However, the COSMO algorithm, based on the huge "general human common sense" stored in the large AI language model and asking "the reasons for users' purchases or joint purchases", analyzes "the importance of anti-slip and other functions for pregnant women", thereby recommending products such as anti-slip shoes that better suit the actual needs of pregnant women.
This recommendation engine, based on a large model of artificial intelligence language, not only helps to increase user satisfaction and improve the shopping experience, but also helps to increase sales. The recommendation engine kazakhstan number data brings more than 35% of the revenue of Amazon's e-commerce platform.
The COSMO algorithm also improves search navigation by adding multi-round navigation to help users accurately express and satisfy their purchase intent. For example, when searching for "camping" products, the algorithm refines recommendations based on the user's successive selections, presenting options such as "air mattresses," "tents," "blankets," "lanterns," and other camping products. If the user selects "air cushion," it further refines to "camping air cushion," greatly improving the accuracy and user experience of the search.
4. How should merchants adjust their operational direction with the launch of the COSMO algorithm?
These changes indicate that the focus of sellers should no longer be solely on "keyword indexing," but rather on implementing more optimizations around the product itself, improving aspects such as appearance, functionality, color, etc. to create product differentiation. Sellers should diversify and comprehensively improve the accuracy of their listings, refining all the details within the link to provide more accurate AI-powered recommendations.