2026-06-30 · 8 min read
Amazon A9 Algorithm Explained: How Search Ranking Works in 2026
How Amazon's A9 (and A10) search algorithm ranks products in 2026: relevance signals, conversion signals, sales velocity, and what sellers can actually influence.
What Is the A9 Algorithm
Amazon's A9 algorithm (sometimes called A10 in seller communities, though Amazon does not officially use this term for a distinct version) is the system that determines which products appear in search results and in what order. Unlike Google, which ranks web pages, A9 ranks products for sale. Its primary goal is to show searchers the products most likely to result in a purchase -- because Amazon makes money when purchases happen.
The Two Core Components: Relevance and Performance
A9 evaluates every product against two broad signal categories. Relevance signals: does this product match what the searcher typed? Performance signals: when shown to previous searchers, how often did they buy? A product with high relevance but low conversion rates loses ground to a product with slightly lower relevance but a much higher purchase rate. This is why a well-optimized listing that doesn't convert is ultimately self-defeating.
Relevance Signals
Title: the most heavily weighted text field. Keywords in the first 60-80 characters matter most. Bullets: second in weight after title. Backend keywords (search terms): indexed but lower weight than visible fields. Brand name: indexed separately. Category and browse nodes: influence which searches your product is eligible for. Price competitiveness: a product priced far above competitors for the same search term gets depressed relevance over time. Description and A+ content: indexed, but low weight for ranking.
Performance Signals
Click-through rate (CTR): does your listing get clicked when shown? Influenced by main image quality, price, star rating, and title clarity. Conversion rate (CVR): when people click your listing, do they buy? Influenced by images, bullets, pricing, reviews, and listing completeness. Sales velocity: absolute sales volume over time. Higher sales = higher rank. Amazon rewards momentum -- a product selling well today tends to continue ranking because its sales history confirms buyer intent. Return rate: high return rates are a negative signal, associated with misrepresented products. Review rating and count: high ratings (4+ stars) with substantial review volume positively influence ranking.
What Sellers Can Actually Influence
Direct: keyword optimization in title and bullets, main image quality, pricing, review solicitation (via Amazon's Request a Review button). Indirect: conversion rate through listing quality, sales velocity through external traffic (social media, email lists, Amazon advertising to build initial momentum), return rate through accurate product descriptions. Cannot influence: Amazon's direct manipulation of rankings is against policy. Fake reviews are against policy and increasingly detected.
The Honeymoon Period
New listings sometimes temporarily receive boosted visibility to gather initial sales data -- commonly called the 'honeymoon period'. This effect is inconsistent and not guaranteed, but many sellers report higher initial rankings for new listings before the algorithm establishes a sales history baseline. Running PPC advertising during this period is a common strategy to capture early sales and accelerate the algorithm's data collection.