What is Amazon A9?
Amazon A9 is the name used for Amazon's original product search algorithm, developed by A9.com, a subsidiary Amazon created specifically to build its search and advertising technology. A9 determined how product listings were ranked in Amazon search results for many years and established the core framework of relevance plus performance that still underlies Amazon's ranking model today. Amazon A9 refers to the product search algorithm Amazon used to rank listings in its marketplace. The name comes from A9.com, the Amazon subsidiary established to develop search and advertising technology for Amazon's platform. A9.com operated as a separate entity for many years before Amazon wound it down in 2023. The A9 algorithm evaluated two primary categories of inputs: relevance, drawn from the keywords present in listing fields like the title, bullets and backend search terms, and performance, measured by sales velocity, conversion rate and click-through rate. Listings that matched a search query and had strong conversion history ranked highest. Under A9, keyword placement in the product title was the most important relevance signal. A listing needed to include the shopper's search term in an indexed field to be eligible for that search. The title, bullet points, backend search terms and product description all contributed to which searches a listing could appear for. Performance signals under A9 were heavily weighted towards sales history. A listing that had sold consistently well for a keyword was prioritised in results over a listing with better copy but fewer sales. This created a compounding advantage for established bestsellers, which maintained ranking partly through their sales history alone. Paid advertising had a significant indirect influence under A9. Running Sponsored Products ads on a keyword generated ad-driven sales, which fed into the sales velocity signal Amazon used for organic ranking. Sellers who invested heavily in PPC could accelerate organic ranking for target keywords by using ad spend to build sales history. A9's heavy reliance on historical sales data created a structural advantage for established listings and a barrier for new entrants. A new product with a well-optimised listing but no sales history ranked behind older products with weaker optimisation simply because the older products had accumulated more sales signals. The model's indirect link between PPC spend and organic ranking also rewarded sellers who could afford to run large ad campaigns, as ad-driven sales translated into organic ranking improvements. This made the relationship between advertising spend and organic visibility more direct than Amazon publicly acknowledged. These characteristics shaped how the algorithm was later updated, with the changes sellers commonly call A10 aiming to address some of A9's dependence on paid sales as a proxy for product quality. The seller community began using the term A10 to describe changes to Amazon's ranking model that appeared to shift emphasis away from ad-driven sales velocity and towards a broader set of organic signals. These included organic sales, seller authority, click-through rate from organic results and the relevance of external traffic sources. Amazon has not officially confirmed the name A10 or published a detailed changelog of ranking algorithm updates. The A9 and A10 framework is a seller community model for understanding observed ranking behaviour, not an official Amazon taxonomy. The foundational principles of the A9 model remain active in the current algorithm. Keyword relevance and conversion performance are still the dominant ranking inputs. The evolution has been a shift in how Amazon weights different sources of sales and traffic data, not a replacement of the core framework.
Amazon A9 is the original name for Amazon's product search algorithm. Learn how A9 ranks listings and how the algorithm has evolved with the A10 update.