Informationized management method, platform and system

Abstract

The invention discloses an information management method. The method includes: dividing all customers into groups according to the first information and the second information in the customer information data pool; business recommendation table; when receiving the notification that the terminal held by the customer logs in to the external device, recommend business to the customer according to the business recommendation table corresponding to the group to which the customer belongs; collect the results of the business recommendation, and The collected results update the business referral form. The invention also discloses an information management platform and system at the same time. By adopting the technical solution of the present invention, after targeted recommendations are made to customers, the recommendation results can be automatically evaluated; through the evaluation results of recommendations from other similar customers of the same category, the recommendation algorithm can be continuously optimized, thereby improving the accuracy of business recommendations; Eliminate customers' aversion to business recommendations and reduce customer complaints.

Description

technical field [0001] The present invention relates to the field of business informatization support, in particular to an informatization management method, platform and system. Background technique [0002] The rapid development of communication technology makes various value-added services emerge in an endless stream. Whether in the sales industry, the Internet industry, or the telecommunications industry, there is huge information contained in the historical behavior of users. By mining the user's historical behavior, the customer's preference can be predicted, and then relevant products can be recommended to them according to the customer's preference, so as to further mine customer value. Generally speaking, a common method to mine customer value is user behavior analysis. In the prior art, by building a model on user historical behavior information, analyzing the user model to obtain the correlation between user behaviors, and then performing targeted service recomm...

AI Technical Summary

Problems solved by technology

[0006] 2. Cannot make full use of the value of other similar users

[0008] 3. The accuracy of business recommendations cannot be continuously improved automatically

[0011] The existing technology generally adopts the method of active recommendation. After mining the users to generate the recommendation list, the recommendation is made by sending a text message or directly dialing the customer phone, which is likely to arouse customer disgust and cause complaints.

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