Amazon A9 algorithm

The Amazon A9 algorithm is a critical component in Amazon's e-commerce operations, driving the search and visibility of products. This complex system sifts through numerous products, presenting the most relevant options based on factors like keyword relevance, conversion rates, and sales history, aimed at improving customer experience and boosting sales.

The Development of A9

The A9 algorithm's origins trace back to the early 2000s, marking a shift towards a technology-centric approach in Amazon's search and recommendation systems. 

Over time, A9 has transformed from a basic search tool into a sophisticated system incorporating machine learning and artificial intelligence, a testament to Amazon's dedication to refining the user experience and maintaining a competitive edge.

A9's Functionality

A9 operates by aligning customer searches with suitable products, analyzing various factors from search terms to customer behavior nuances.

This process, blending technical precision with a nuanced approach, seeks a balance between relevance and profitability, adapting to changing consumer trends and technologies.

A9 is also responsible of the Sponsored Advertising placements you can see across Amazon’s site: Sponsored Products, Brands and Display.

Keyword Relevance in A9

Keywords play a pivotal role in A9, guiding the search engine towards relevant products. Effective keyword optimization is essential for sellers, requiring strategic integration of keywords in product titles, descriptions, and backend search terms, while avoiding excessive keyword use that could harm product ranking.

The Role of Sales Velocity

Sales velocity is a vital indicator of product appeal in Amazon's marketplace. A9 values rapid sales as a sign of consumer interest and product relevance. 

Sellers can enhance their product's visibility by adopting strategies to increase sales velocity, which can lead to improved search rankings and higher sales.

Optimizing Conversion Rates

Conversion rate is a crucial A9 metric, reflecting the percentage of visitors who purchase a product. Sellers can enhance their conversion rates and thereby improve their product's search ranking through strategies like optimizing product visuals and encouraging positive reviews.

Components of Amazon SEO

Effective Amazon SEO involves several elements, including keyword-rich yet clear titles, concise bullet points highlighting key features, detailed product descriptions with secondary keywords, and high-quality images for better engagement and conversion.

Adapting to A9's Dynamics

For sellers, adapting to A9's evolving nature is key to success in Amazon's e-commerce environment. Focusing on aspects like keyword relevance and conversion optimization, and staying responsive to Amazon's algorithm changes, are critical for maintaining product visibility and sales momentum.

Remember A9 algorithm evolves, but there’s no such thing as an A10 algorithm. All the patents are filed for A9, not A10.

A9 Patents and Their Impact

Speaking about patents… Amazon's A9 algorithm is not only a product of technological evolution but also a subject of various patents that shape its functionalities and capabilities. These patents demonstrate the intricate mechanisms behind A9 and Amazon's broader search ecosystem.

To me this are the 4 main patents you can use and apply to your listings and Amazon SEO to gain visibility on the platform. 

Let’s check’em out:

1. Indexing and Presenting Content Using Latent Interests

This patent focuses on establishing a relationship between a user's interests and displayed products by monitoring content that generates user interest outside of Amazon. Registered in July 2021, it enhances the relevance of responses in the Marketplace ecosystem.

2. Sales Rank Increases as a Measure of Interest

Filed in 2016, this patent interprets increases in sales as a sign of product relevance, influencing the display of products based on their Best Seller Rank (BSR). It reviews sales rankings hourly to arrange product positioning.

3. Machine Learning-Based Database Query Retrieval

Registered on March 8, 2022, this patent uses historical information of similar products to rank new products with no reference, as part of the "Cold Start Service" or "Honeymoon Period." It aims to provide new products with a fair initial ranking.

4. Providing Location-Based Search Information

Dating back to June 13, 2017, this patent allows A9 to produce different rankings based on the geographical location of the user, leading to different classifications for the same product in various locations.

These patents are just a few examples of how Amazon's A9 algorithm leverages technological advancements and legal protections to stay at the forefront of e-commerce search and recommendation systems.

What’s coming next? A9 is starting to show Augmented Reality results, video results and 360º results so it will be more visual in the future.

If you want to learn more about Amazon A9 algorithm, you can check my A to Z guide.