Dive into the evolving landscape of Amazon's A9 algorithm, exploring algorithm improvements from 2022 to 2023. Discover how Bayesian updates and advancements in machine learning are reshaping ranking and visibility. The discussion debunks the 'honeymoon period' myth, emphasizing the significance of personalized product titles and accurate data. Gain insights into launching products effectively and leveraging Amazon's AI recommendations to enhance conversions. Understand the pivotal role of keyword prioritization in improving search relevance and shopper experience.
The podcast emphasizes the significance of understanding Amazon's evolving algorithms, specifically the shift towards personalized ranking mechanisms influenced by real user data.
Debunking the myth of a honeymoon period for new products, the discussion covers the importance of optimized launch strategies amid constant algorithm updates.
Deep dives
Collaboration on Comprehensive Articles
The collaboration between the speakers led to an extensive series of articles that delves deep into topics relevant to seller strategies. Their first significant piece about the 'Cosmo' algorithm was comprehensive, spanning several thousand words and exploring various aspects of its functionality. This was followed by further articles in which they analyzed multiple patents and scientific papers, which added layers of complexity and understanding to their work. The discussion reflects a commitment to creating a significant public resource for comprehending the evolution of algorithms affecting sellers.
Understanding Algorithmic Changes
There is a focus on highlighting key differences between past and current algorithms, particularly the evolution observed in November 2023 compared to 2022. The speakers address what they describe as a 'honeymoon period' where new products are expected to perform better, emphasizing that this boost is not guaranteed due to significant changes in the way Amazon calculates product rankings. They discuss the implications of Bayesian updates and machine-learning models that help personalize the shopping experience, suggesting that the algorithm now relies heavily on real user data for assessing product relevancy and conversion likelihood. The conversation stresses the importance of effective launching strategies and traffic generation to achieve and maintain high visibility.
Challenges and Strategies in Selling
A detailed examination of the challenges sellers face when navigating Amazon's complex ecosystem is presented, particularly with the evolving nature of product attributes and advertising strategies. There is an emphasis on the need for sellers to optimize their listings and adapt to Amazon's dynamic changes, such as personalized titles and the way keywords are presented in search results. The discussion also highlights the significance of understanding customer behavior to enhance product conversions, indicating that a well-thought-out strategy can lead to better outcomes for sellers. This includes the necessity for critical thinking and blending scientific insights with practical observations to improve performance and drive sales.
Bayesain Updates - Changing the Game of Ranking In this episode of Seller Sessions, Danny and Oana unveil their latest collaborative article, which delves into Amazon's patents and algorithms, particularly focusing on the evolution from 2022 to 2023. This monumental piece—over 10,000 words—aims to be the most extensive public resource on Amazon's A9 algorithm, tracking its history and impact. Article Origins and Team Effort -Danny and Oana teamed up for several papers, each expanding in scope. Their latest collaboration incorporates insights from two patents and 15-16 additional scientific papers. -The goal: Analyze the algorithm changes between 2022 and 2023, highlighting key differences and their implications for sellers. Key Themes Covered -BERT, Cosmo, and External Traffic: Deep dive into these technologies and how they impact ranking, visibility, and traffic management. -Sales Velocity and Cold Start Mechanisms: The duo explores how Amazon’s cold start problem has evolved, driven by Bayesian updates and machine learning. -Honeymoon Period Myth: A thorough debunking of the concept, explaining why it no longer holds true after algorithm changes in 2022. Data-Driven Approach This project digs into how Amazon now processes data, with updates to ranking and product visibility happening every 2-24 hours. The emphasis is on personalization, driven by Amazon’s focus on conversion likelihood, making an optimized launch strategy critical. Amazon’s Shift Towards Personalization -Amazon’s increasing focus on tailored customer experiences, from personalized search results to dynamically adjusted product titles. -Concerns about how machine learning models, like Cosmo and Rufus, will continue to evolve and potentially override manual optimizations sellers make. Tune in to gain the edge on launching your products and mastering Amazon's constantly evolving system. READ THE ARTICLE HERE
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode