Guess what you like, as the name suggests, push the goods and services that users are interested in; there are so many long-term and short-term behavioral preferences generated by users, which should be pushed and how. Looking at the whatsapp database product recommendation logic, the CTR prediction model is currently most used, which combines the user's long-term and short-term browsing, collection, add-on, and purchase behaviors to whatsapp database predict the probability of users clicking on products. Second, look at the product supply chain of the platform.
The breadth and depth of the supply chain determines whether it can launch suitable products for users; there is no broad whatsapp database product pool, and guessing what you like is also "a clever woman can't cook without rice"; it is recommended to outline the user's crowd portrait and tags, the first guess provides a display scene, linking the platform's vast whatsapp database commodity pool. 2. Show Interactions and Patterns The clicks and conversions of single products are the highest. Guess you like to focus on conversions, and the display is naturally based on single products.
In order to distribute more traffic to other channels, the platform will also embed "cards" to guide users, such as Taobao's channel card, which guides users to visit the Daily Good Store channel; JD.com's venue card, which guides users to visit the whatsapp database main promotion activities of the day. ; Pinduoduo's list card, guide users to browse the best-selling list of preferred products. According to the characteristics of each platform, the traffic whatsapp database distribution of the first guess will also be emphasized. 3. Taobao In addition to the regular single-product feed stream.