CN114820028A

CN114820028A - Potential user recommendation method and storage medium

Info

Publication number: CN114820028A
Application number: CN202210313615.4A
Authority: CN
Inventors: 汤周文; 陈丹明; 刘旺
Original assignee: Fujian Kaimi Network Science & Technology Co ltd
Current assignee: Fujian Kaimi Network Science & Technology Co ltd
Priority date: 2022-03-28
Filing date: 2022-03-28
Publication date: 2022-07-29

Abstract

The invention discloses a potential user recommendation method and a storage medium, comprising the following steps: building a networking information platform, wherein the networking information platform is connected with more than two merchants; the networking information platform collects offline activity data of users and calculates social relations among different users according to the offline activity data; calculating potential users having the social relationship with users already existing in the merchant; and pushing the potential user to the merchant. According to the invention, potential users with social relations of existing users can be calculated through offline activity data collected by the networking information platform, and the potential users are pushed to the merchant through the social relations, so that the development range of potential users of the merchant can be expanded, and high-quality potential customers can be recommended to the merchant.

Description

Potential user recommendation method and storage medium

Technical Field

The present application relates to the field of big data technologies, and in particular, to a potential user recommendation method and a storage medium implemented based on big data.

Background

For different industries such as the digital entertainment field, catering, health care and the like, how to efficiently and accurately find target consumer groups has always been the key and difficult point of merchant operation. The traditional marketing mode is mainly updated by advertising, leaflet and the like, and the marketing mode has high cost and general effect. And the current marketing activities of the merchants only relate to existing member users of the merchants or universal members which have been activated by the merchants, so that the popularization range of the existing marketing information is limited, and target users which do not come from the merchants but have consumption potential are difficult to touch, thereby seriously restricting the development and the performance increase of the merchant users. Therefore, how to efficiently pull new is an urgent need of the merchant.

Disclosure of Invention

In view of the above problems, the present application provides a potential user recommendation method, which is used to solve the technical problems of low efficiency and high cost of the conventional marketing method.

To achieve the above object, the inventor provides a potential user recommendation method, comprising the following steps:

building a networking information platform, wherein the networking information platform is connected with more than two merchants;

the networking information platform collects offline activity data of existing users of each accessed merchant and calculates social relations among different users according to the offline activity data;

calculating potential users having the social relationship with users existing in each of the merchants;

and pushing the potential users to the corresponding merchants.

Further, in some aspects, the offline activity data includes data of activities performed by the user in the same location.

Further, in some aspects, the venue comprises a digital entertainment venue having more than one car, each car having a unique feature code, and the user accessing the feature code is collected to determine that the user is traveling to the same car in the same venue.

Further, in some embodiments, the "calculating social relationships between different users according to the offline activity data" includes:

counting the times that more than two users access the feature code of the same box in a preset time period;

and calculating the social relationship among the users according to the times, wherein the closeness of the social relationship is positively correlated with the times.

Further, in some technical solutions, before the step of "pushing the potential user to each corresponding merchant", the method further includes the steps of:

and if existing users which are already the merchants exist in the potential users, removing the existing users.

and if the potential users have users with resident addresses which are not located at the business place of the merchant, rejecting the users.

Further, in some technical solutions, the networked information platform is connected to more than two merchants in different industries.

Further, in some technical solutions, the method further includes the steps of:

before the potential user registers as the user of the merchant, the merchant can only send marketing information to the potential user through the networked information platform, so that the privacy of the user is better protected.

Further, in some technical solutions, the networking information platform includes a cloud server, and the cloud server is configured to provide cloud services for two or more merchants.

In order to solve the above technical problems, the present invention further provides another technical means:

a computer storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of any one of the above claims.

Different from the prior art, the technical scheme is that a networking information platform is built, the networking information platform collects offline activity data of users, and the social relationship among different users is calculated according to the offline activity data; calculating potential users having the social relationship with the users existing in the merchant; and pushing the potential user to the merchant. According to the technical scheme, the potential users with social relations of the existing users can be calculated through the offline activity data collected by the networking information platform, and the potential users are pushed to the merchant through the social relations, so that the development range of the potential users of the merchant can be expanded, and meanwhile, the users with the social relations are similar, and the pushed users are also in accordance with the consumption characteristics of merchant positioning. This also recommends potential customers of better quality for the merchant.

The above description of the present invention is only an overview of the technical solutions of the present application, and in order to make the technical solutions of the present application more clearly understood by those skilled in the art, the present invention may be further implemented according to the content described in the text and drawings of the present application, and in order to make the above objects, other objects, features, and advantages of the present application more easily understood, the following description is made in conjunction with the detailed description of the present application and the drawings.

Drawings

The drawings are only for purposes of illustrating the principles, implementations, applications, features, and effects of particular embodiments of the present application, as well as others related thereto, and are not to be construed as limiting the application.

In the drawings of the specification:

FIG. 1 is a flow chart of a method for potential user recommendation in accordance with an embodiment;

FIG. 2 is a schematic diagram of a networked information platform, in accordance with an embodiment;

FIG. 3 is a flow diagram illustrating the calculation of social relationships between users, according to an embodiment;

FIG. 4 is a flowchart of a method for potential user recommendation in accordance with an embodiment;

FIG. 5 is a schematic diagram of a computer storage medium according to an embodiment;

the reference numerals referred to in the above figures are explained below:

201. a networked information platform;

500. a computer storage medium;

Detailed Description

In order to explain in detail possible application scenarios, technical principles, practical embodiments, and the like of the present application, the following detailed description is given with reference to the accompanying drawings in conjunction with the listed embodiments. The embodiments described herein are merely for more clearly illustrating the technical solutions of the present application, and therefore, the embodiments are only used as examples, and the scope of the present application is not limited thereby.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase "an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or related to other embodiments specifically defined. In principle, in the present application, the technical features mentioned in the embodiments can be combined in any manner to form a corresponding implementable technical solution as long as there is no technical contradiction or conflict.

Unless defined otherwise, technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the use of relational terms herein is intended only to describe particular embodiments and is not intended to limit the present application.

In the description of the present application, the term "and/or" is a expression for describing a logical relationship between objects, meaning that three relationships may exist, for example a and/or B, meaning: there are three cases of A, B, and both A and B. In addition, the character "/" herein generally indicates that the former and latter associated objects are in a logical relationship of "or".

In this application, terms such as "first" and "second" are used merely to distinguish one entity or operation from another entity or operation without necessarily requiring or implying any actual such relationship or order between such entities or operations.

Without further limitation, in this application, the use of "including," "comprising," "having," or other similar expressions in phrases and expressions of "including," "comprising," or "having," is intended to cover a non-exclusive inclusion, and such expressions do not exclude the presence of additional elements in a process, method, or article that includes the recited elements, such that a process, method, or article that includes a list of elements may include not only those elements but also other elements not expressly listed or inherent to such process, method, or article.

As is understood in the examination of the guidelines, the terms "greater than", "less than", "more than" and the like in this application are to be understood as excluding the number; the expressions "above", "below", "within" and the like are understood to include the present numbers. In addition, in the description of the embodiments of the present application, "a plurality" means two or more (including two), and expressions related to "a plurality" similar thereto are also understood, for example, "a plurality of groups", "a plurality of times", and the like, unless specifically defined otherwise.

As shown in fig. 1 to 4, the present invention provides a potential user recommendation method, which can be applied to different industries such as digital entertainment, catering, and health care, and is used for recommending high-quality potential users for merchants of various industries. According to the potential user recommendation method, online data of users are collected by building a networking information platform, the social relations among different users are calculated by utilizing the offline data, and potential user recommendation is carried out according to the social relations. Because the closer the social relationship is, the higher the similarity is, the closer the consumption habits and interests are, the potential user recommendation method utilizes the similarity between the users with the social relationship to recommend the potential users to the merchant, thereby improving the range and the accuracy of the development of the potential users of the merchant.

As shown in FIG. 1, in one embodiment, a potential user recommendation method includes the steps of:

s101, building a networking information platform, wherein the networking information platform is connected with more than two merchants;

s102, the networking information platform collects offline activity data of existing users of each accessed merchant, and calculates social relations among different users according to the offline activity data;

s103, potential users having the social relation with the existing users of all the merchants are calculated;

and S104, pushing the potential users to the corresponding merchants.

As shown in fig. 2, in step S101, the networked information platform 201 may connect to multiple merchants, such as a first merchant, a second merchant, and the merchants are connected to the networked information platform 201 through the internet, and data of the merchants may be transmitted to the networked information platform 201 through the network. The merchant can be merchants in different industries such as the digital entertainment field, catering, health care and the like. In some embodiments, the merchants to which networked information platform 201 connects may also be of the same industry, and the merchants may also be of other areas. The networked information platform 201 may be provided with a server for storing and computationally analyzing data uploaded by various merchants. Before collecting data of a merchant, the networked information platform 201 needs to obtain authorization permission of the merchant first, and if the data of the merchant is not authorized by the merchant, the networked information platform 201 cannot collect the data of the merchant. Preferably, the networking information platform is connected with more than two merchants in different industries. Therefore, the sharing of resources and information among different industries can be effectively promoted, and high-quality merchants of different industries are recommended for the user.

In step S102, the offline activity data refers to activities within the same spatial range that are not completely performed through the network, and the offline activity data includes whether the user participates in the same offline activity. In some embodiments, the collected offline activity data includes only the participating people, and the offline activity data may not include specific content of the offline activity, such as eating together, karaoke, games, and the like.

In step S102, the social relationship is used to reflect the closeness of daily life and interaction between different users. Social relationships may include general friends (only known, not frequently connected), good friends (closely connected), and so on. Social relationships may be represented by specific numerical values, with higher numerical values representing closer connections between different users. The higher the value of the social relationship among different users, the greater the similarity value and the relevance. When the social relationship data of the users exceed the preset value, the users can be considered as the friendship. Having a social relationship between two users may characterize that the two users are likely to have some similarity in terms of age, hobbies, consumption habits, etc. of the behavior characteristics related to the user representation. In some embodiments, the social relationship data of the users may be calculated by counting the number of times the users participate in the same offline activity or the same place of offline activity, and the social relationship data between the users is considered to be larger when the number of times the different users participate in the same offline activity or the same place of offline activity is larger.

In step S103, the networking information platform first obtains an existing user set of the merchant, and then takes out users having social relationships with the merchant user set to form a candidate user set, where the candidate user set is a potential user. For example, for each merchant a, first, an existing user set UserSet of the merchant a is obtained, and then users having a social relationship with the user set UserSet are taken out to form a candidate user set CandidateUserSet.

In step S104, the potential users obtained in step S103 may be recommended to the corresponding merchants. In some embodiments, the potential users obtained in step S103 may be further filtered and then recommended to the merchant.

The inventor has found through research and analysis that users with similar hobbies and consumption habits generally participate in the same activities, for example, people with the same hobbies, income, age or occupation will often get together to get together for a party. Based on the discovery of this characteristic, the inventor proposes a potential user recommendation method, which collects data of online activities of different users together, analyzes social relationships among the different users according to the collected online data, and then recommends potential users for a merchant according to the social relationships (i.e. similarity relationships) of the users. According to the technical scheme, the potential users with social relations of the existing users can be calculated through the offline activity data collected by the networking information platform, and the potential users are pushed to the merchants through the social relations, so that the development range of the potential users of the merchants can be expanded, and high-quality potential customers can be recommended to the merchants.

In some embodiments, the offline activity data includes data of a user performing an activity to the same venue. The places comprise digital entertainment places such as KTVs, bars, cinemas and the like, the digital entertainment places are provided with more than one box, each box is provided with a unique feature code, and users are confirmed to move to the same box in the same place by acquiring the feature codes accessed by the users. The feature code can be associated with the multimedia entertainment system in the box, and a user can access the multimedia entertainment system in the box by scanning the feature code, so that the multimedia entertainment system can be controlled by an intelligent terminal such as a mobile phone after access, for example, song ordering, online commodity ordering and the like can be carried out by the mobile phone.

In the embodiment, the same box in the same place can be conveniently collected by a user to move through the box feature code.

As shown in fig. 3, in some embodiments, the "calculating social relationships between different users from the offline activity data" comprises the steps of:

s301, counting the times that more than two users access the feature code of the same box in a preset time period;

s302, calculating the social relationship of the user according to the times, wherein the affinity of the social relationship is positively correlated with the times.

In step S301, if two users both access the feature code in the box within the same preset time period, the two users are considered to have been moved together within the parameter line in the box, and the social number of the two users is incremented by one. The preset time period can be the same day or the same half day (for example, the same afternoon or the same evening), the times of visiting the feature codes of the same box are counted in the same preset time period, the total number of people visiting the feature codes of offline activities in different fields in the same box can be effectively eliminated, and therefore the accuracy of social relationship calculation is improved. In particular embodiments, when calculating a user entertainment social relationship, it may be defined that a social relationship between two users is only present when the number of times that the two users have a social relationship is greater than or equal to n (n > 0). In some embodiments, in order to increase the reliability of the social relationship, the number of social contacts n may be set to be larger.

In some embodiments, before said "pushing said potential user to said merchant" further comprises the steps of:

rejecting users that are already the merchant among the potential users.

Further, in some embodiments, before the "pushing the potential user to the merchant", the method further includes:

and eliminating users whose resident addresses are not located at the business place of the merchant from the potential users.

As shown in fig. 4, in this embodiment, the potential user recommendation method includes the following steps:

s401, building a networking information platform, wherein the networking information platform is connected with more than two merchants;

s402, the networking information platform collects offline activity data of each user accessing to a merchant and calculates social relations among different users according to the offline activity data;

s403, calculating potential users having the social relationship with the existing user of the merchant;

s404, eliminating users whose resident addresses are not located at the business place of the merchant from the potential users;

s405, pushing the potential users to the corresponding merchants.

In the embodiment, people who have social relations with existing users but are not likely to reach the site for consumption due to regional factors can be effectively screened out, so that the quality of the recommended potential customers is guaranteed.

In some embodiments, further comprising the step of:

In some embodiments, the networked information platform includes a cloud server for providing cloud services to two or more of the merchants. The cloud server can be a cloud service platform provided by cloud service providers such as Ali cloud and Baidu cloud. Cloud services such as cloud storage, data processing and operation services can be provided for different merchants connected with the networking information platform through the cloud server.

As shown in fig. 5, in an embodiment, there is further provided a computer storage medium 500 on which a computer program is stored, which when executed by a processor, implements the steps of the potential user recommendation method according to any of the above technical solutions.

The computer storage medium 500 is implemented by setting up a networking information platform, wherein the networking information platform collects offline activity data of users and calculates social relationships among different users according to the offline activity data; calculating potential users having the social relationship with the users existing in the merchant; and pushing the potential user to the merchant. According to the technical scheme, the potential users with social relations of the existing users can be calculated through the offline activity data collected by the networking information platform, and the potential users are pushed to the merchants through the social relations, so that the development range of the potential users of the merchants can be expanded, and high-quality potential customers can be recommended to the merchants.

Finally, it should be noted that, although the above embodiments have been described in the text and drawings of the present application, the scope of the patent protection of the present application is not limited thereby. All technical solutions which are generated by replacing or modifying the equivalent structure or the equivalent flow according to the contents described in the text and the drawings of the present application, and which are directly or indirectly implemented in other related technical fields, are included in the scope of protection of the present application.

Claims

1. A method for potential user recommendation, comprising the steps of:

the networking information platform collects offline activity data of each user accessing to a merchant and calculates social relations among different users according to the offline activity data;

and pushing the potential users to the corresponding merchants.

2. The method of potential user recommendation according to claim 1, wherein said offline activity data comprises data of a user performing an activity to the same location.

3. A method for recommending potential users according to claim 1 or 2, characterized in that said venue comprises a digital entertainment venue having more than one compartment, each of said compartments being provided with a unique signature code, said signature code being accessed by a user to determine that the user is performing an activity in the same compartment of the same venue.

4. The potential user recommendation method according to claim 3, wherein said "calculating social relationships between different users according to said offline activity data" comprises the steps of:

5. The method of claim 1, further comprising, before the step of pushing the potential users to the corresponding merchants:

6. The method of recommending potential users according to claim 1, further comprising, before said step of pushing said potential users to respective corresponding said merchants, the steps of:

7. The method of claim 1, wherein two or more merchants of different industries are connected to the networked information platform.

8. The method of potential user recommendation according to claim 1, further comprising the steps of:

the merchant can only send marketing messages to the potential user through the networked information platform before the potential user registers as a user of the merchant.

9. The potential user recommendation method of claim 1, wherein the networked information platform comprises a cloud server configured to provide cloud services for two or more of the merchants.

10. A computer storage medium on which a computer program is stored, which program, when executed by a processor, carries out the steps of any of claims 1 to 9.