What Will the Sellers Do When Deep Dive into Amazon’s COSMO Algorithm-Amazon Freight Forwarder

Amazon’s COSMO algorithm is a novel artificial intelligence algorithm developed based on Large Language Models (LLMs), aimed at analyzing user behavior data to uncover potential shopping intents and construct a user-centric knowledge graph. Below is an in-depth exploration of the COSMO algorithm:

Core Functions of the COSMO Algorithm

1. Uncovering User Intents:
   1. COSMO precisely pushes products by combining big data such as user information and shopping history to match user purchase intentions.
   2. For example, when a pregnant woman searches for “slippers,” the COSMO algorithm not only identifies that she needs “maternity shoes” but also further analyzes her need for “non-slip” features, thereby recommending maternity shoes with non-slip properties.
2. Multi-Round Navigation:
   1. COSMO re-mines consumers’ potential needs through intelligent recommendations.
   2. For instance, a search for “camping” may lead to the selection of “inflatable mattresses” and then narrow down to “camping inflatable mattresses,” offering various types to meet different needs.
3. Conversational Shopping:
   1. COSMO enhances its analytical capabilities by integrating rich data obtained from Rufus, Amazon’s new shopping dialog assistant.
   2. Rufus assists customers in searching, discovering, researching, and purchasing products through a “question-and-answer” approach, guiding consumers more precisely to the desired items.
4. Improving Recommendation Accuracy:
   1. COSMO optimizes the recommendation algorithm through intelligent algorithms, enhancing the accuracy of common-sense recommendations for complementary and substitute products.
   2. It leverages historical conversion rate data, combined with users’ personalized characteristics and needs, to further improve recommendation effectiveness.

Impact of the COSMO Algorithm on Sellers

1. Changes in Keyword Ranking Strategies:
   1. Under the COSMO algorithm, the ranking of search results no longer solely depends on exact keyword matching but more on user shopping intents and context.
   2. Sellers need to focus on analyzing user profiles and shopper behavior, studying reviews, return data, and user actions to provide richer context for the COSMO algorithm.
2. Product Differentiation and Personalization:
   1. The COSMO algorithm emphasizes product diversity and user demand personalization, allowing orders to be obtained even if keyword rankings are not high.
   2. Sellers should create differentiated and unique products to avoid homogenization and meet users’ personalized needs.
3. Optimizing Product Information:
   1. Sellers need to optimize product listings and detail pages, including keywords, images, descriptions, etc., to improve AI recognition.
   2. Providing detailed product information, such as usage methods, applicable scenarios, compatibility with other products, etc., helps COSMO better understand and classify products.
4. Leveraging Rufus to Increase Traffic:
   1. Sellers should pay attention to the matching of products with specific scenarios or festival keywords, optimizing relevant product keywords and descriptions to ensure products can be recommended by Rufus.
   2. Utilize Rufus’s dialog function to guide consumers in product comparison and selection, increasing product exposure and conversion rates.

Future Trends of the COSMO Algorithm

1. Deepening Personalized Recommendations:
   1. As the COSMO algorithm continues to optimize and upgrade, personalized recommendations will become more precise and considerate.
   2. Sellers need to continuously monitor changes in user needs and analyze shopping behavior to adjust product strategies and optimize marketing plans.
2. Synergy with the A9 Algorithm:
   1. The COSMO algorithm is not a replacement for the A9 algorithm but complements it.
   2. The A9 algorithm still plays a crucial role in processing keyword relevance and product quality rankings, while the COSMO algorithm focuses on enhancing the personalization and accuracy of search results. Together, they more comprehensively meet users’ shopping needs.
3. Impact on the E-commerce Ecosystem:
   1. The introduction of the COSMO algorithm marks a new era in Amazon’s e-commerce ecosystem.
   2. It requires sellers to pay more attention to product differentiation and personalization to meet user demands, while also promoting innovation and development in the e-commerce platform.