Information processing device and information processing method

Abstract

To realize data distribution that enhances user satisfaction.SOLUTION: An information processing device according to one embodiment of the present disclosure includes: a type information acquisition unit that acquires type information in which customers of each service provided by each of a plurality of business operators are classified, the type information being classified according to diversity possessed by the customers; a linking information acquisition unit that acquires linking information in which customer information regarding the use of the service provided by a specific business operator among the plurality of business operators is linked to the type information in which the customers of the service are classified; an integration unit that integrates, from among the linking information, pieces of the customer information having the identical or similar type information; and a provision unit that provides the integrated information, which is the integrated pieces of the customer information, to the requesting business operator.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an information processing device and an information processing method. [Background technology]

[0002] Conventionally, there have been many efforts to classify customers into a certain type (so-called persona, etc.) based on information about the customers, and to utilize the results of the classification in marketing business, etc.

[0003] For example, in the information processing system described in Patent Document 1, customers are classified into predetermined types based on customer information related to personal information of the customers, information on services used, and the like. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-105868 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the above-mentioned conventional technology merely classifies customers into predetermined types based on customer information, and there is room for improvement in terms of realizing data distribution that increases user satisfaction.

[0006] Therefore, the present invention proposes an information processing device, an information processing method, and an information processing program that are capable of achieving data distribution that enhances user satisfaction. [Means for solving the problem]

[0007] In order to solve the above problems, one form of information processing device according to the present invention is characterized in having a type information acquisition unit that acquires type information into which customers of each service provided by each of a plurality of businesses are classified, the type information being classified according to the diversity possessed by the customers; a linking information acquisition unit that acquires linking information that links customer information regarding the use of a service provided by a specific business among the plurality of businesses with the type information into which customers of the service are classified; an integration unit that integrates customer information among the linking information, the type information of which matches or is similar; and a provision unit that provides the integrated information, which is the integrated customer information, to the business that requested the request. Effect of the Invention

[0008] According to the present invention, data distribution that increases user satisfaction can be realized. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is an explanatory diagram for explaining an overview of the present invention. [Diagram 2] FIG. 2 is a diagram showing an example of various personas that a user has. [Diagram 3] FIG. 3 is a diagram illustrating an example of a system according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an overall view of information processing according to the embodiment. [Diagram 5] FIG. 5 is a conceptual diagram showing an example of how integrated information is used. [Figure 6] FIG. 6 is a diagram illustrating an example of a configuration of a platform management device according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a persona information storage unit according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of the integration data storage unit according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of the accumulation data storage unit according to the embodiment. [Figure 10]FIG. 10 is a diagram showing a specific example of the integration process according to the embodiment. [Figure 11] FIG. 11 is a flowchart showing the procedure of the integration process executed by the platform management device. [Figure 12] FIG. 12 is a block diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0011] One or more embodiments (including examples, modifications, and application examples) described below can be implemented independently. Meanwhile, at least a part of the embodiments described below may be implemented in appropriate combination with at least a part of another embodiment. These embodiments may include novel features different from each other. Thus, these embodiments may contribute to solving different purposes or problems and may provide different effects.

[0012] (Embodiment) 1. Overview First, an overview of the present invention will be described with reference to Fig. 1. Fig. 1 is an explanatory diagram for explaining the overview of the present invention.

[0013] Recently, with the advancement of IT technology, provision of information personalized to each user has become widespread. For example, Fig. 1(a) shows an example of a conventional marketing method. According to Fig. 1(a), in a conventional marketing method, a business such as a company collects historical information (e.g., behavioral history) and personal information of users, and takes action against users based on assumptions (e.g., user segment A is interested in XX / user segment B is interested in XX) obtained by analyzing the collected information.

[0014] However, in the conventional marketing method, for example, content that the user is not interested in may be displayed, and the user may feel that his / her actions are being tracked by the company. In other words, the conventional marketing method has a problem that it makes the user feel uncomfortable and does not adequately protect the privacy of the user.

[0015] One of the causes of these problems is that conventional methods are company-driven (companies take the lead). For example, in conventional methods, companies can classify users into specific types based on information such as the user's behavior and provide content related to those types, but there is room for improvement in understanding the individuality and diversity of users and taking actions that are tailored to the user. In this way, in a situation where individual diversity is becoming more and more important in society as a whole, company-driven personalization is becoming less acceptable, and it is also difficult for companies to properly understand the diversity of their users.

[0016] Furthermore, it is difficult for conventional methods to respond to the situation where users are becoming more conscious of privacy issues. For example, users may have doubts about whether their personal information is being stolen while using the Internet, and conventional methods have room for improvement in this regard as well.

[0017] As mentioned above, conventional methods do not necessarily realize the distribution of data that increases user satisfaction. For example, "well-being" is known as a concept that means people are in a good physical, mental, and social condition, i.e., in a happy state, but conventional methods do not necessarily realize the distribution of data that increases user well-being.

[0018] Therefore, in this invention, in order to utilize valuable personal data, we propose a new marketing method to replace conventional methods, which can increase customer satisfaction in both the utilization of personal data and well-being. For example, this invention proposes a new personalization method based on data distribution with sufficient consideration for privacy, and premised on a shift from corporate-led to user-led personalization.

[0019] In this way, the present invention aims to extract, for example, the diversity within a group or the diverse needs within an individual, and to propose information according to these needs, rather than judging a user by their attributes. In other words, the present invention differs from conventional methods in that it does not treat a user simply as an "individual," but instead focuses on the user's "persona," shifting the focus to user-driven personalization.

[0020] For example, the platform PF according to the present invention acts as an information bank that realizes new personalization based on personas and acts as an intermediary between businesses. In addition, well-being indicators are incorporated into this information bank. With the platform PF incorporating well-being indicators, the information bank will have a wealth of data on places, stores, individuals, etc., and as a result, member businesses will be able to carry out marketing that captures the situation in a comprehensive manner.

[0021] First, the information processing realized by the platform PF according to the present invention (information processing according to the embodiment) will be briefly described with reference to FIG.

[0022] In the information processing according to the embodiment, an information bank that makes use of the diversity of individuals is used to propose services based on the user's "desired self." For example, in the information processing according to the embodiment, a "persona diagnosis" is performed on the user by incorporating well-being indicators into the information bank, and customer information provided by each business is integrated using persona information that is the result of the diagnosis. Specifically, the persona information includes persona classification as typological information classified according to the diversity possessed by the user.

[0023] Therefore, in the information processing according to the embodiment, unique customer information held by a certain business and unique customer information held by another business are integrated in a privacy-protected state based on this persona classification, and the integrated information obtained by the integration is provided to the business. The business can realize user-driven personalization by analyzing this integrated information. For example, the business can provide content that meets the potential needs of the user.

[0024] [2. About Persona] Next, personas will be described with reference to Fig. 2. Fig. 2 is a diagram showing examples of various personas that users have. According to Fig. 2, a user does not have a uniform "personality," and even a single user has various "personalities," such as the persona at work and the persona in front of family members.

[0025] Furthermore, as shown in FIG. 2, for example, in addition to the actual "self," a user also has a "self" that is in relation to an ideal self, such as the ideal self at work or the self they want to be in front of their family. These various aspects that a user possesses, that is, "self," are called "personas." Also, users divided into different personas are called "dividuals." For example, even for the same user, a user who is in persona classification A can be called dividual X, and a user who is in persona classification B can be called dividual Y. Note that the personas shown in FIG. 2 are merely examples, and personas may be various types that classify users, that is, people.

[0026] As explained in Fig. 2, a user naturally adopts different personalities depending on the environment and time axis, for example, when at work, at home, in a network environment, etc. This differentiation is called a "division," and personal data corresponding to the division is managed in an information bank. Therefore, the platform PF according to the present invention allows for a deeper and more layered expression of individuality and diversity, enabling businesses to provide services that realize natural humanness in the cyber world in the real world, which is believed to lead to improved well-being.

[0027] 3. System Configuration Fig. 3 is a diagram showing an example of a system according to an embodiment. Fig. 1 shows a system 1 as an example of a system according to an embodiment. Information processing according to the embodiment is realized in the system 1.

[0028] 3, the system 1 includes a customer device 10, a business operator device 30, and a platform management device 100. The customer device 10, the business operator device 30, and the platform management device 100 are connected to each other via a network N so as to be able to communicate with each other via wired or wireless communication. The system 1 may include any number of customer devices 10 and any number of business operator devices 30.

[0029] The customer device 10 is an information processing terminal used by a customer U (user) of any of the businesses participating in the services of the platform PF, and corresponds to an edge computer. For example, the customer device 10 is a smartphone, a wearable device, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. The customer U can use the customer device 10 to receive a persona diagnosis.

[0030] The business operator device 30 is a server device that realizes services provided by a business operator (company) and corresponds to a cloud computer. For example, the business operator device 30 manages various information obtained when the business operator's services are used by a customer U, by linking the information to an account ID (customer ID). For example, the business operator device 30 manages customer information including customer attribute information and service specific information.

[0031] In addition, the business operator device 30 has a function of generating linking information in which statistical information is linked on a persona classification basis (based on the persona classification) by statistically processing customer information of customers U belonging to each persona classification into which customers U who use the company's services are classified.

[0032] The platform management device 100 is a server device that realizes information processing according to the embodiment, and corresponds to a cloud computer. The platform management device 100 corresponds to a platform PF having a function as an information bank that makes use of the diversity of individuals, and has a role of, for example, mediating data exchange between businesses. The platform management device 100 provides a service that performs information processing and information provision for businesses to realize user-driven personalization. In other words, the platform management device 100 provides a service that supports businesses so that they can carry out marketing that captures situations in a comprehensive manner.

[0033] In addition, the business operator who has the right to manage and maintain the platform management device 100 is a separate organization from the business operators who join the platform PF and seek to receive the above-mentioned support, and is a company that seeks to do new business using the platform PF's services.

[0034] [4. Overview of Information Processing] Next, an overview of information processing realized by the platform PF will be described using an example of business-to-business transactions via the platform PF. FIG. 4 is a diagram showing an overview of information processing according to an embodiment. In the following embodiment, "linking information" can be understood as statistical information in which customer information is statisticalized on a persona-by-persona basis, that is, "persona-based statistical information." Furthermore, "statistical information" provided by a business (business device 30) refers to "persona-based statistical information."

[0035] In addition, in the services provided by the platform PF, operators have the following behavioral patterns:

[0036] (i) An operator provides statistical information generated by the operator (the operator's device 30) to the platform management device 100 as data for integration, and requests integration of the statistical information generated by other operators on the basis of persona classification. At this time, the operator can set integration conditions for the statistical information of other operators to be integrated with the operator's statistical information. For example, the operator can set the provider of the statistical information to be integrated with the operator's statistical information (individual would like to be integrated with statistical information of company X), the service type of the statistical information to be integrated with the operator's statistical information (individual would like to be integrated with statistical information based on customer information of service X), or the period covered by the statistical information to be integrated with the operator's statistical information (individual would like to be integrated with statistical information based on customer information for a period XY), etc. Thus, the platform management device 100 performs data integration according to the integration conditions.

[0037] (ii) A business entity provides statistical information generated by the business entity (the business entity device 30) to the platform management device 100 as data for storage, thereby allowing other business entities to sell the statistical information of the business entity to purchase the information. In other words, the business entity provides the statistical information of the business entity to the platform management device 100 for the purpose of selling the information.

[0038] (iii) An enterprise does not provide its own statistical information as data for integration or storage to the platform management device 100, but purchases statistical information that it wishes to utilize for its own marketing analysis from among the statistical information provided by other enterprises as data for storage. In other words, an enterprise accesses the platform management device 100 for the purpose of purchasing statistical information of other enterprises.

[0039] (iv) The business operator requests the platform management device 100 to analyze (estimate) the persona classification of the customer U by conducting a persona diagnosis of the customer U who uses the business operator's services.

[0040] (v) A business operator does not necessarily need to conduct a persona diagnosis of customer U who uses its services.

[0041] (vi) An enterprise falling under (iv) above may be in any of the following positions: (i) to (iii).

[0042] (vii) The business entity in (v) above may be in any of the following positions: (i) to (iii).

[0043] Here, Fig. 4 shows an example of a business operator that is a member of the platform PF, which is a business operator C1 (C1 company) that provides "service SA1" and a business operator C2 (C2 company) that provides "service SA2." Also, in the example of Fig. 4, an example of information processing in which C1 company is in a state where (iii) and (iv) are combined, and C2 company is in a state where (ii) and (iv) are combined, is shown.

[0044] Specifically, in the example of FIG. 4, company C1 requests a persona diagnosis for customer U1 who uses its service SA1, and plans to perform its own marketing analysis based on the diagnosis results and the linking information purchased from company C2. Meanwhile, in the example of FIG. 4, company C2 requests a persona diagnosis for customer U2 who uses its service SA2, and provides the linking information generated by the company to the platform management device 100 as data to be stored. Details of information processing in this example are described below. When there is no need to distinguish between customer U1 and customer U2, they will simply be referred to as customer U. Also, both customer U1 and customer U2 are not a single person, but are composed of multiple people.

[0045] 4 shows an example in which a persona diagnosis is performed for each customer U1 of company C1 and for each customer U2 of company C2 via the customer device 10 (step S1). In this case, the platform management device 100 acquires information on the persona diagnosis from the customer device 10 (step S2).

[0046] Diversity includes the individual's innate personality (such as race and age), characteristics that change depending on the environment (such as hobbies and beliefs), and role in an organization (such as place of work and employment type), and in the persona diagnosis, questions related to these may be provided. For example, the persona diagnosis may be conducted in a Q&A format regarding emotional or theoretical, conservative or innovative, dog person or cat person, music lover or art lover, etc., and the platform management device 100 acquires persona diagnosis information including the answers of customer U. For this reason, the information on the diversity of customer U obtained by persona diagnosis can be said to be information used to estimate the persona classified as customer U.

[0047] Furthermore, the platform management device 100 may provide the business operator device 30 with a persona diagnosis format (Q&A format) to allow the business operator device 30 to carry out persona diagnosis at any timing and in any medium. Therefore, for example, the business operators C1 and C2 can freely implement measures such as increasing the number of respondents by carrying out persona diagnosis as a point campaign.

[0048] When the platform management device 100 acquires the information of the persona diagnosis, it performs an analysis process to estimate a persona classification, which is a type of persona, for each customer U based on the information of the persona diagnosis, and returns the analysis results to companies C1 and C2 (step S3). Specifically, the platform management device 100 returns the persona classification classified for each customer U1 as the analysis result to company C1 in a state in which the persona classification is associated with, for example, a customer ID. In addition, the platform management device 100 returns the persona classification classified for each customer U2 as the analysis result to company C2 in a state in which the persona classification is associated with, for example, a customer ID.

[0049] According to the example of Figure 4, the business operator device 30-2 of Company C2 holds a purchasing history for each customer U2, and manages the persona classification returned from the platform management device 100 and the purchasing history by linking them, for example, based on a customer ID that identifies customer U2 (step S4).

[0050] In this state, the business operator device 30-2 extracts a purchase history for each persona classification (that is, with the persona classification as an axis), and links the extracted purchase history to the persona classification that is the axis (step S5).

[0051] Then, the business operator device 30-2 performs statistical processing on the purchase history linked to each persona classification (step S6). The statistical processing is performed for the purpose of protecting privacy. As a result of the statistical processing, the business operator device 30-2 can generate persona-based purchasing tendency data in which purchasing tendencies are linked by persona classification unit, as shown in FIG. 4. The persona-based purchasing tendency data is an example of customer information according to the embodiment, and a specific example thereof is "people in persona classification A tend to like craft beer." Although not shown in FIG. 4, the business operator device 30-2 can also generate statistical information for other persona classifications (e.g., persona classification B) classified for customer U2, which are statistically processed by persona classification unit.

[0052] The persona-based purchasing tendency data is shared between the business operator device 30-2 and the platform management device 100 (step S7). Specifically, the business operator device 30-2 provides the persona-based purchasing tendency data to the platform management device 100. The persona-based purchasing tendency data is held in the platform management device 100 as data to be accumulated for the purpose of selling to other business operators different from the business operator device 30-2.

[0053] Here, it is assumed that the platform management device 100 receives from company C1 a request to purchase the persona-based purchasing tendency data generated by company C2. In this case, the persona-based purchasing tendency data provided by business operator device 30-2 is linked between the platform management device 100 and business operator device 30-1 (step S8). Specifically, the platform management device 100 transmits the persona-based purchasing tendency data to business operator device 30-1. The persona-based purchasing tendency data is held as external input data in business operator device 30-1.

[0054] In addition, since the business operator device 30-1 holds customer information (e.g., personal information) for each customer U1, the business operator device 30-1 may manage the persona classification returned from the platform management device 100 and the customer information by linking them together, for example, based on a customer ID that identifies customer U1.

[0055] Then, the business device 30-1 extracts customer information that matches or is similar to the persona classification to be used for linking between the customer information it has and the persona-based purchasing tendency data provided by the business device 30-2, and integrates the extracted customer information and the persona-based purchasing tendency data in units of the persona classification to be used (step S9).

[0056] For example, suppose that the persona classification used to link customer information is the persona classification of customer U1, which includes persona classification A and persona classification C. Meanwhile, the persona classification used to link persona-based purchasing tendency data provided by business operator device 30-2 is the persona classification of customer U2, which includes persona classification A and persona classification B. In this case, since persona classification A matches between the customer information and the persona-based purchasing tendency data, business operator device 30-1 integrates the customer information linked to persona classification A and the persona-based purchasing tendency data linked to persona classification A on a persona classification A basis.

[0057] Since the business operator device 30-1 can generate integrated information by integrating its own customer information with the persona-based purchasing tendency data of company C2 in units of persona classification A, the business operator device 30-1 may further perform statistical processing on the part of its own customer information in the integrated information (step S10). This statistical processing is also performed for the purpose of protecting privacy.

[0058] For example, if the statistical customer information indicates that "people of persona classification A tend to like Tokyo Tower," then, in combination with the statistical information from company C2, it becomes possible to arrive at a measure such as "recommending a shop where you can drink craft beer at Tokyo Tower to people of persona classification A." In this way, according to the information processing of the embodiment, company C1 can utilize data to enhance the well-being of users, unlike when simply using demographic attributes, for example.

[0059] 4 shows an example in which data integration is performed on the business entity device 30-1 side as described in step S9, but data integration may be performed on the platform management device 100 side. A case in which data integration is performed on the platform management device 100 side will be described later.

[0060] [5. Examples of use of integrated information] Next, an example of how the integrated information is used will be described with reference to Fig. 5. Fig. 5 is an image diagram showing an example of how the integrated information is used. The example in Fig. 5 shows a scene in which the persona classification used for linking between the statistical information provided by the business device 30-1 (persona-based statistical information in which customer information is statisticalized on a persona-by-persona basis) and the statistical information provided by the business device 30-2 (persona-based statistical information in which purchasing history is statisticalized on a persona-by-persona basis) matches at "persona classification A."

[0061] In addition, by statistically analyzing the customer information linked to persona classification A, it is possible to obtain a tendency that "people of persona classification A like Tokyo Tower," and by statistically analyzing the historical information linked to persona classification A, it is possible to obtain a tendency that "people of persona classification A like craft beer."

[0062] In such a case, company C1 can implement measures such as "opening a shop where you can drink rare craft beer while looking at Tokyo Tower for one week only, and recommending it to people who have persona classification A for both company C1 and company C2" and conduct marketing analysis. Also, company C2's business operator can implement measures such as "opening a shop where you can drink rare craft beer while looking at Tokyo Tower for one week only, and recommending it to people who have persona classification A for both company C2 and company C1".

[0063] 6. Configuration of Platform Management Device The platform management device 100 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram showing a configuration example of the platform management device 100 according to the embodiment. As shown in Fig. 6, the platform management device has a communication unit 110, a storage unit 120, and a control unit 130.

[0064] (Regarding communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC) etc. For example, the communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information between the customer device 10 and the business device 30.

[0065] (Regarding the storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk, an optical disk, etc. The storage unit 120 has a persona information storage unit 121, an integration data storage unit 122, and an accumulation data storage unit 123.

[0066] (Persona information storage unit 121) The persona information storage unit 121 stores persona classifications and the like as analysis results for persona diagnosis information (including customer U's answers to questions). Here, Fig. 7 shows an example of the persona information storage unit 121 according to the embodiment. In the example of Fig. 7, the persona information storage unit 121 has items such as "business operator ID", "service ID", "customer ID", "persona configuration information", and "persona classification".

[0067] The "business operator ID" is identification information that identifies a business operator that is a member of the platform PF. The "service ID" is identification information that identifies a service provided by the business operator indicated by the "business operator ID." The "customer ID" is identification information that identifies a customer U who uses the service indicated by the "service ID."

[0068] The "persona configuration information" includes, as information on the persona diagnosis, the answers, items, values, etc. of the customer U. The "persona classification" indicates the persona classification estimated for the customer U by analyzing the information on the persona diagnosis.

[0069] FIG. 7 shows an example in which a customer U11 who uses a service SA1 of a business operator C1 is classified into persona classification A by analyzing persona configuration information CF11 obtained from the customer U11 through a persona diagnosis of the customer U11.

[0070] (Integration data storage unit 122) The integration data storage unit 122 stores statistical information to be used for integration with statistical information of other operators. Fig. 8 shows an example of the integration data storage unit 122 according to the embodiment. In the example of Fig. 8, the integration data storage unit 122 has items such as "operator ID", "service ID", "integration conditions", and "linking information". Furthermore, the "linking information" includes items such as "persona classification" and "statistical information".

[0071] "Provider ID" is identification information that identifies a provider that is a member of the Platform PF and has requested to integrate the statistical information it has generated with that of other providers. The provider indicated by the "Provider ID" can set the "integration conditions." "Service ID" is identification information that identifies the service provided by the provider indicated by the "Provider ID."

[0072] The "integration condition" indicates condition information that conditions the statistical information of other operators to be integrated with the statistical information generated by the operator. As described above, the operator can set, as the "integration condition", for example, the operator that provides the statistical information to be integrated with the operator's statistical information, the service type of the statistical information to be integrated with the operator's statistical information, or the period covered by the statistical information to be integrated with the operator's statistical information.

[0073] Also, in the example of FIG. 8, in the "association information", "statistical information" is associated with each "persona classification" using the "persona classification" as the linking axis. The "persona classification" used here is the persona classification estimated for customer U by analyzing the information of the persona diagnosis, and is the same as that in FIG. 7. Also, the "statistical information" is information obtained by statisticizing existing data that the business operator indicated by the "business operator ID" possesses in advance by providing the service indicated by the "service ID". The existing data referred to here is, for example, customer information (e.g., attribute information and history information of customer U) accumulated by customer U using the service indicated by the "service ID".

[0074] 8 shows an example in which company C1 (business operator device 30 of company C1) generates linking information in which statistical information SDA11 is linked to persona classification A by statisticalizing customer information of customer U1 belonging to persona classification A. Also shown is an example in which company C1 (business operator device 30 of company C1) provides this linking information to the platform management device 100 as data for integration together with integration condition #11.

[0075] (Accumulation data storage unit 123) The accumulation data storage unit 123 stores the linking information provided by the business operator for the purpose of sales. The accumulation data storage unit 123 stores the linking information for the purpose of sales. FIG. 9 shows an example of the accumulation data storage unit 123 according to the embodiment. In the example of FIG. 9, the accumulation data storage unit 123 has items such as "business operator ID", "service ID", "sales destination conditions", and "linking information". Furthermore, the "linking information" includes items such as "persona classification" and "statistical information".

[0076] "Business ID" is identification information that identifies a business that is a member of the platform PF and has requested that the statistical information generated by the business be stored for the purpose of selling it to other businesses. The business indicated by the "Business ID" can set "Integration Conditions." "Service ID" is identification information that identifies the service provided by the business indicated by the "Business ID."

[0077] The "Sales Conditions" indicate the content that the business operator indicated by the "Business Operator ID" permits as a sales destination of its statistical information. The "Linking Information" consisting of the "Persona Classification" and "Statistical Information" is the same as that in Figure 8, so the explanation is omitted here.

[0078] 8 shows an example in which company C1 (business operator device 30 of company C1) generates linking information in which statistical information SDA11 is linked to persona classification A by statisticalizing customer information of its own customers U belonging to persona classification A. Also shown is an example in which company C1 (business operator device 30 of company C1) provides this linking information to the platform management device 100 as data for sales, together with buyer conditions #11.

[0079] (Regarding the control unit 130) 6, the control unit 130 is realized by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like executing various programs (for example, an information processing program according to the embodiment) stored in a storage device inside the platform management device 100 using a RAM as a working area. The control unit 130 is also realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0080] As shown in Fig. 6, the control unit 130 has a response acquisition unit 131, an estimation unit 132, a persona information acquisition unit 133, a linking information acquisition unit 134, an integration unit 135, and a provision unit 136, and realizes or executes the functions and actions of information processing described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Fig. 6, and may be other configurations as long as they perform information processing described below. Also, the connection relationship between the processing units of the control unit 130 is not limited to the connection relationship shown in Fig. 6, and may be other connection relationships.

[0081] (Answer acquisition unit 131) The answer acquisition unit 131 acquires answer information input by the customer U to questions in the persona diagnosis. For example, the answer acquisition unit 131 acquires answer information input using the customer device 10, and registers the answer information in the persona information storage unit 121 as one piece of persona configuration information.

[0082] (Estimation part 132) The estimation unit 132 estimates the persona classification of each customer U of each service provided by each business operator based on answer information input by the customer U to questions in the persona diagnosis. That is, the estimation unit 132 analyzes the answer information and classifies the customer U of each service provided by each business operator into a specific persona based on the analysis result. In addition, the estimation unit 132 registers information on the estimated persona classification in the persona information storage unit 121.

[0083] (Persona information acquisition unit 133) The persona information acquisition unit 133 acquires persona information including the persona classification estimated by the estimation unit 132. For example, the persona information acquisition unit 133 acquires persona information necessary for the current integration process from the persona information storage unit 121, and outputs the persona information to the integration unit 135.

[0084] (Linking information acquisition unit 134) The linking information acquisition unit 134 acquires linking information from the business operator, including statistical information obtained by statistically processing customer information accumulated by using a service provided by the business operator according to a persona classification classified for a customer U of the service. Specifically, the linking information acquisition unit 134 acquires statistical information obtained by statistically processing, by the business operator device 30, customer information of the customer U belonging to the persona classification for each persona classification. More specifically, the linking information acquisition unit 134 acquires statistical information obtained by statistically aggregating customer information with the persona classification as an axis, and in a state of being linked to the persona classification as an axis. That is, when the linking information generated by the business operator device 30 is provided from the business operator device 30, the linking information acquisition unit 134 acquires the provided linking information.

[0085] In addition, when the linking information is provided as data for integration, the linking information acquisition unit 134 registers it in the data for integration storage unit 122, and when the linking information is provided as data for accumulation, the linking information acquisition unit 134 registers it in the data for accumulation storage unit 123.

[0086] (Integrated Section 135) The integration unit 135 integrates the linking information acquired by the linking information acquisition unit 134, which is provided by different businesses and has the same or similar persona classification of the target used for linking, on a per-persona classification basis.

[0087] For example, when an integration request including the linking information provided by a business operator as an integration condition is received from the business operator, the integration unit 135 extracts statistical information provided by other business operators that has the same or similar type information of the target of use as the statistical information provided by the business operator.The integration unit 135 then generates integrated information by integrating the extracted statistical information of the other business operators with the statistical information provided by the requesting business operator.

[0088] (Providing Department 136) The providing unit 136 provides the integrated information generated by the integrating unit 135 to the requesting business operator. The providing unit 136 also provides the linking information provided by the seller business operator to other businesses different from the seller business operator so that the linking information can be purchased. The providing unit 136 also provides the requesting business operator with the persona classification corresponding to the customers of the service provided by the requesting business operator, out of the persona classifications estimated by the estimation unit 132.

[0089] [7. Specific examples of integration processing] Fig. 10 is a diagram showing a specific example of the integration process according to the embodiment. Fig. 10 also shows an example of a business operator affiliated with the platform PF, which is a business operator C1 (C1 company) that provides "service SA1" and a business operator C2 (C2 company) that provides "service SA2". However, in the example of Fig. 10, the behavior patterns of both C1 and C2 companies are a combination of (i) and (iv) described at the beginning of Fig. 4.

[0090] Specifically, in the example of Fig. 10, company C1 requests a persona diagnosis for customer U1 who uses its service SA1 (assumed to be a payment service), and also requests that the statistical information generated by company C2 be integrated with the statistical information generated by company C1. Company C2 also requests a persona diagnosis for customer U2 who uses its service SA2 (assumed to be an M2E service), and also requests that the statistical information generated by company C2 be integrated with the statistical information generated by company C1.

[0091] First, the data structure of the business operator device 30-1 of company C1 will be described. The business operator device 30-1 holds customer information UDA1 as a result of the service SA1 being used by customer U1. In the customer information UDA1, attribute information of customer U1 and service specific information are associated with a customer ID. The attribute information of customer U1 includes personal information such as name, address, age, and occupation. The service specific information is unique information that is accumulated according to the use of service SA1, and includes payment history in the example of FIG. 10.

[0092] Furthermore, the business operator device 30-1 acquires persona information PDA1 including a persona classification for each customer U1 from the platform management device 100 as an analysis result of the persona diagnosis. The persona information PDA1 includes persona classification information and persona configuration information. FIG. 10 shows, as a simple example, an example in which the persona information PDA1 includes persona classification A and persona classification C. That is, in FIG. 10, each customer U1 is classified into either persona classification A or persona classification C.

[0093] In this example, the business operator device 30-1 uses the customer ID of the customer U1 belonging to persona classification A to extract the payment history of each customer U1 belonging to persona classification A, and performs statistical processing on the extracted payment history while linked to persona classification A. Also, the business operator device 30-1 uses the customer ID of the customer U1 belonging to persona classification C to extract the payment history of each customer U1 belonging to persona classification C, and performs statistical processing on the extracted payment history while linked to persona classification C. As a result of these statistical processes, the business operator device 30-1 can generate linking information LDA1.

[0094] For example, the business operator device 30-1 can generate linking information LDA11 (persona-based payment tendency data) in which payment tendencies are linked in units of persona classification A. The business operator device 30-1 can also generate linking information LDA12 (persona-based payment tendency data) in which payment tendencies are linked in units of persona classification C.

[0095] Fig. 10 illustrates an example of the data structure of linked information LDA11 corresponding to persona classification A. According to the example of Fig. 10, in linked information LDA11, information that cannot identify an individual (statistical information SDA111) of customer information UDA1 and service-specific information (statistical information SDA112) of customer information UDA1 are linked to persona classification A.

[0096] The statistical information SDA111 is information that has been processed to make it impossible to identify individuals by statisticalizing attribute information (such as name, address, age, and occupation) of customer U1 who belongs to persona classification A. The statistical information SDA112 is information that has been processed to make it impossible to identify individuals by statisticalizing the payment history of customer U1 who belongs to persona classification A.

[0097] In addition, the linking information LDA12 corresponding to persona classification C has a similar data structure, so its explanation is omitted.

[0098] 10, the business operator device 30-1 provides the linking information LDA1 (linking information LDA11, linking information LDA12) to the platform management device 100. Therefore, the linking information acquisition unit 134 of the platform management device 100 acquires the linking information LDA1.

[0099] Next, the data structure of the business operator device 30-2 of company C2 will be described. The business operator device 30-2 holds customer information UDA2 as a result of the service SA2 being used by customer U2. In the customer information UDA2, attribute information of customer U2 and service specific information are associated with a customer ID. The attribute information of customer U2 includes personal information such as residential area, height, age, etc. The service specific information is unique information that is accumulated in response to the use of service SA2, and in the example of FIG. 10, includes a location history including the number of steps.

[0100] Furthermore, the business operator device 30-2 acquires persona information PDA2 including a persona classification for each customer U2 from the platform management device 100 as an analysis result of the persona diagnosis. The persona information PDA2 includes persona classification information and persona configuration information. FIG. 10 shows, as a simple example, an example in which the persona information PDA2 includes persona classification A and persona classification B. That is, in FIG. 10, each customer U2 is classified into either persona classification A or persona classification B.

[0101] In this example, the business operator device 30-2 uses the customer ID of the customer U2 belonging to persona classification A to extract the location history of each customer U2 belonging to persona classification A, and performs statistical processing on the extracted location history in a state linked to persona classification A. The business operator device 30-2 also uses the customer ID of the customer U2 belonging to persona classification B to extract the location history of each customer U2 belonging to persona classification B, and performs statistical processing on the extracted location history in a state linked to persona classification B. As a result of these statistical processes, the business operator device 30-2 can generate association information LDA2.

[0102] Fig. 10 illustrates an example of the data structure of linked information LDA21 corresponding to persona classification A. According to the example of Fig. 10, in linked information LDA21, non-personally identifiable information (statistical information SDA211) of customer information UDA2 and service specific information (statistical information SDA212) of customer information UDA2 are linked to persona classification A.

[0103] The statistical information SDA211 is information that has been processed to a state in which an individual cannot be identified by statistically converting attribute information (residential area, height, age, etc.) of the customer U2 who belongs to persona classification A. The statistical information SDA212 is information that has been processed to a state in which an individual cannot be identified by statistically converting the location history of the customer U2 who belongs to persona classification A.

[0104] In addition, the linked information LDA22 corresponding to persona classification B has a similar data structure, so its explanation is omitted.

[0105] 10, the business entity device 30-2 provides the association information LDA2 (association information LDA21, association information LDA22) to the platform management device 100. Therefore, the association information acquisition unit 134 acquires the association information LDA2.

[0106] The integration unit 135 of the platform management device 100 performs an integration process of integrating the association information LDA1 and the association information LDA2 by using the persona classification.

[0107] Here, in the example of FIG. 10, the persona classifications of the target users used for the association in the association information LDA1 are persona classifications A and C. On the other hand, the persona classifications of the target users used for the association in the association information LDA2 are persona classifications A and B. Therefore, the integration unit 135 compares the persona classifications A and C of the target users on the C1 side with the persona classifications A and B of the target users on the C2 side to determine whether there are matching or similar persona classifications between the two. In the example of FIG. 10, the integration unit 135 can determine that persona classification A exists as a matching persona classification between the C1 company and the C2 company.

[0108] The integration unit 135 uses the persona classification A that matches between companies C1 and C2 as a data extraction key to extract linking information LDA11 linked to persona classification A and linking information LDA21 linked to persona classification A from the integration data storage unit 122.

[0109] Then, the integration unit 135 integrates the associated information LDA11 and the associated information LDA21 based on the persona classification A. Specifically, the integration unit 135 integrates the statistical information SDA112 corresponding to the service specific information and the statistical information SDA212, and integrates the statistical information SDA111 corresponding to the information that does not identify an individual and the statistical information SDA211, based on the persona classification A. As a result, the integration unit 135 can generate integrated information X based on the persona classification A.

[0110] In addition, the providing unit 136 of the platform management device 100 provides the generated integrated information X to each of companies C1 and C2. As a result, companies C1 and C2 can combine the integrated information X with information collected by their own companies, for example, and utilize it for marketing analysis, etc.

[0111] 8. Processing Procedure Next, the operation procedure of the platform management device 100 will be described with reference to Fig. 11. Fig. 10 is a flowchart showing the integration process executed by the platform management device 100.

[0112] First, the association information acquisition unit 134 determines whether or not an integration request has been received from the business operator (step S1101). If an integration request has not been received from the business operator (step S1101; No), the association information acquisition unit 134 waits until it can be determined that an integration request has been received from the business operator.

[0113] On the other hand, when the linking information acquisition unit 134 receives an integration request from an operator (step S1101; Yes), it acquires the linking information provided by the requesting operator that made the integration request as the linking information to be used for the integration (step S1102).

[0114] Furthermore, the linking information acquisition unit 134 acquires linking information provided by businesses other than the requesting business that is conditioned by the integration conditions defined by the requesting business (step S1103).

[0115] Next, the integration unit 135 extracts the persona classification of the target used for linking in the linking information (step S1104). Specifically, the integration unit 135 extracts the persona classification of the target used in the linking information provided by the requesting business and the persona classification of the target used in the linking information provided by other businesses that satisfy the integration conditions.

[0116] The integration unit 135 determines whether or not there is an identical persona classification between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side (step S1105). For example, the integration unit 135 performs an identical determination between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side.

[0117] When the integration unit 135 determines that the same persona classification exists between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side (step S1105; Yes), it extracts the linking information having the same persona classification as the linking unit from the linking information of both business companies (step S1106). For example, if the persona classification A matches between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side, the integration unit 135 extracts the linking information obtained in step S1102 that has persona classification A as the linking unit. In addition, the integration unit 135 extracts the linking information obtained in step S1103 that has persona classification A as the linking unit.

[0118] Next, the integration unit 135 generates integrated information by integrating the statistical information included in the linking information of both businesses extracted in step S1106, with the same persona classification as an axis (step S1107).

[0119] Then, the providing unit 136 provides the integrated information to the requesting business entity (step S1108).

[0120] On the other hand, if the integration unit 135 determines that there is no identical persona classification between the persona classification of the target of use on the requesting operator's side and the persona classification of the target of use on the other operator's side (step S1105; No), it determines whether there is a similar persona classification between the persona classification of the target of use on the requesting operator's side and the persona classification of the target of use on the other operator's side (step S1109).

[0121] For example, the integration unit 135 performs a similarity determination between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side. For example, the integration unit 135 may calculate the degree of agreement based on the distance between the persona classifications, and determine that the two persona classifications are similar if the calculated degree of agreement is equal to or greater than a threshold. The integration unit 135 may also calculate the degree of agreement based on the nature of the persona classification, and determine that the two persona classifications are similar if the calculated degree of agreement is equal to or greater than a threshold.

[0122] If the integration unit 135 determines that there is no similar persona classification between the persona classification of the target of use on the requesting operator's side and the persona classification of the target of use on the other operator's side (step S1109; No), it determines that integration is not possible and terminates the processing.

[0123] On the other hand, when there is an approximate persona classification between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side (step S1109; Yes), the integration unit 135 extracts the linking information of both business companies with the approximate persona classification as the linking unit (step S1110). For example, if the persona classification A between the persona classification of the target of use on the requesting business side and the persona classification of the target of use on the other business side is approximate, the integration unit 135 extracts the linking information acquired in step S1102 with the persona classification A as the linking unit. In addition, the integration unit 135 extracts the linking information acquired in step S1103 with the persona classification A as the linking unit, and executes the processing from step S1107 onwards.

[0124] 9. Other Embodiments From here on, other embodiments of the platform management device 100 will be described. The platform management device 100 may be implemented in various different aspects other than the above-described embodiment. Therefore, other embodiments of the platform management device 100 will be described below.

[0125] In the above embodiment, an example has been shown in which the platform management device 100 performs integration processing between a business operator and other business operators desired by the business operator according to integration conditions set by the business operator. However, the platform management device 100 does not necessarily need to set integration conditions, and may dynamically perform integration processing between predetermined business operators. For example, the platform management device 100 may dynamically determine business operators with high relevance, and integrate the linking information between the determined business operators. As an example, the platform management device 100 can define arbitrary conditions, such as business content, service type, or business operator size, and integrate the linking information between business operators that satisfy the arbitrary conditions.

[0126] On the other hand, the platform management device 100 may randomly extract unrelated businesses and integrate the linking information between the extracted businesses. In this way, the business that has been provided with the integrated information may be able to notice, for example, that a customer U who uses the company's services has an unintended tendency to use the service.

[0127] [10. Hardware Configuration] Next, a hardware configuration example of an information processing device (platform management device 100) according to an embodiment will be described. FIG. 12 is a block diagram showing a hardware configuration example of the information processing device according to an embodiment. Referring to FIG. 12, the information processing device has, for example, a processor 801, a ROM 802, a RAM 803, a host bus 804, a bridge 805, an external bus 806, an interface 807, an input device 808, an output device 809, a storage 810, a drive 811, a connection port 812, and a communication device 813. Note that the hardware configuration shown here is an example, and some of the components may be omitted. Also, components other than those shown here may be further included.

[0128] (Processor 801) The processor 801 functions, for example, as an arithmetic processing device or control device, and controls all or part of the operation of each component based on various programs recorded in the ROM 802, the RAM 803, the storage 810, or the removable recording medium 901.

[0129] (ROM802, RAM803) The ROM 802 is a means for storing the programs to be read into the processor 801, data to be used for calculations, etc. The RAM 803 temporarily or permanently stores, for example, the programs to be read into the processor 801, various parameters that change appropriately when the programs are executed, etc.

[0130] (host bus 804, bridge 805, external bus 806, interface 807) The processor 801, ROM 802, and RAM 803 are connected to each other via, for example, a host bus 804 capable of high-speed data transmission. On the other hand, the host bus 804 is connected to an external bus 806 having a relatively low data transmission speed via, for example, a bridge 805. In addition, the external bus 806 is connected to various components via an interface 807.

[0131] (Input device 808) Examples of the input device 808 include a mouse, a keyboard, a touch panel, a button, a switch, and a lever. Furthermore, a remote controller capable of transmitting control signals using infrared rays or other radio waves may be used as the input device 808. The input device 808 also includes an audio input device such as a microphone.

[0132] (Output Device 809) The output device 809 is a device capable of visually or audibly notifying the user of acquired information, such as a display device such as a CRT (Cathode Ray Tube), LCD, or organic EL, an audio output device such as a speaker or a headphone, a printer, a mobile phone, or a facsimile. The output device 809 according to this embodiment also includes various vibration devices capable of outputting tactile stimulation. The output device 809 may also include an AI speaker or a wearable device.

[0133] (Storage 810) The storage 810 is a device for storing various types of data. For example, a magnetic storage device such as a hard disk drive (HDD), a semiconductor storage device, an optical storage device, or a magneto-optical storage device may be used as the storage 810.

[0134] (Drive 811) The drive 811 is a device that reads information recorded on a removable recording medium 901 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, and writes information to the removable recording medium 901.

[0135] (Connection port 812) The connection port 812 is a port for connecting an external device 902, such as a Universal Serial Bus (USB) port, an IEEE1394 port, a Small Computer System Interface (SCSI), an RS-232C port, or an optical audio terminal.

[0136] (Communication device 813) The communication device 813 is a communication device for connecting to a network, such as a communication card for wired or wireless LAN, Bluetooth (registered trademark), or WUSB (Wireless USB), a router for optical communications, a router for ADSL (Asymmetric Digital Subscriber Line), or a modem for various types of communications.

[0137] (Removable recording media 901) The removable recording medium 901 is, for example, a DVD medium, a Blu-ray (registered trademark) medium, an HD DVD medium, various semiconductor storage media, etc. Of course, the removable recording medium 901 may be, for example, an IC card equipped with a non-contact type IC chip, or an electronic device.

[0138] (External connection device 902) The external connection device 902 is, for example, a printer, a portable music player, a digital camera, a digital video camera, or an IC recorder.

[0139] When the information processing device according to the embodiment is the platform management device 100, the memory unit 120 is realized by the ROM 802, the RAM 803, and the storage 810. Also, the control unit 130 realized by the processor 801 reads out and executes each control program (for example, the information processing program according to the embodiment) that realizes the answer acquisition unit 131, the estimation unit 132, the persona information acquisition unit 133, the association information acquisition unit 134, the integration unit 135, and the provision unit 136 from the ROM 802, the RAM 803, etc.

[0140] [11. Others] Among the above-mentioned processes, all or part of the processes described as being performed automatically may be performed manually. Also, all or part of the processes described as being performed manually may be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings may be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0141] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure. Furthermore, each component may be configured by distributing and integrating functionally or physically in any unit, in whole or in part, depending on various loads and usage conditions. Furthermore, each process described above may be executed in appropriate combination within a range that does not contradict.

[0142] The above describes the embodiments of the present application in detail with reference to several drawings. However, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the Disclosure of the Invention section. [Explanation of symbols]

[0143] 1 System 10 Customer equipment 30 Operator equipment 100 Platform management device 120 Storage section 121 Persona information storage unit 122 Integrated Data Storage Unit 123 Accumulation data storage unit 130 Control section 131 Answer acquisition part 132 Estimation Department 133 Persona Information Acquisition Department 134 Linked information acquisition unit 135 Integration Department 136 Provision Department

Claims

1. a type information acquiring unit that acquires type information in which customers of each service provided by each of a plurality of businesses are classified according to the diversity possessed by the customers; a linking information acquisition unit that acquires linking information in which customer information regarding the use of a service provided by a specific business among the plurality of businesses is linked to the type information in which customers of the service are classified; an integration unit that integrates customer information having the same or similar type information among the linking information; a providing unit that provides integrated information, which is the integrated customer information, to a business that has made a request; 13. An information processing device comprising:

2. The linking information acquisition unit acquires, as the linking information, linking information including statistical information obtained by statistically processing the customer information accumulated by using the service according to the type information into which the customers of the service are classified.

2. The information processing apparatus according to claim 1,

3. The integration unit integrates customer information included in the linking information provided by the different predetermined businesses, the customer information having the same or similar type information.

2. The information processing apparatus according to claim 1,

4. when an integration request including the customer information provided by the specified business operator as an integration condition is received from the specified business operator, the integration unit generates the integrated information by integrating customer information provided by the specified business operator with customer information provided by another business operator different from the specified business operator, the customer information having the same or similar type information as the customer information provided by the specified business operator; The providing unit provides the integration information to the business entity that has made the integration request.

4. The information processing apparatus according to claim 3.

5. The integration unit integrates the customer information in a corresponding state with respect to the type information that matches or is similar between the predetermined business operator and the other business operator.

5. The information processing apparatus according to claim 4.

6. The linking information acquisition unit acquires, as the linking information, linking information provided for sale by the predetermined business operator, The providing unit provides the linking information provided by the specified business entity as a seller to a business entity other than the specified business entity as a seller, so that the linking information can be purchased.

2. The information processing apparatus according to claim 1,

7. An estimation unit that estimates type information of each customer of each service provided by each of a plurality of businesses based on information on the diversity of the customer. Furthermore, The type information acquisition unit acquires the type information estimated by the estimation unit.

2. The information processing apparatus according to claim 1,

8. The providing unit provides type information corresponding to a customer of a service provided by a business that has made a request, out of the type information estimated by the estimation unit, to the business that has made a request.

8. The information processing apparatus according to claim 7,

9. An information processing method executed by an information processing device, a type information acquiring step of acquiring type information in which customers of each service provided by each of a plurality of businesses are classified according to the diversity possessed by the customers; a linking information acquisition step of acquiring linking information linking customer information regarding the use of a service provided by a predetermined business among the plurality of businesses with the type information into which customers of the service are classified; an integration step of integrating customer information having the same or similar type information among the linked information; a providing unit that provides integrated information, which is the integrated customer information, to a business that has made a request; 13. An information processing method comprising:

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