JP7488622B1 - Information processing device and computer program - Google Patents

Abstract

[Problem] To provide a new platform technology for communities. [Solution] An information processing device 1 provides a dedicated platform for multiple communities, each of which has an owner and members gathering on the Internet NW. This information processing device 1 acquires target content and the chronological behavioral details of the owner and members based on the behavioral policy of each community, analyzes the behavioral policy and the behavioral details, and personalizes each community. It also analyzes the interest prediction value in the target content for each community based on the analysis results. Then, one or more communities are selected according to the analysis results, and the target content is presented to the selected one or more communities, while qualitatively or quantitatively evaluating the change in the behavioral details of the community resulting from the presentation. [Selected Figure] Figure 1

Description

The present invention relates to an information processing device and a computer program that provide a platform for a community on a computer network, for example.

In recent years, communities (online communities), which are places for communication on computer networks, are often used for business purposes. For example, Patent Document 1 discloses a technology for using communities for marketing. This technology focuses on a user whose behavior has changed within the community, and extracts comment information from other users to whom that user responded in the community, thereby extracting comment information that influences the user's behavior due to some factor, and analyzes the content of this information for use in marketing.

Patent document 2 discloses a technology that acquires user action information indicating actions taken by multiple users who use a community toward visiting a target store, and estimates the level of preference of each of multiple store users on the waiting list for cancellations in the community based on this user action information, so that the lower the level of preference, the more likely the user is to be selected as a target user who will be notified about changing a reservation to one of the available stores.

Patent document 3 discloses a technology that acquires activity information for each community, extracts community characteristics from the acquired activity information, and recommends at least one category to a target community based on the community characteristics.

Japanese Patent No. 5815168 JP 2022-80621 A JP 2022-87835 A

As the lifestyles of consumers and others have become more diverse due to the spread of network technology, market needs for business items have changed significantly. Furthermore, as digital technology evolves, new market needs or new markets that did not exist before are often born. For this reason, the forms of community utilization based on the results of analyses of previous facts, etc., as disclosed in Patent Documents 1 to 3, have made it difficult to accurately grasp the ever-changing market needs, and improvements were required.

One of the objectives of the present invention is to provide a community platform technology that facilitates marketing that flexibly responds to the fluidity of market needs for business items. Other objectives of the present invention will become apparent from this disclosure.

One aspect of the present invention is an information processing device that provides a dedicated platform for a plurality of communities on a computer network, each of which has an owner and members, the information processing device comprising: an acquisition means for acquiring the chronological behavioral details of the owner and the members based on a course of action for each community, the owner attributes of the owner, and the member attributes of the members; an analysis means for analyzing the course of action, the owner attributes, the member attributes , and the chronologically acquired behavioral details of the owner and the members, and for classifying the communities, the owner, and the members into new communities by grouping, subdividing, or hierarchizing them according to a predetermined criterion according to the analysis results; and a management means for saving the new classified communities as new destinations for the platform. This information processing device can be realized, for example, by a computer having a communication function reading and executing a computer program.

The above aspect of the invention provides a community platform technology that facilitates marketing that flexibly responds to the fluidity of market needs for products and services.

1 is a diagram illustrating an overall configuration of an information processing apparatus according to an embodiment of the present invention. FIG. 13 is a diagram illustrating an example of grouping owners with similar attributes. FIG. 1 is a diagram illustrating an example of a community on the Internet as viewed from an information processing device. FIG. 13 is a view showing an example of a top screen specific to a certain registered community. FIG. 2 is a diagram illustrating a procedure of hypothesis processing by an information processing device. FIG. 13 is a detailed explanatory diagram of the zeroth-order hypothesis processing. FIG. 13 is a detailed explanatory diagram of the first hypothesis processing. FIG. 13 is a detailed explanatory diagram of the secondary hypothesis processing. FIG. 13 is a detailed explanatory diagram of the third hypothesis processing. FIG. 13 is a detailed explanatory diagram of the fourth hypothesis processing.

Below, we will explain an embodiment of the present invention applied to an information processing device that provides a platform for multiple communities (online communities) on a computer network where owners and members who share common attributes and interests gather. A community is, for example, a group of members brought together by an owner or who are under the influence of the owner (region, ideas, events, values), or a collection of their respective attributes.

The information processing device of this embodiment facilitates support for, for example, POC (Proof of Concept) processing, test marketing processing, fan marketing processing, and the like, through the community.
POC involves the process of conducting various hypothesis testing to determine whether a product (including a product or its parts, product groups, and parts groups) or a service (including intangible services) can actually be established as a business item, demonstrating the results of such hypothesis testing in a community environment that is as close as possible to the actual market environment, and evaluating the results of the testing from various perspectives.
Test marketing is a process in which consumers try out a new product or service before its release and analyze their reactions. Fan marketing is a marketing process aimed at increasing the number of fans of a product or service.

[overall structure]
1 is an explanatory diagram of a computer network environment including an example of a functional configuration of an information processing device 1 according to the present embodiment. The information processing device 1 is a computer having a communication function connected to the Internet NW, which is an example of a computer network, and has a computer unit having a CPU (Central Processing Unit), a ROM (Read only memory), a RAM (Random Access Memory), a storage such as an SSD (Solid State Drive), and an input/output interface for these. The present invention can be implemented by having this computer unit execute the computer program of the present invention.

Multiple communities have been established on the Internet NW. Therefore, multiple member terminals MT and multiple owner terminals OT are connected to the Internet NW. The member terminals MT are communication terminals operated by members, and the owner terminals OT are communication terminals operated by owners. Both are information terminals with communication functions that have the above-mentioned computer unit.

In the information processing device 1, the CPU reads and executes the computer program of the present invention, causing the above computer units to operate as a communication control unit 11, a registration unit 12, an information acquisition unit 13, an analysis unit 14, an analysis unit 15, a management unit 16, an evaluation unit 17, an information presentation unit 18, and a main control unit 19. In addition, a community DB 21, an owner DB 22, a member DB 23, a content DB 24, and a POC information DB 25 are constructed within the storage.

The communication control unit 11 controls communication with the Internet NW. The registration unit 12 registers communities established in the Internet NW and posted content in the community DB 21. Registered communities may be called registered communities. The registration unit 12 also registers target content to be presented to each community, such as the content of products or services that are potential business items, or the content of combinations of products and services and the conditions for providing them, in the content DB 24 in a manner that allows the content to be changed.

The registration unit 12 also performs owner registration processing and member registration processing.
The owner registration process accepts the opening of a community and registers in owner DB22 the community's policy (purpose, direction, shortcomings, value desired to be given to the community, etc.), owner attributes which are the attributes of the owner, and the owner's behavioral history such as disseminating information, along with the owner's email address, in association with the community's identification information.

From the viewpoint of protecting personal information, it is desirable that the owner attributes are pseudo-personality attributes that are one-to-one replicas of real human attributes (date of birth, blood type, gender, etc.) excluding personal names. The pseudo-personality attributes are determined, for example, based on fortune-telling information based on human attributes. This makes it possible to predict the behavior of owners in individual communities without knowing the owner attributes in detail.

The member registration process registers, for each community, the member attributes of the members participating in the community, along with the member's email address and the request information requested by the owner that was entered when joining the community. "For each community" means that it is associated with the identification information of the community. The request information is, for example, a question from the owner, favorite food, favorite animal, etc.

The member DB 23 also stores the behavioral history of members in the community. It is preferable that these member attributes are also the pseudo-personality attributes described above. This makes it possible to predict the behavior of a member without knowing the member attributes in detail.

Note that an owner may host one community while participating as a member in other communities. In this case, the owner will be registered in both the owner DB 22 and the member DB 23.

The information acquisition unit 13 acquires various information from each owner terminal OT, each member terminal MT, registered communities, other websites, and each DB 21 to 24. For example, target contents are acquired from a request terminal (not shown) or an owner terminal OT connected to the Internet NW, or from the POC information DB 25. One of the target contents when used for POC is, for example, one or more POC hypotheses created or revised to predict the feasibility of a business for a business item candidate, and a POC result reflecting the result.
The information acquisition unit 13 also acquires the chronological behavioral details of the owner and members based on the behavioral policy for each community from the owner terminal OT, the member terminal MT, the owner DB 22, or the member DB .

The analysis unit 14 analyzes the contents of the communities. For example, it analyzes the course of action for each community, the owner attributes, the member attributes, and the behavioral content of the owner and members acquired in time series, and performs grouping, subdivision, and hierarchical classification of the communities, owners, and members according to the analysis results. In addition, when grouping, each group is individualized and then each group is added to and registered in the community DB 21 as a new community.
Incidentally, "individualization" refers to classifying into categories that represent, for example, cultures and values that are unique to a community, etc. The categories are one of the pieces of identification information for a community, etc., and are preferably quantitative values, etc., but may also be qualitative words, etc.

Figure 2 is an example diagram of grouping communities, etc. Here, focusing on owner attributes, group G10, which includes multiple owners who are similar in "income" beyond a specified standard among multiple communities that actually exist, and another group G20, which includes owners who are similar in "hobbies, tastes" beyond a specified standard, are shown. In addition, owners who are similar in "gender," "age," "organization," "ideology," etc. beyond a specified standard may be grouped. The same applies to communities or members. Subdivision, for example, is separating members of a single community who have the same or similar "income," "hobbies, tastes," "gender," "age," "organization," "ideology," etc., and hierarchization is, for example, hierarchizing grouped or subdivided communities, etc. by genre.

By grouping, subdivision, hierarchical organization, etc., the communities existing on the Internet NW as seen from the information processing device 1 are as shown in FIG. 3. That is, in the illustrated example, a grouped "PTA" community G30, a "study group" community G40, a "company A" community G50, a "dojo" community G60 for judo, etc., and hierarchical groups G#1, G#2, etc., which are further subdivided and hierarchicalized from multiple communities, are shown.

The analysis unit 14 may obtain and analyze, in addition to the course of action for each community, the rate at which information sent by the owner in the community is communicated to members and/or the members' reactions to the information sent, for example, from the community DB 22, and may individualize the community based on the results of this analysis. The communication rate can be calculated, for example, from the ratio of the number of reactions by members to the number of messages sent by the owner, or the number of members who responded to one piece of information sent by the owner.

The analysis unit 14 may analyze the course of action for each community and the action content of each community, as well as at least any of the owner attributes, member attributes, owner attributes and member attributes, and combinations of relationship information representing the personal relationships between the owner and members, and may individualize the community based on the results of this analysis.
Alternatively, the analysis unit 14 may analyze market needs based on the market conditions of various products and the like acquired from the corresponding website on the Internet NW.

The analysis unit 15 analyzes the interest times and member trends of each community. For example, based on the results of the analysis by the analysis unit 14, the interest prediction value for the target content when the target content is presented is analyzed for each community. The interest prediction value is, for example, a numerical value between 1% and 99%, and is derived by machine learning statistical values of behavioral history and the like obtained from numerous community sites and websites, owner DB 22, and member DB 23 that exist on the Internet NW.

The following describes the management unit 16. The management unit 16 mainly performs community management, owner management, member management, content management, and hypothesis management.

The community management performed by the management unit 16 searches for communities that meet predetermined conditions among the many communities existing on the Internet NW in addition to the registered communities, and identifies the owner attributes of the owner and the member attributes of the members of the community identified by the search.The identified owner attributes are additionally registered in the owner DB 22, and the identified member attributes are additionally registered in the member DB 23.A new community that has been grouped, subdivided, and hierarchized by the analysis unit 15 is also generated, and this is additionally registered in the community DB 21.In addition, information on the registered or additionally registered community is appropriately modified or deleted.

The owner management performed by the management unit 16 includes, for example, registering, adding, modifying, and deleting owner attributes for each community in the owner DB 22, and associating member attributes of the same person with communities. Another aspect of owner management is to identify owners with similar attributes based on the owner attributes and associate the identified owner attributes with each other. The similarity of owner attributes can be determined, for example, by using a collaborative filtering algorithm. In addition to collaborative filtering, known clustering algorithms and machine learning algorithms can also be used.

The member management performed by the management unit 16 involves registering, adding, modifying and deleting member attributes for each community in the member DB 22, and associating the same person's owner attributes with communities. Another aspect of member management is to identify members with similar attributes based on the member attributes and associate the identified member attributes with each other. The method for determining whether member attributes are similar can be the same as the method for determining whether owner attributes are similar.

The content management performed by the management unit 16 involves generating unique content or original applications that are expected to have a certain interest prediction value or greater, for example, based on the behavioral history of members of a registered community, or acquiring them from the owner terminal OT, registering them in the content DB 24, and accepting editing or deletion as appropriate.
An example of the unique content is a video, still image, application, or URL of a website where these are stored that is linked to a top screen or a lower-level screen that is unique to the community. The above-mentioned target content is also an example of the unique content.

Figure 4 is an example diagram of unique content. In the example of Figure 4, a top screen that is unique to a certain registered community is shown. In the example shown, in addition to "Announcements" 201, 202 and "Announcements from the community owner" 203 for all registered communities, a content group 200 that can only be viewed or used by the owner and members of the registered community is posted.

The hypothesis management performed by the management unit 16 generates hypotheses for test marketing, fan marketing, and POC of the target content. A hypothesis is a tentative answer that is considered to be the most likely, and can be generated using the analysis results of the analysis unit 14 and/or the analysis results of the analysis unit 15. For example, when the interest prediction value for a certain product is low, one of the hypotheses may be that "the price is too high" or "there are too many unnecessary functions."
There are two types of hypotheses: "current situation hypotheses" and "action hypotheses." Current situation hypotheses are hypotheses based on a guess at the current situation, such as "this is probably how it is." The current situation hypotheses have the advantage of making it clear who to ask and what to ask. On the other hand, action hypotheses are strategic hypotheses based on action plans, such as "if the current situation hypothesis is like this, then perhaps adopting this strategy will work well."

The evaluation unit 17 will now be described. The evaluation unit 17 performs various evaluations according to the purpose of each community. Information for the evaluation can be obtained, for example, from the community DB 21, the owner DB 22, the member DB 23, and the content DB 24, and/or the analysis results of the analysis unit 15 obtained via the management unit 16.

In one embodiment, the evaluation unit 17 verifies the above hypothesis. In another embodiment, the evaluation unit 17 selects one or more communities to which the target content is to be introduced according to the results of the analysis by the analysis unit 16, presents the target content to the selected one or more communities, and qualitatively or quantitatively evaluates changes in the behavioral content of the communities resulting from the presentation. The one or more communities to which the content is to be presented are selected, for example, by identifying one or more communities with a relatively high interest prediction value. Alternatively, the selection is performed by identifying all communities with an interest prediction value for the target content that exceeds a certain value.

The information presenting unit 18 presents the presented content to the community selected by the evaluation unit 17 via the communication control unit 11 .
The main control unit 19 comprehensively controls the operations of the communication control unit 11, registration unit 12, information acquisition unit 13, analysis unit 14, analysis unit 15, management unit 16, evaluation unit 17, and information presentation unit 18 described above.

[Operation form]
Next, an example of operating the information processing device 1 configured as above as a POC platform will be described. Here, an example of the case where the information processing device 1 performs processes in the order of 0th hypothesis processing S0, 1st hypothesis processing S1, 2nd hypothesis processing S2, 3rd hypothesis processing S3, 4th hypothesis processing S4, and POC processing S5 as shown in Fig. 5 will be described.

FIG. 6 is a diagram illustrating a detailed procedure of the zeroth-order hypothesis process (S0) executed by the information processing device 1.
In the zeroth hypothesis process, a current hypothesis process is performed for POC preparation. The information processing device 1 first accepts input of information on a set rental of multiple products that are candidate business items as an example of target content (S01). Then, a target content analysis (S02) and a community analysis (S03) are performed. In this example, the target content analysis is the content of multiple products and the offered price for the set rental. The community analysis is a process of searching for a community where topics related to product set rental are being discussed, for example.

If such a community exists, the information processing device 1 determines the target customer (expected customer) for the product set rental (S04). Target customers include purchasers, prospective purchasers, and those considering purchasing. When the target customer is determined, the information processing device 1 selects a community of interest, that is, a community to which content related to the product set rental (catalogs, proposals, etc.) will be presented, and presents the content (S05). The information processing device 1 detects the degree of community reaction (S06) and stores (registers) the detection result in the POC information DB 25 (S07). The degree of community reaction can be detected, for example, from the number of comments made by the owner and members, the content of the comments (positive/negative), the reaction rate of members to the owner's comments (positive/negative/ignored), the ratio of the above interest prediction value to a predetermined reference value, etc.

FIG. 7 is a diagram illustrating a detailed procedure of the primary hypothesis process (S1) executed by the information processing device 1.
In the first hypothesis processing, hypothesis processing is performed focusing on the attributes of the owner, utilizing the rule that the attributes tend to have a large influence on the awareness and behavior of each member of the community.
The information processing device 1 first analyzes the detection results of the zero-order hypothesis processing (S11). Depending on the analysis results, the conditions for providing the product set rental are changed. Next, the owner attributes of the owner who leads the presented community are acquired (S12), and it is determined whether the owner's behavior regarding the product set rental has been predicted based on the owner attributes (S13). If the behavior has been predicted (S13: Y), the owner is registered as a persona for the product set rental (S14). A "persona" is a virtual personality with a unique personality, and is created based on various purchasing activities and behavioral histories. In this embodiment, the persona is used as a virtual personality for purchasing prediction and preference prediction.

The information processing device 1 estimates the purchasers of the product set rental based on the behavioral history of the owner who is the persona (S15), and detects the market needs for the product set rental, for example, by accessing the corresponding website on the Internet NW (S17). In addition, other communities to which owners who have attributes similar to the owner attributes of the owner belong are detected as similar communities (S18). Information on similar communities can be used to detect communities or similar market needs to be used for the next hypothesis processing. If the owner's behavior is not predicted in S13 (S13:N), behavioral information is obtained by a separate method, such as by interviewing the owner by email, and prediction processing is performed (S16), and then the process of detecting market needs is started (S17). The information processing device 1 stores (registers) the results of the first hypothesis processing in the POC information DB 25 (S19).

FIG. 8 is a diagram illustrating a detailed procedure of the secondary hypothesis process (S2) executed by the information processing device 1.
In the secondary hypothesis processing, hypothesis processing is performed focusing on the attributes of each member of the community. That is, the information processing device 1 first analyzes the results of the primary hypothesis processing, and if a new problem is found, changes the conditions for providing the target content, which is the product set rental (S21). In addition, the information processing device 1 acquires the member attributes of the members of the community to which the product set rental information is presented (S22), and determines whether the behavior of the target content has been predicted based on the member attributes (S23). If the behavior has been predicted (S23: Y), the member is registered as a persona for the product set rental (S24). The personas are as described above.

Based on the behavioral history of the persona member, the purchaser of the product set rental is estimated (S25), and the market needs for the product set rental are detected (S27). In addition, similar members having attributes similar to the member attributes of the persona member and other communities to which the similar members belong are detected as similar communities (S28). Information on similar members can be used to provide a platform for a new community, or to detect similar market needs.
In S23, if the member's behavior is not predicted (S23: N), the behavior information is obtained by a different method, such as by interviewing the member by email, and prediction processing is performed based on the behavior information (S26), and then the process proceeds to market needs detection processing based on the result (S27). The information processing device 1 stores (registers) the result of the secondary hypothesis processing in the POC information DB 25 (S29).

FIG. 9 is a diagram illustrating a detailed procedure of the third hypothesis process (S3) executed by the information processing device 1.
In the tertiary hypothesis process, processing is performed on the execution hypothesis of the first stage. That is, the information processing device 1 analyzes the results of the primary hypothesis process and the secondary hypothesis process (S31). If a new problem is found based on the results of the analysis, the provision conditions of the product set rental are changed.
The information processing device 1 then provides actual product samples to the owners and members registered as personas and has them actually use them, and collects information via e-mail or the like on areas for improvement in the form of delivery, possibility of purchase, current price, requests, etc. (S33).

The information processing device 1 analyzes the collected contents and quantitatively or qualitatively evaluates the degree of satisfaction of the personas with the products provided as samples using the above-mentioned method (S34). If the overall satisfaction level is lower than the expected standard value (S34: N), the information processing device 1 acquires information that another sample corresponding to the set rental provision conditions when the set rental price or product combination is changed has been provided to the persona again, and returns to the processing of S33 (S35). If the satisfaction level exceeds the expected standard value in S34 (S34: Y), the information processing device 1 performs processing to increase the index representing the likelihood, i.e., the certainty, of the market needs detected in the previous hypothesis processing (S36), and detects further similar members (S37). The information processing device 1 stores (registers) the results of the third hypothesis processing in the POC information DB 25 (S38).

FIG. 10 is a detailed procedure diagram of the fourth hypothesis processing (S4) executed by the information processing device 1. In the fourth hypothesis processing, processing related to the second stage execution hypothesis is performed. That is, the information processing device 1 analyzes the results of the third hypothesis processing (S41). If a new problem is discovered as a result of the analysis, a candidate measure for solving the problem is identified, for example, by machine learning using information on the solving method of the problem discovered so far as input. In addition, the interpersonal bias of the owner and members of the community to which the persona identified in the third hypothesis processing belongs is detected (S42). The interpersonal bias is a numerical value estimated, for example, based on the degree of the content (positive/negative/ignored) of the response to the owner in response to the member's statement.

The information processing device 1 determines the conditions for providing the product sample redetermined based on the interpersonal bias or a different sample (S43), simultaneously provides the samples with the changed conditions to the owners and/or members of multiple communities including the community to which the persona belongs (S44), and analyzes and evaluates the responses from each community (S45). The information processing device 1 creates marketing or branding content tailored to the individuality of the community determined to be satisfied or dissatisfied based on, for example, the registered information in the POC information DB 25 and a specified format (S46), and saves (registers) this as the result of the fourth hypothesis processing (S47).

As explained above, the information processing device 1 of this embodiment acquires the chronological behavioral details of the owner and members based on the behavioral policy of each community, analyzes the behavioral policy and behavioral details to individualize the analysis results for each community, and analyzes the interest prediction value for target content (e.g., content related to candidate business items) for each community based on the analysis results. Then, one or more communities are selected according to the analysis results, and the target content is presented to the selected one or more communities, while qualitatively or quantitatively evaluating changes in the behavioral details of the community resulting from the presentation. Therefore, it is possible to provide a community platform technology that facilitates marketing that flexibly responds to the fluidity of market needs for business items.

In the above operating mode, an example of facilitating POC has been described, but the same procedure can also be applied to test marketing processing or fan marketing processing. Also, in the above operating mode, an example of content when product set rental is used as the target content has been described, but the same can be applied to other business items, such as food, clothing, daily necessities, or financial products and funds.

1: Information processing device, 11: Communication control unit, 12: Registration unit, 13: Information acquisition unit, 14: Analysis unit, 15: Analysis unit, 16: Management unit, 17: Evaluation unit, 18: Information presentation unit, 19: Main control unit, 21: Community DB, 22: Owner DB, 23: Member DB, 24: Content DB, 25: POC information DB.

Claims (7)

An information processing device that provides a dedicated platform for a plurality of communities, each of which has an owner and members, on a computer network, comprising:
an acquisition means for acquiring the chronological behavioral details of the owner and the members based on a behavioral policy for each community, the owner attributes of the owner, and the member attributes of the members ;
an analysis means for analyzing the course of action, the owner attributes, the member attributes, and the actions of the owner and the members acquired in time series, and for grouping, subdividing , or hierarchizing the community, the owner, and the members according to a predetermined criterion to classify them into new communities according to the analysis results;
A management means for storing the new classified community as a new destination of the platform;
An information processing device comprising: The course of action is associated with the value that the owner wants to give to the community and the owner's behavioral history in the community.
The information processing device according to claim 1 . the management means associates owners corresponding to each owner attribute with each other when a plurality of owner attributes are similar to each other based on a predetermined criterion;
The information processing device according to claim 1 . the management means associates members corresponding to each member attribute with each other when a plurality of member attributes are similar to each other based on a predetermined criterion;
The information processing device according to claim 1 . and an evaluation means for qualitatively or quantitatively evaluating a change in the behavior of a community with respect to a predetermined target content when the target content is presented to the community.
The information processing device according to claim 1 . The target content is content related to one or more hypotheses created or revised to predict the business feasibility of a potential business item, a product, a service, or a combination of products and services;
The information processing device according to claim 5 . A computer program that causes a computer having a communication function to operate as the information processing device according to claim 1.

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