COSMO, this new term has attracted widespread attention in the e-commerce field. How is it different from the A9 algorithm that has long dominated Amazon's search and ad rankings? What fundamental changes will the application of this new algorithm bring to operations? How should sellers adapt to this change? Will the A9 algorithm gradually withdraw? Historical stage? These issues have undoubtedly become the focus that sellers are eager to understand. Let’s first review what Amazon’s A9 algorithm is:

 

 

 

The Amazon A9 algorithm is a complex system used to determine product ranking and display. It makes personalized recommendations based on the user's behavior and preferences, taking into account a variety of factors, such as sales performance, product relevance, user reviews, etc., to help users find products that meet their needs more easily. Sellers can improve the performance of their products in the A9 algorithm by providing high-quality products, optimizing keywords, accumulating positive reviews, and maintaining sufficient inventory, thereby obtaining better rankings and placements, and increasing product exposure and sales.
 

 

 

Amazon believes that although the existing e-commerce knowledge graph integrates a large number of concepts or product attributes, it cannot discover the user's intention, and there is a gap between people's thinking, behavior and the way they interact with the world around them.

 

COSMO has changed all this. It is a scalable system that can mine user-centered common sense knowledge from massive behaviors and build an industry-scale knowledge graph to empower diverse online services. Amazon has expanded COSMO to 18 major Amazon categories, including search relevancy, session-based recommendations, and search navigation.

 

COSMO can more accurately match consumers' purchasing intentions. Once COSMO is used on a large scale, Amazon's search algorithm logic and traffic distribution principles will undergo earth-shaking changes.
 

 

 

In fact, COSMO has been rigorously tested by Amazon before it was officially released to the public, and has achieved impressive results. Previously, Amazon conducted several months of A/B testing for some users on the US site. Test results show that when COSMO is integrated into the online search navigation system, product sales in specific markets significantly increase by 0.7%. This increase means a huge increase in annual revenue. Even more noteworthy, navigation engagement rates also increased by 8%, showing a significant increase in customer engagement and satisfaction.

 

Based on the success of initial testing, Amazon expects to generate billions of dollars in revenue growth by expanding COSMO’s adaptability to cover all navigation paths. More importantly, for Amazon, COSMO has huge potential in various functions and applications, opening up new ways to improve user experience and business growth.

 

According to relevant information, the full name of COSMO is "Amazon Large-scale E-Commerce Knowledge Generation and Service System". This system utilizes the power of large language models (LLM) to mine common sense knowledge related to user intentions from a large number of user behaviors and build a huge knowledge graph. This knowledge graph can improve the relevance of search and make search results closer to the actual needs of users.
 

 

 

"Common sense" is like eating when you are hungry and not wearing shoes when sleeping. Alibaba has created such a common sense system under the online shopping model. For example, if a user searches for "senior mobile phone", according to common sense, the elderly have poor eyesight and the mobile phone should have "large screen" features, then the user will be presented with a mobile phone with relevant features.

 

The COSMO algorithm is somewhat similar to the "thousands of people, thousands of faces" personalized recommendations of domestic e-commerce, that is, the system determines that consumers may want and be more suitable. To put it simply, the COSMO algorithm uses AI to perform "artificial thinking" on the user's search and guess the product the user wants to buy. In online shopping scenarios, if e-commerce platforms can accurately capture user behavior, they can provide users with interpretable recommendations and personalized search experiences in a more intelligent and friendly manner.

 

Although only 10% of the shares have been introduced so far, based on the current test results, it is only a matter of time before it is introduced on a large scale. However, sellers still have many questions to be answered.
 

 

 

As mentioned earlier, A9 is Amazon’s long-term algorithm for search and ad ranking. It ranks search results mainly based on keyword matching and relevance.

 

According to the report, the COSMO algorithm pays more attention to the understanding of users’ intentions and purchasing behaviors. By analyzing user big data, it predicts users’ purchasing intentions, thereby providing more personalized search results and recommendations.

 

Compared with the A9 algorithm, COSMO pays more attention to the understanding of user intentions and purchasing behavior. It analyzes users' big data and predicts users' purchasing intentions to provide more personalized search results and recommendations. This algorithm change means that the keyword ranking mechanism will be subverted. Under the A9 algorithm, sales volume is often a key factor in determining rankings, resulting in search results under the same keyword often being similar products. COSMO, on the other hand, pays more attention to the diversity of products and the personalization of user needs. Even if the keyword ranking is not high, it is possible to obtain more orders.
 

 

 

 

First, sellers need to understand in detail how COSMO works, including how it analyzes user behavior, generates knowledge graphs, and optimizes recommendations and searches. This will help sellers better grasp the impact of the COSMO algorithm on product sales, thereby developing more effective marketing strategies.
 

 

 

The overall pictures, keywords, comments, and even videos of the listing must meet the user's purchase intention, which means the more content in the listing, the better, so that AI can effectively identify it, and the more overlap, the better;
 

 

 

The COSMO algorithm recommends products based on user behavior and purchase intentions. Therefore, sellers need to have a deep understanding of the shopping habits, needs and preferences of their target customers. By analyzing user data, sellers can discover potential market needs, adjust product strategies, and provide products that better meet user needs.
 

 

 

Sellers need to regularly track the impact of the COSMO algorithm on product sales and evaluate the effectiveness of various strategies. By constantly adjusting and optimizing strategies, sellers can gradually adapt to changes in the COSMO algorithm and achieve better sales performance.

 

 

Hastily adjusting a store's operating strategy may have immeasurable consequences, which will undoubtedly bring great risks to sellers. Use multiple stores to determine which operating method is more suitable for the COSMO algorithm, but multiple stores will undoubtedly have associated risks, so avoid To associate and open more stores, BitBrowser is one of the best choices for you.

 

BitBrowser allows multiple accounts to be run at the same time, creating an independent browser environment for each account. These environments are called "fingerprints" and they emulate different devices and operating systems to hide the user's true identity. This can greatly improve work efficiency for users who need to manage multiple Amazon accounts.
 

 

 

Combining BitBrowser's group control function and PRA automation function, you can complete the operation of multiple store windows faster. The group control function can synchronize all mouse and keyboard events in the master store to multiple controlled stores by setting up a master store. In the store, batch group control and synchronization operations can be performed on all stores, including: basic operations, arrangement operations, tab page operations, simulated input of the same text, simulated input of different text, one-click identification and verification code coding, etc. .If you have tedious operations required by the store, such as loading and unloading products, channel account development, etc., you only need to turn on the automation (RPA) function of BitBrowser, and create a new RPA function through a simple function combination to achieve 7x24 hours of uninterrupted operations. shop.
 

 

 

Combined with BitBrowser, sellers can easily manage multiple brands or product lines and operate multiple Amazon stores to adopt more solutions to cope with the changes brought about by the COSMO algorithm. The separation and isolation of BitBrowser ensures the security of commercial operations. and efficiency that traditional browsers cannot provide.
 

 

 

For sellers, the arrival of the COSMO algorithm means that they need to pay more attention to product differentiation and personalization. Only products that can meet the personalized needs of users can gain more exposure and orders under the new algorithm. At the same time, sellers also need to adapt to the new traffic distribution principles and improve product rankings in search results by optimizing titles, descriptions, etc. However, although COSMO has brought many changes, it does not mean that the A9 algorithm will completely withdraw from the stage of history. In fact, both algorithms have their own advantages, and the future platform may be comprehensively applied according to actual needs. Therefore, while sellers are adapting to the new algorithm, they should not neglect the optimization and operation of the A9 algorithm. At the same time, adopting a multi-account strategy combined with BitBrowser can help you adapt to and respond to the COSMO algorithm faster. BitBrowser effectively reduces the association between accounts by providing an independent browsing environment and customized browser fingerprints for each account. risks of. This is crucial, both for business expansion and long-term account security.