How does the Amazon algorithm work?
Amazon's search algorithm ranks product listings by evaluating two main groups of signals: relevance, which determines whether your listing matches what a shopper is searching for, and performance, which reflects how well your listing converts those shoppers into buyers. Listings that score strongly on both consistently rank at the top of results. Amazon's search algorithm determines which products appear in search results and in what order. Every time a shopper enters a search query, the algorithm evaluates all eligible product listings and ranks them based on how likely each one is to result in a sale. The listing the algorithm predicts will convert best ranks highest. The algorithm works in two stages. First, it filters for relevance: only listings that are indexed for the search query are considered. Second, among the relevant listings, it ranks by performance: how well similar shoppers have responded to each listing in the past. Both stages must be addressed for a listing to rank well. Amazon indexes listings based on the keywords present in specific listing fields. The product title carries the highest relevance weight. Keywords in the title influence which searches the listing is considered for more than any other field. Bullet points and product description contribute next, followed by backend search terms, subject matter fields and other attribute fields. For a listing to appear in search results for a keyword, that keyword or a close variant must be present in at least one indexed field. If a shopper searches for 'insulated lunch bag for adults' and none of those words appear in your listing, your product will not be shown, regardless of how well it might convert. Backend search terms are the hidden keyword field in Seller Central, limited to 250 bytes. They allow you to include relevant search terms that would look unnatural or repetitive in your visible listing copy. Terms in the backend field count for indexation but are not visible to shoppers. Among all the listings relevant to a search, Amazon ranks by predicted purchase probability. The strongest performance signal is sales velocity: how many units have been sold recently for related searches. Listings that sell consistently rank higher than listings with similar keyword coverage but fewer sales. Conversion rate is closely tied to sales velocity. Amazon tracks what percentage of shoppers who view each listing go on to purchase. A high conversion rate signals that the listing effectively convinces shoppers, which Amazon rewards with higher ranking. Click-through rate, the percentage of searchers who click your listing from results, and review score, including the star rating and total review count, are additional performance signals. Both affect how often shoppers interact positively with your listing, which feeds back into the ranking model. Amazon's algorithm does not consider factors outside the Amazon ecosystem. Website domain authority, social media following, press coverage, backlinks and external brand reputation play no role in Amazon rankings. A brand with no website at all can outrank a global company if its Amazon listing is better optimised and converts more effectively. Amazon also does not use keyword density in the way early Google SEO did. Repeating a keyword multiple times in your title or bullets does not improve ranking. Amazon reads the presence of a keyword, not the frequency. Including the same keyword in your title and again in your backend search terms does not improve indexation for that term.
Learn how Amazon's search algorithm ranks listings, which signals matter most and how to optimise your keywords and sales performance to improve rank.