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Seo Expert
Jul 28, 2022
In Welcome to the Arts Forum
First determine the target user to be recommended, and analyze the user's behavioral preferences through the target user's behavior data, such as product browsing records, search records, purchase records, etc. range of goods. Then use big data to match the browsing records of other users. The higher the matching degree of the target product range, the greater the similarity of user interests, and the more credible the analysis results. Finally, a user group with high similarity of customer interests is found. Finally, analyze the users in this user group, besides the target product, what other products have they seen? The higher the degree of overlap of the products browsed by the user group, the higher the possibility of matching the interests of the target user with these products. Country Email List The products with the highest degree of overlap can be used as the matching result and recommended to the target user. . I For example, user A has browsed products A and B. Through big data, we found user groups who have also read these two books. Through analysis, we found that most of the users in this user group have browsed products such as C. Then we can think that A's interest in commodity C may also be very large, so we can recommend C product to A. Through the use of big data, it is possible to capture the interests of users, and fundamentally change the form of marketing, from a wide-spreading form of advertising passively waiting for interested users to come to the door to actively recommending to interested users. The precise form of marketing has changed from the traditional passive marketing method to the active marketing method. . Improve overall marketing efficiency, increase transaction volume, reduce marketing costs, and help maximize profits. In offline scenarios, the work of identifying users and matching needs is mostly done in the interaction between sales staff and customers. Only when the customer actively expresses his interest, can the sales staff make recommendations according to their interests and promote the follow-up transaction work. However, in online scenarios, we can roughly analyze the user's interests without the user's explicit statement. On the whole, the biggest advantage of online is the retention and precision of data, which is more comprehensive and efficient, and can be ahead of the predecessor! The biggest advantage offline is people. If there are people, there will be trust, and the interaction with customers will be stronger! Each has its advantages and disadvantages.
In addition, a high degree of matching between users and the needs of products can prompt users to make transactions quickly content media
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