Overview

Amazon’s A9 search algorithm decides which products appear at the top of shopper queries, directly affecting a seller’s visibility and sales. The algorithm evaluates relevance, performance, pricing, and customer experience to rank listings. Sellers who understand and act on these signals can capture more organic traffic and grow revenue in the highly competitive U.S. marketplace.

Key Points

• Relevance signals — Keywords placed in the title, bullet points, description, and backend fields tell A9 whether a product matches a shopper’s search; a listing titled “Organic Cotton Baby Blanket – 30 × 40 in” will rank higher for that exact phrase.
• Performance metrics — Sales velocity, conversion rate, and recent purchase history act as strong demand indicators; a product moving 35 units per day with a 27 % conversion rate outranks a similar item selling 8 units daily.
• Customer experience factors — High‑resolution images, detailed bullet points, and a low return rate improve perceived value, giving the listing a ranking edge over sparse competitors.
• Pricing and promotions — Competitive pricing combined with Amazon coupons or lightning deals boosts click‑through and conversion, sending positive signals to the algorithm.
• Review profile — A larger pool of verified‑purchase reviews and an average rating of 4.5 + stars increase trust, leading to better placement in search results.

How Amazon Product Ranking Works

1. Keyword Matching — A9 parses the title, bullet points, description, and backend keywords for terms that match the shopper’s query.

   • Example: A buyer searches “stainless steel water bottle 32 oz.” A product titled “32 oz Stainless Steel Insulated Water Bottle” receives a higher relevance score than a listing that only mentions “water bottle” in the description.

2. Sales Performance Evaluation — Recent sales data is weighted heavily; items with strong, consistent purchase activity are favored.