Service recommendation method, service recommendation device, service recommendation equipment and computer readable storage medium

Abstract

The invention discloses a service recommendation method, which comprises the steps of acquiring user identification information of a stock user when a sharing instruction of the stock user based on acertain service on a service platform is received; generating a sharing link of the service according to the user identification information, and pushing the sharing link to a corresponding social platform according to the sharing instruction; acquiring the user identification information in the sharing link when an access request sent by the social platform based on the sharing link is received,and displaying a corresponding service interface; monitoring an operating instruction based on the service interface, and judging whether the stock user meets a preset service recommendation reward condition or not according to the operating instruction; and if so, rewarding a user account of the stock user according to a preset reward mechanism. The invention further discloses a service recommendation device, service recommendation equipment and a computer readable storage medium. According to the invention, the service sharing enthusiasm of the stock user can be improved, and the promotion scope of the service is expanded.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a service recommendation method, device, equipment and computer-readable storage medium. Background technique [0002] At present, there are various ways of marketing products based on the Internet. "Member get a memver" (MGM for short) is one of them. Push it to new users, so as to realize "bringing the new with the old". If the recommendation is successful, the existing users will be rewarded accordingly. [0003] In the prior art, when stock users make business recommendations, as long as they share the business information on the business system with others through the Internet (such as QQ, WeChat and other social software), the business system will immediately allocate fixed rewards to the stock users. The disadvantages of this are: 1) This type of reward is generally less, and existing users are not enthusiastic about sharing; 2) It is impossible to track the ...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, when stock users make business recommendations, as long as they share the business information on the business system with others through the Internet (such as QQ, WeChat and other social software), the business system will immediately allocate fixed rewards to the stock users. The disadvantages of this are: 1) This type of reward is generally less, and existing users are not enthusiastic about sharing; 2) It is impossible to track the sharing results of existing users, that is, it is impossible to know how many new members the existing users have successfully recommended. Many new members have been successfully recommended, but they cannot get more rewards, which will also lead to low sharing enthusiasm of existing users, which is not conducive to business promotion

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