an official KDP document defining a historical A9 ranking formula and then announcing a replacement A10 formula with new weights.
Amazon search technology has evolved
Amazon has spent decades developing search, recommendations, personalization, advertising, and AI-assisted shopping.
A public KDP A9-to-A10 formula swap
Amazon has not published a KDP cutover date or a table showing old and new organic-search weights.
So the useful comparison is not “old percentage versus new percentage.” It is older optimization habits versus Amazon’s current published guidance and current shopping environment.
A9 Was Real, but Not in the Way Most KDP Charts Suggest
A9 is not an invented name. Amazon launched A9.com in 2004 as a separately operated Amazon subsidiary focused on search technology. Amazon’s own historical material describes A9.com as researching and building search technologies, including technologies connected with product discovery.
What that history does not give KDP authors is a public “A9 ranking formula” with official weights for keyword relevance, conversion, sales velocity, reviews, click-through rate, or any of the other percentages that appear in SEO graphics.
That distinction is easy to lose because “A9” gradually became publishing and ecommerce shorthand for Amazon search itself. Once that happened, it became tempting to describe every later change as a numbered successor.
So What Is “A10”?
For KDP authors, “A10” is best treated as non-official industry shorthand for a newer view of Amazon search, not as the name of a documented Amazon ranking system.
The label became popular because the old search-optimization story felt too narrow. Amazon increasingly personalized shopping, used more behavioral context, expanded recommendation surfaces, improved advertising tools, and later introduced conversational AI shopping. Marketers needed language for the change, and “A10” became a convenient label.
The problem is that the label often arrived with precise claims Amazon never published: fixed percentages for seller authority, review velocity, external traffic, click-through rate, conversion, or other supposed ranking factors.
Reasonable: Amazon search and shopping have become more contextual and personalized over time.
Unsupported: Amazon now gives external traffic exactly three times the organic-search weight it received under A9.
If a claim includes a precise weight, multiplier, score, or cutover date, ask for the Amazon source before treating it as fact.
What Amazon Actually Says About KDP Search
KDP’s current Search Results guidance says search results are dynamic and can be influenced by factors including, but not limited to:
Past sales history
Amazon explicitly includes previous sales activity among the factors that can influence search results.
Availability
Whether an item is available is another factor Amazon lists in its search guidance.
Time listed
KDP says the length of time an item has been listed can influence search results.
Popularity
Popularity is also explicitly included in Amazon’s list of possible influences.
KDP separately says that search can be determined by information not always visible on the results page, including keywords, book details, and the text of the book itself. Its Read Sample guidance goes further and says Amazon uses actual matching words inside books to return relevant book results.
Authors also still have concrete discovery controls. KDP currently allows up to seven relevant keywords or short phrases and up to three category selections. Amazon says categories and keywords help determine where the book is shelved in its digital store.
Best Sellers Rank is separate from organic search position. KDP says BSR is based on customer activity relative to other books, using both recent and historical activity with recent activity weighted more heavily. Its keyword guidance nevertheless mentions sales history and BSR alongside relevant keywords when discussing discoverability, which is another reason to keep commercial performance and search visibility connected without pretending they are the same metric.
What Really Changed for Authors?
The absence of an official A10 formula does not mean nothing changed. Quite a lot did. The useful changes are simply broader than a ranking-factor pie chart.
Shopping became more personalized
Amazon has used personalization for years, and in 2026 it made that direction even more explicit. Its About You feature lets shoppers view and edit information that shapes recommendations, including signals connected with purchase history, searches, reviews, Lists, and conversations with Alexa for Shopping.
That makes the old mental model of one universal ranking for every shopper increasingly incomplete. A book still needs visibility, but the path by which an individual shopper encounters it can be more personalized than a traditional keyword-results page suggests.
Shopping became more conversational
On May 13, 2026, Amazon renamed Rufus as part of Alexa for Shopping, initially for U.S. customers. Amazon says the shopping assistant can combine product catalog information with reviews, community Q&As, information from across the web, personal preferences, shopping history, and conversational context.
That is a genuine change in product discovery. A reader can ask a natural-language question such as “What is a good puzzle book for an older adult who likes large print but finds ordinary word searches too easy?” rather than typing a short keyword phrase.
The practical implication is not “optimize for the Alexa factor.” Amazon has not published one. The implication is that clear product information, accurate positioning, useful reviews, and a book that genuinely fits a specific reader remain valuable across more kinds of discovery.
Amazon is exposing more engagement context
KDP is also testing Book Trends data on some search and detail pages. The feature reflects an aggregate of recent customer engagement, including purchases, Kindle reading, and Audible listening. Amazon explicitly says it is not a sales report.
That is interesting evidence of how Amazon presents customer activity, but it should not be repackaged as a newly documented organic-search factor.
External marketing became easier to measure
Amazon Attribution gives eligible KDP authors a free way to measure how non-Amazon marketing contributes to Amazon activity. It can be used with channels such as search, social, display, video, and email in supported marketplaces.
That is much more useful than assuming every off-Amazon visitor receives a hidden ranking bonus. You can measure whether a campaign actually produces useful outcomes.
What Did Not Change?
The foundations of good KDP discovery are less dramatic than algorithm folklore suggests.
Reader relevance
The book needs to be a credible answer to the search, category, recommendation, or shopping question that brought the reader to it.
Accurate metadata
Keywords, categories, title information, and the description should describe the real book rather than manipulate the store.
Commercial activity
Amazon explicitly names sales history in search guidance and customer activity in its sales-ranking guidance.
A listing that earns the sale
Visibility has little commercial value if the cover, positioning, description, sample, reviews, or price fail to convince the right shopper.
Relevant search language still matters
KDP still tells authors to choose keywords that accurately portray the book and reflect the language customers use when searching. That does not mean repeating the same exact phrase mechanically in the title, subtitle, description, keyword boxes, and manuscript.
Use the keyword fields for relevant search language. Use reader-facing copy to explain and sell the book naturally. Our semantic search and KDP listings guide looks at that distinction in more detail.
Relevant categories still matter
KDP currently lets authors choose up to three categories and specifically tells them to pick categories that accurately describe the book. Amazon warns that irrelevant categories create a poor shopping experience and says it does not tolerate category choices intended to mislead or manipulate customers.
That makes the old “find the tiniest category and grab a badge” mindset much harder to defend as a publishing strategy.
Which Ranking Claims Should You Treat Carefully?
| Common claim | What the evidence supports |
|---|---|
| Amazon officially replaced A9 with A10 for KDP | Amazon has not published a KDP cutover document defining an A9 formula and its A10 replacement. |
| External traffic has a special organic-search multiplier | External marketing can create sales and other customer activity, but KDP does not publish a special multiplier for traffic simply because it came from outside Amazon. |
| Seller authority has a fixed ranking weight | Amazon enforces account and policy standards, but KDP does not publish a seller-authority score for organic book search. |
| Review velocity has a fixed organic-search weight | Reviews can influence shoppers and Amazon says Alexa for Shopping can use review information, but no KDP organic-search weighting is published. |
| Conversion rate carries a published organic-search percentage | Conversion matters commercially because clicks that do not buy produce no sales. Amazon does not publish a KDP organic-search percentage for conversion rate. |
| Keyword density has a documented penalty threshold | KDP prohibits misleading metadata and recommends relevant keywords. It does not publish a keyword-density threshold for book copy. |
| Alexa for Shopping gives books an AI optimization score | Amazon describes the information its shopping assistant can use, but it does not publish a KDP-specific Alexa score or guaranteed inclusion formula. |
How to Build a Strategy That Survives Search Changes
The safest response to an opaque search system is not to ignore search. It is to separate what you can observe from what you can only speculate about.
Start with the reader journey:
Is there a real market?
Check whether enough readers appear to want this kind of book before optimizing the listing.
Can the right shopper find it?
Look at relevant searches, categories, competitor visibility, and existing keyword positions.
Does the result earn attention?
Cover, title, price, positioning, and review evidence all shape the decision to open the detail page.
Does the page close the sale?
Description, sample, reviews, price, A+ Content where relevant, and audience fit all influence the buying decision.
Does the book deliver?
Long-term sales, reviews, repeat buying, and read-through depend on the actual product fulfilling its promise.
Then keep a before-and-after record for meaningful changes. Note the date, what you changed, current keyword positions, sales-rank direction, price, advertising conditions, and any major promotion. Where practical, change one meaningful variable at a time rather than rewriting the entire listing and then guessing which part caused the movement.
For the broader current-search framework, see our guide to what KDP authors can actually verify about Amazon search in 2026. This article is deliberately narrower: its job is to separate the A9/A10 comparison from the facts authors can use today.
Frequently Asked Questions
Was A9 a real Amazon search system?
A9 was a real Amazon search technology organization and brand. Amazon launched A9.com as a search-focused subsidiary in 2004. That does not mean Amazon published a KDP organic-ranking formula called A9 with factor weights authors could calculate.
Does Amazon officially call its newer KDP search algorithm A10?
Amazon does not currently publish KDP documentation defining an “A10” ranking formula. The term is better treated as non-official industry shorthand for changes in Amazon search and shopping.
Was A9 officially replaced by A10 on a specific date?
Amazon has not published a KDP cutover document giving authors an official replacement date, old formula, new formula, and changed factor weights.
Should I stop using exact search phrases?
No. Relevant reader language remains useful in keyword research and metadata. The mistake is assuming that repeating one phrase mechanically throughout every field earns a documented ranking benefit.
Does external traffic improve Amazon organic ranking?
External marketing can produce real sales and customer activity, which are commercially useful. Amazon does not publish a special KDP organic-search multiplier awarded simply because a shopper arrived from outside Amazon.
Are reviews an official organic-search factor?
Amazon does not publish a fixed KDP organic-search weighting for reviews. Reviews still matter to shoppers, and Amazon says Alexa for Shopping can draw on customer-review information.
What KDP search facts are documented?
KDP names examples including past sales history, availability, time listed, and popularity. It also says search can use keywords, book details, and text inside the book. Authors can currently select up to seven keywords or short phrases and up to three categories.
What should replace A9-versus-A10 checklists?
Use a diagnostic workflow based on demand, visibility, click appeal, conversion, and reader response. Change the weakest stage first and measure what happens rather than optimizing an imaginary score.
The Better Comparison
The most useful distinction is not old algorithm versus new algorithm. It is unsupported certainty versus evidence-led publishing.
Keep the parts of classic KDP SEO that still help the right reader find the right book: relevant search language, accurate categories, coherent metadata, good positioning, and a product readers actually want.
Add the newer realities Amazon has genuinely documented: more personalized shopping, conversational product discovery, broader engagement signals in the customer experience, and better measurement of off-Amazon marketing.
Then drop the imaginary percentages. You do not need to know whether someone calls the system A9, A10, or something else to make a better publishing decision.
