JP7836719B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

This invention relates to an information processing device, an information processing method, and an information processing program.

Traditionally, businesses performing various tasks have undertaken initiatives to visualize "invisible" problems that arise during project work, with the aim of promoting business process improvement activities.

Furthermore, in recent years, technologies have been used to visualize the process from service delivery to user, along with the actions of the service provider, with the aim of efficiently identifying areas for improvement in the service provider's systems.

Japanese Patent Publication No. 2009-271600

However, conventional technologies still have room for improvement in providing information to identify areas for improvement in the service provider's system.

This application was made in view of the above, and aims to provide an information processing device, an information processing method, and an information processing program that can provide information to identify areas for improvement in the service provider's system.

The information processing device according to this application comprises a generation unit, a calculation unit, a placement unit, and a provision unit. The generation unit generates content that visualizes a sequence of actions or experiences a user takes when using a predetermined service, by associating it with second information consisting of measures implemented by the service provider in response to those actions or experiences. The calculation unit calculates indicator values for each measure to measure its effectiveness. The placement unit arranges the indicator values calculated by the calculation unit in relation to the measures. The provision unit provides the user with the content containing the arranged indicator values.

According to one embodiment of the system, it is possible to provide information to identify areas for improvement in the service provider's system.

Figure 1 is a diagram illustrating an example of an information processing system according to an embodiment. Figure 2 shows an example of the configuration of an information processing device according to the embodiment. Figure 3 is a diagram showing an overview of the information stored in the journey master storage unit according to this embodiment. Figure 4 is a diagram showing an overview of the information stored in the business system master storage unit according to the embodiment. Figure 5 is a diagram showing an overview of the information stored in the policy master storage unit according to this embodiment. Figure 6 is a diagram showing an overview of the index master stored in the index master storage unit according to the embodiment. Figure 7 is a diagram showing an overview of the information stored in the reference value information storage unit according to the embodiment. Figure 8 is a flowchart showing an example of a processing procedure by the information processing device according to the present invention. Figure 9 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus according to the embodiment.

The following describes in detail, with reference to the drawings, the embodiments for implementing the information processing device, information processing method, and information processing program according to this application (hereinafter referred to as "embodiments"). Note that the embodiments described below do not limit the information processing device, information processing method, and information processing program according to this application. Furthermore, the embodiments described below can be combined as appropriate, provided that the processing content is not inconsistent. Also, the same parts are denoted by the same reference numerals in the embodiments described below, and redundant descriptions are omitted.

Furthermore, in the following explanation, terminal device 10 may be referred to as user UX. That is, user UX can be read as terminal device 10.

Furthermore, in the embodiments described below, the information processing device 100 collects user information relating to each user utilizing various online services. These various online services may include API (Application Programming Interface) services corresponding to various applications, and other online services. Additionally, these online services may include internet connectivity, search services, SNS (Social Networking Services), e-commerce services, electronic payment services, online games, online banking services, online trading services, hotel reservation services, ticket reservation services, video streaming services, music streaming services, news streaming services, map information services, route search services, route guidance services, route information services, train operation information services, and weather information services.

Furthermore, the user information collected by the information processing device 100 may include, for example, the history of search queries entered by each user in search services, the purchase history and product browsing history of each user in e-commerce services, the browsing history of news and other content viewed by each user in news distribution services, the posting history of text and images posted on SNS (Social Networking Services), and location history.

Furthermore, the information processing device 100 may use information estimated based on the collected information as user information. For example, the information processing device 100 may estimate income, such as a household or individual monthly income of 300,000 yen or more, if the average total monthly grocery purchase amount is 100,000 yen or more, or family structure, such as being a family of three, or the composition of cohabitants, based on purchase history. Also, for example, the information processing device 100 may estimate items owned by the user, the user's place of residence, workplace, etc., from location history and purchase history, and use the estimated information as user information.

Furthermore, the information processing device 100 may provide various online services, or it may acquire the service usage history of each user for various online services from a server device that provides various online services as the user information described above. The information processing device 100 may also collect various information estimated from each user's service usage history by the server device that provides various online services, or by a separate server device, as user information. Furthermore, the information processing device 100 may collect information indicating various demographic attributes and psychographic attributes such as hobbies and preferences that have been registered or estimated by the user as user information.

Furthermore, the information processing device 100 can generate statistical information from the various user information it has collected, and based on the generated statistical information, it can calculate index values used in the information processing according to the embodiment described later. For example, the information processing device 100 collects user information from multiple users who match the target conditions received from the service user UX, and identifies the characteristics of the collected user information (i.e., the tendencies of users belonging to the same cluster). In other words, the information processing device 100 identifies personas (virtual profiles) of multiple users belonging to the same cluster. Then, the information processing device 100 calculates index values based on the information about the identified personas.

[1. An example of an information processing system]
The following describes an information processing system SYS according to an embodiment. Figure 1 is a diagram illustrating an example of an information processing system according to an embodiment. As shown in Figure 1, the information processing system SYS according to an embodiment includes a terminal device 10 and an information processing device 100. Note that the information processing system SYS is not limited to the example shown in Figure 1, and may have multiple information processing devices 100.

The terminal device 10 and the information processing device 100 are each connected to a network N (see, for example, Figure 2) by wired or wireless means. Network N is a communication network such as a LAN (Local Area Network), WAN (Wide Area Network), telephone network (mobile phone network, fixed telephone network, etc.), regional IP (Internet Protocol) network, or the Internet. Network N may include wired networks or wireless networks. The terminal device 10 and the information processing device 100 can communicate with each other through network N.

The terminal device 10 shown in Figure 1 is an information processing device used by the user UX, who is a user of the content service provided by the information processing device 100. For example, the terminal device 10 can be implemented as a smartphone, tablet, notebook PC (Personal Computer), desktop PC, or PDA (Personal Digital Assistant).

Furthermore, the terminal device 10 can connect to network N via wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), as well as short-range wireless communication such as Bluetooth® and Wi-Fi (Local Area Network).

Furthermore, the terminal device 10 can display information for using content provided by the information processing device 100, for example, via a web browser or application. When the terminal device 10 receives control information for displaying information from the information processing device 100 or the like, it will perform the display processing according to the control information.

The information processing device 100 shown in Figure 1 is an information processing device that provides content services to the user UX. The information processing device 100 is typically a server device, but it may also be implemented as a mainframe or workstation. When the information processing device 100 is implemented as a server device, it may be implemented as a single server, or as a cloud system in which multiple server devices and multiple storage devices operate collaboratively.

Furthermore, the information processing device 100 may function as a distribution device that distributes control information to the terminal device 10 used by the service user. Here, the control information is written using, for example, a scripting language such as JavaScript (registered trademark) or a stylesheet language such as CSS (Cascading Style Sheets). Alternatively, the application itself distributed from the information processing device 100 may be considered as the control information.

The information processing device 100 shown in Figure 1 can provide content that visualizes the relationship between two pieces of information: first information, which models the behavioral process consisting of a series of actions or experiences a user takes when using a predetermined service, and second information, which consists of measures implemented by the service provider in response to that series of actions or experiences.

[2. An example of information processing]
An example of information processing according to the embodiment will be described below with reference to Figure 1. As shown in Figure 1, when the information processing device 100 receives a content acquisition request from the user UX, it generates content corresponding to the content acquisition request (step S1). For example, the information processing device 100 generates content that visualizes a sequence of actions or experiences taken by a user when using a predetermined service, by associating it with a second piece of information consisting of measures taken by the service provider in response to the sequence of actions or experiences. In the following description, as one example to which the information processing according to the embodiment can be applied, it is assumed that the "user" in the generated content is a service user using an electronic commerce (EC) service, and the "service provider" in the generated content is a business operator that operates an electronic commerce service.

First, the information processing device 100 refers to the customer journey master and automatically selects a model case of the action process corresponding to the industry type included in the content acquisition request. The customer journey master stores pre-prepared model cases of the action process for each industry type as reference information. In the example shown in Figure 1, the model case of the action process corresponding to the industry "EC (e-commerce)" is selected as "Open app" → "Select product" → "Add to cart" → "Purchase" → "Product arrives".

Next, the information processing device 100 refers to the business structure master and automatically selects a model case of the business structure corresponding to the industry type included in the content acquisition request. The business structure master stores pre-prepared model cases of the service provider's business structure for each industry type as reference information. In the example shown in Figure 1, the "Marketing Team," "Product Team," and "Sales Team" are selected as model cases of the service provider's business structure corresponding to the industry "EC (Electronic Commerce)."

Next, the information processing device 100 refers to the policy master and automatically selects a policy corresponding to the combination of the customer journey and the business structure. For example, the policy master stores information as reference information for automatically selecting a pre-prepared list of policy candidates that each service department can take, for each combination of actions or experiences that constitute the behavioral process and each service department that constitutes the business structure. In the example shown in Figure 1, "Advertising" is selected as a policy that the "Marketing Team" can take in response to the user's action of "Opening the App." Also in the example shown in Figure 1, "Input Suggestion Function" is selected as a policy that the "Product Team" can take in response to the user's action of "Adding to Cart." Also in the example shown in Figure 1, "Review Function" is selected as a policy that the "Product Team" can take in response to the user's experience of "The Product Arrives." "Product Pricing" is selected as a policy that the "Sales Team" can take in response to the user's action of "Choosing a Product."

The information processing device 100 then generates matrix-like content by placing a model customer journey in a predetermined area A1, a model business system in a predetermined area A2, and measures in a predetermined area A3, all within the base model for content provision.

Furthermore, the information processing device 100 may provide the user UX with a tool that allows the user UX to manually configure customer journeys, business systems, and measures, as part of the content services provided to the user UX. In this case, the information processing device 100 does not automatically place model cases for customer journeys and business systems, or candidate measures, but rather provides them as reference information for the user UX to configure manually.

After content generation, the information processing device 100 refers to the indicator master and calculates indicator values for each measure included in the content, which are pre-associated with the measures that the service provider can take, in order to measure the effectiveness of those measures (Step S2). For example, in the example shown in Figure 1, "PV (Paper View)" is calculated as the indicator corresponding to the measure "Advertising." Also in the example shown in Figure 1, "Number of Reviews" is calculated as the indicator corresponding to the measure "Review Function."

After calculating the indicator values, the information processing device 100 places the calculated indicator values in the content in relation to the measures (step S3). For example, the information processing device 100 places the calculated indicator values in the same column as the column where the corresponding measures are placed, among the columns in area A4, which is pre-defined in the base model of the content. For example, in the example shown in Figure 1, the indicator value "PV" corresponding to the measure "Advertising" is placed in column C1 of the content, and the indicator value "Number of Reviews" corresponding to the measure "Review Function" is placed in column C2 of the content.

The information processing device 100 then provides the user UX by transmitting content containing indicator values corresponding to the measures to the terminal device 10 (step S4). As shown in Figure 1, an example of content provided to the user UX, Content CT, is structured in a matrix with a model customer journey in area A1, a model business system in area A2, measures in area A3, and indicator values in area A4.

The user UX can utilize the content provided by the information processing device 100 (for example, content CT) as a business framework for identifying areas for operational improvement in its own e-commerce services.

Furthermore, if there are multiple indicator values pre-associated with a policy, the information processing device 100 may arrange these indicator values in the content and provide them to the user UX. This provides the user UX with opportunities to measure the effectiveness of the policy from various angles.

Furthermore, the information processing device 100 may provide the user UX with content that highlights the area where the measures associated with the calculated indicator values are displayed, if any of the indicator values calculated for each measure fall below a predetermined threshold value. In the case shown in Figure 1, if the indicator value "Number of Reviews" is below the threshold, the information processing device 100 highlights the measure "Review Function" associated with the indicator value "Number of Reviews." This makes it easier to identify measures that may be bottlenecks in operations.

[3. Configuration of Information Processing Device]
The configuration of the information processing device 100 according to the embodiment will be explained using Figure 2. Figure 2 is a diagram showing an example of the configuration of the information processing device according to the embodiment.

As shown in Figure 2, the information processing device 100 comprises a communication unit 110, a storage unit 120, and a control unit 130. Note that Figure 2 shows an example configuration of the information processing device 100, and is not limited to the configuration shown in Figure 2; it may also have other functional units not shown in Figure 2.

(Communications Department 110)
The communication unit 110 is connected to the network N by wire or wireless means, for example, and transmits and receives information with other devices such as the terminal device 10 via the network N. The communication unit 110 is implemented by, for example, a NIC (Network Interface Card) or an antenna. The network N is a communication network such as a LAN (Local Area Network), a WAN (Wide Area Network), a telephone network (such as a mobile phone network or a fixed telephone network), a regional IP (Internet Protocol) network, or the Internet. The network N may include a wired network or a wireless network.

For example, the communication unit 110 transmits and receives various information related to the processing required to provide content services to the terminal device 10.

(Storage unit 120)
The storage unit 120 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) or flash memory, or by storage devices such as hard disks or optical discs. The storage unit 120 stores programs and data for realizing information processing performed by each part of the control unit 130.

As shown in Figure 3, the storage unit 120 includes a journey master storage unit 121, a business system master storage unit 122, a policy master storage unit 123, an indicator master storage unit 124, a reference value information storage unit 125, and a user information storage unit 126.

(Journey Master Memory Unit 121)
The journey master storage unit 121 stores information that represents pre-prepared model cases of the aforementioned behavioral processes for each industry type. Figure 3 shows an overview of the information stored in the journey master storage unit 121 according to this embodiment.

As shown in Figure 3, the information stored in the journey master storage unit 121 includes the "industry" item and the "model case" item. These items in the information stored in the journey master storage unit 121 are interconnected.

The "Industry" field stores information indicating the industry type. The "Model Case" field stores information indicating a model case of the behavioral process corresponding to that industry type. The behavioral process consists of a series of actions or experiences that a user takes when using a specific service. According to Figure 3, an example of a model case of the behavioral process corresponding to the "EC" industry is shown as: "Open app" → "Select product" → "Add to cart" → "Purchase" → "Product arrives."

(Business System Master Storage Unit 122)
The business system master storage unit 122 stores information that shows model cases of business systems on the service provider side, which are prepared in advance for each industry type. Figure 4 shows an overview of the information stored in the business system master storage unit 122 according to this embodiment.

As shown in Figure 4, the information stored in the business system master storage unit 122 includes the fields "Industry" and "Model Case." These fields in the information stored in the business system master storage unit 122 are interconnected.

The "Industry" field stores information indicating the industry type. The "Model Case" field stores information showing model cases for each service department that constitute the service provider's operational structure corresponding to the industry type. According to Figure 4, the "Marketing Team," "Product Team," and "Sales Team" are shown as example model cases for each service department that constitute the service provider's operational structure corresponding to the "EC" industry.

(Policy Master Storage Unit 123)
The policy master storage unit 123 stores information indicating pre-prepared policy candidates that each service department can take, for each combination of actions or experiences that constitute the action process and each service department that constitutes the work system. Figure 5 shows an overview of the information stored in the policy master storage unit 123 according to this embodiment.

As shown in Figure 5, the information stored in the policy master storage unit 123 includes the items "Customer Journey," "Business System," and "Policy." These items stored in the policy master storage unit 123 are interconnected.

The "Customer Journey" section stores information indicating the series of actions or experiences a user follows. The "Operational Structure" section stores information indicating each service department that makes up the service provider's operational structure. The "Measures" section stores information indicating the measures each service department can take in relation to the combination of actions or experiences that make up the user journey and the service departments that make up the operational structure. According to Figure 5, for the combination of the user's action "open the app" and "marketing," one of the services that make up the operational structure, "advertising" is shown as an example of a measure that "marketing" can take. Note that Figure 5 illustrates a case where no measures are set for the service department corresponding to the user's action "purchase," but it is also possible that a service department and measures corresponding to the action "purchase" are set up in association.

(Indicator master storage unit 124)
The indicator master storage unit 124 stores information indicating indicator values for measuring the effectiveness of the measures. Figure 6 shows an overview of the indicator master stored in the indicator master storage unit 124 according to this embodiment.

As shown in Figure 6, the information stored in the indicator master storage unit 124 includes the items "Policy" and "Indicator Value." These items in the indicator master storage unit 124 are interconnected.

The "Measures" field stores information about the measures being taken. The "Metric Values" field stores information indicating the types of metric values pre-assigned to the measures being taken by the service provider for measuring their effectiveness. According to Figure 6, examples of metric values corresponding to the "Advertising" measure include "PV (Paper View)," "CTR (Click Through Rate)," and "CVR (Conversion Rate)."

(Reference value information storage unit 125)
The reference value information storage unit 125 stores information indicating a reference value for evaluating each index value. Figure 7 shows an overview of the information stored in the reference value information storage unit 125 according to this embodiment.

As shown in Figure 7, the information stored in the reference value information storage unit 125 includes an "indicator value" item and a "reference value" item. These items in the reference value information storage unit 125 are interconnected. The "indicator value" item stores information indicating the indicator value. The "reference value" item stores information indicating a predetermined reference value for evaluating the indicator value.

(User information storage unit 126)
The user information storage unit 126 stores user information for each user who uses various online services. The user information stored in the user information storage unit 126 is used, for example, as sample data for calculating indicator values linked to policies.

(Control unit 130)
Returning to Figure 2, the control unit 130 is a controller that controls the information processing device 100. The control unit 130 is implemented by a CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), etc., which executes various programs (for example, information processing programs) stored in the internal memory of the information processing device 100 using RAM as the working area. Alternatively, the control unit 130 may be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

As shown in Figure 2, the control unit 130 comprises a generation unit 131, a calculation unit 132, a placement unit 133, and a supply unit 134. The control unit 130 realizes or executes the information processing functions and operations described below through these units. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Figure 2; other configurations are also acceptable as long as they perform the information processing described later. Furthermore, the connection relationships of the units of the control unit 130 are not limited to those shown in Figure 2; other connection relationships are also acceptable.

(Generation unit 131)
The generation unit 131 generates content that visualizes a customer journey model case (an example of "first information") which shows the behavioral process consisting of a series of actions or experiences that a user takes when using a predetermined service, and a business system model case (an example of "second information") which consists of measures implemented by the service provider in response to that series of actions or experiences.

For example, when the generation unit 131 receives a content acquisition request from a user (for example, the user UX shown in Figure 1) who is a user of the content service via the communication unit 110, it refers to the information stored in the journey master storage unit 121. The generation unit 131 then automatically selects a model case of the behavioral process corresponding to the industry type included in the content acquisition request.

Furthermore, the generation unit 131 refers to the information stored in the business system master storage unit 122 and automatically selects a model case of a business system corresponding to the industry type included in the content acquisition request.

Furthermore, the generation unit 131 refers to the information stored in the policy master storage unit 123 and automatically selects policies corresponding to combinations of customer journey model cases and business system model cases. For example, the generation unit 131 refers to the policy master and automatically selects policies from a pre-prepared list of possible policies for each service department, based on combinations of user actions or experiences constituting the customer journey (behavioral process) and each service department constituting the business system of the service provider that provides predetermined services to the user.

The generation unit 131 then generates content by placing the automatically selected customer journey model case, business system model case, and pre-configured areas for placing the measures in the base model for content provision (for example, template data).

(Calculation unit 132)
The calculation unit 132 calculates indicator values for each measure to measure the effectiveness of the measures. For example, the calculation unit 132 refers to the information stored in the indicator value master storage unit 124 and identifies the indicators that are pre-associated with the measures. Next, the calculation unit 132 sets a target according to the industry type included in the content acquisition request and obtains user information corresponding to the set target from the user information storage unit 126. Next, the calculation unit 132 appropriately selects the information necessary to calculate the indicators identified based on the indicator value master storage unit 124 from the user information obtained from the user information storage unit 126, and uses the selected information to calculate the indicator values corresponding to each measure.

(Arrangement part 133)
The placement unit 133 places the indicator values calculated by the calculation unit 132 into the content generated by the generation unit 131, associating them with the measures. For example, in the base model for content provision, the placement unit 133 places the indicator values calculated for each measure into pre-set areas for placing the indicator values, associating them with the measures.

(Providing unit 134)
The provision unit 134 provides content to users, who are users of the content service, by transmitting content containing indicator values corresponding to the measures to the terminal device 10 via the communication unit 110.

[4. Processing Procedure]
The processing procedure by the information processing device 100 according to this embodiment will be described below with reference to Figure 8. Figure 8 is a flowchart showing an example of the processing procedure by the information processing device according to this embodiment. The processing procedure shown in Figure 8 is executed by the control unit 130 of the information processing device 100. The processing procedure shown in Figure 8 is repeatedly executed while the information processing device 100 is in operation.

As shown in Figure 8, the generation unit 131 automatically selects a model case of the behavioral process corresponding to the industry type by referring to the journey master (step S101).

Furthermore, the generation unit 131 automatically selects a model case of the business system corresponding to the industry type by referring to the industry system master (step S102).

Furthermore, the generation unit 131 automatically selects measures corresponding to combinations of customer journey model cases and business system model cases by referring to the measure master (step S103).

Furthermore, the generation unit 131 generates content by placing the information automatically selected in steps S101 to S103 into a predetermined area provided in the base model for content provision (step S104).

Furthermore, the calculation unit 132 refers to the indicator master to identify the indicator values corresponding to the measures automatically selected in step S103, and calculates the identified indicator values for each measure (step S105).

Furthermore, the placement unit 133 associates the indicator values calculated in step S105 with the measures corresponding to those indicator values and places them in the content generated in step S104 (step S106).

Furthermore, the provisioning unit 134 provides the user with content containing the indicator values (step S107), and then terminates the processing procedure shown in Figure 8.

[5. Variations]
The information processing device 100 described above may be implemented in various different forms other than those described above. Therefore, modifications of the embodiment will be described below.

(5-1. Content editing function)
In the embodiment described above, the information processing device 100 may provide the user, who is a user of the content service, with a function to accept edits to the content provided to the user. For example, the information processing device 100 may accept changes to the customer journey process included in the content, additions to measures for the content, or deletions of measures from the content. Furthermore, if measures are added to the content, the information processing device 100 may select an indicator corresponding to the added measure, calculate an indicator value corresponding to the selected indicator, and place it in the content.

(5-2. Information provision based on content provision history)
In the embodiment described above, the information processing device 100 may manage information about the content provided to each user, who is a user of the content service, as a content provision history. In this case, the information processing device 100 may also provide the user with proposed changes to the measures based on the time-series changes in the indicator values included in the content provision history. For example, the time-series changes in the indicator values can be traced based on the content provision history of one user belonging to the same industry. Then, if there is a measure in which the time-series change of the indicator value is on an upward trend, the information processing device 100 provides information about the measure corresponding to the indicator value that is on an upward trend to the other user belonging to the same industry. The information processing device 100 can provide information on the type of service, the measure, and the indicator value as information on the measures.

Furthermore, the information processing device 100 traces the metric values included in the content provision history of one user belonging to the same industry and identifies points where the metric value exceeds a baseline value. The information processing device 100 then obtains the difference between the content corresponding to the identified point and the content provided immediately before it, and may provide the obtained difference information (such as different measures between the content) to the other user belonging to the same industry.

[6. Hardware Configuration]
The information processing device 100 according to the embodiment is implemented by a computer 1000 having the configuration shown in Figure 9. Figure 9 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device according to the embodiment.

The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which an arithmetic unit 1030, a primary storage device 1040, a secondary storage device 1050, an output interface 1060, an input interface 1070, and a network interface 1080 are connected by a bus 1090.

The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, as well as programs read from the input device 1020, and executes various processes. The primary storage device 1040 is a memory device, such as RAM, that temporarily stores data used by the arithmetic unit 1030 for various calculations. The secondary storage device 1050 is a storage device where data used by the arithmetic unit 1030 for various calculations and various databases are registered, and is implemented using ROM (Read Only Memory), HDD, flash memory, etc.

The output IF 1060 is an interface for transmitting information to be output to output devices 1010, such as monitors and printers. It is implemented using connectors conforming to standards such as USB (Universal Serial Bus), DVI (Digital Visual Interface), and HDMI (High Definition Multimedia Interface). The input IF 1070 is an interface for receiving information from various input devices 1020, such as mice, keyboards, and scanners. It is implemented using, for example, USB.

The input device 1020 may be, for example, a device that reads information from optical recording media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), and PDs (Phase-change rewritable Disks), magneto-optical recording media such as MOs (Magneto-Optical disks), tape media, magnetic recording media, or semiconductor memory. Alternatively, the input device 1020 may be an external storage medium such as a USB memory stick.

The network interface 1080 receives data from other devices via the network N and sends it to the computing unit 1030, and also transmits data generated by the computing unit 1030 to other devices via the network N.

The arithmetic unit 1030 controls the output device 1010 and input device 1020 via the output IF 1060 and input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or secondary storage device 1050 onto the primary storage device 1040, and then executes the loaded program.

For example, when computer 1000 functions as an information processing device 100, the arithmetic unit 1030 of computer 1000 performs the same functions as the control unit 130 by executing a program (for example, an information processing program) loaded onto the primary storage device 1040. That is, the arithmetic unit 1030 works in cooperation with the program (for example, an information processing program) loaded onto the primary storage device 1040 to perform the processing performed by the information processing device 100 according to this embodiment.

[7. Others]
Of the processes described in the embodiments described above, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified.

In the above-described embodiment, in order to realize the information processing method by the information processing device 100 (see, for example, Figure 8), the processing functions corresponding to each part of the control unit 130 of the information processing device 100 (generation unit 131, calculation unit 132, arrangement unit 133, and provision unit 134) may be implemented as add-ons to an information processing program pre-installed on the information processing device 100, or they may be implemented by flexibly writing a dedicated information processing program using a lightweight programming language or the like.

Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown; all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions. For example, the generation unit 131 and the arrangement unit 133 of the control unit 130 may be functionally integrated.

Furthermore, the above-described embodiments and modifications can be combined as appropriate, provided that the processing content remains consistent.

[8. Effects]
The information processing device 100 according to the above embodiment comprises a generation unit 131, a calculation unit 132, a placement unit 133, and a provision unit 134. The generation unit 131 generates content that visualizes a series of actions or experiences taken by a user when using a predetermined service, by associating it with a second piece of information consisting of measures taken by the service provider in response to those actions or experiences. The calculation unit 132 calculates an indicator value for each measure for measuring the effectiveness of the measures. The placement unit 133 arranges the indicator values calculated by the calculation unit 132 in association with the measures. The provision unit 134 provides the user with the content in which the indicator values have been arranged.

Furthermore, the placement unit 133 places indicator values within the content in relation to the policy.

Furthermore, the calculation unit 132 calculates multiple indicator values that are pre-associated with the policy. The placement unit 133 then places these multiple indicator values into the content, in relation to the policy.

The provisioning unit 134 provides content that highlights the area where the measures associated with the indicator values are displayed, if there are indicator values that are below a predetermined threshold value for each indicator value.

Furthermore, the generation unit 131 automatically selects a pre-prepared model case of the behavioral process for each industry type, according to the industry type set by the user.

Furthermore, the generation unit 131 automatically selects a model case of the service provider's operational structure, which is pre-prepared for each industry type, according to the industry type.

Furthermore, the generation unit 131 automatically selects pre-prepared candidate measures that each service department can take, based on the industry type, for each combination of actions or experiences constituting the behavioral process and each service department constituting the operational structure.

In this way, the information processing device 100 according to the embodiment can provide information for identifying areas for improvement in the service provider's system through the processing performed by each of the above-described parts, or any combination thereof. For example, a user of a content service can use the content obtained from the information processing device 100 as a business framework for identifying operational improvements in the services they operate.

Although embodiments of this application have been described in detail above with reference to several drawings, these are illustrative examples, and the present invention can be implemented in various modified and improved forms based on the knowledge of those skilled in the art, starting with the embodiments described in the disclosure section of the invention.

Furthermore, the terms "section," "module," and "unit" mentioned above can be replaced with "means" or "circuit," etc. For example, a control unit can be replaced with a control means or control circuit.

10 Terminal device 100 Information processing device 110 Communication unit 120 Storage unit 121 Journey master storage unit 122 Business system master storage unit 123 Policy master storage unit 124 Indicator master storage unit 125 Reference value information storage unit 126 User information storage unit 130 Control unit 131 Generation unit 132 Calculation unit 133 Placement unit 134 Provision unit

Claims (4)

A generation unit generates content that visualizes the relationship between first information, which represents a behavioral process consisting of a series of actions or experiences that a user takes when using a specified service, and second information, which consists of measures taken by the service provider in response to the series of actions or experiences.
A calculation unit that calculates indicator values for each of the measures in order to measure the effectiveness of the measures,
A configuration unit that arranges the indicator values calculated by the calculation unit in relation to the measures,
The system comprises a providing unit that provides the user with the content on which the aforementioned index values are arranged,
The generating unit is
Depending on the industry type set by the user, a pre-prepared model case of the aforementioned action process is automatically selected for each industry type.
An information processing device characterized by automatically selecting a model case of the service provider's operational structure, which is prepared in advance for each industry type, according to the aforementioned industry type. The generating unit is
The information processing device according to claim 1, characterized in that, according to the industry type, it automatically selects the measures that can be taken by each service department from a pre-prepared list of candidates for measures that each service department can take, for each combination of the actions or experiences constituting the action process and each service department constituting the business system. A method of information processing performed by a computer,
A generation process that generates content that visualizes the relationship between first information, which represents an action process consisting of a series of actions or experiences that a user takes when using a specified service, and second information, which consists of measures taken by the service provider in response to the series of actions or experiences.
A calculation step for calculating indicator values for each of the measures in order to measure the effectiveness of the measures,
A configuration step involves arranging the indicator values calculated in the calculation step in relation to the measures,
The process includes providing the content on which the aforementioned index values are placed to a user,
The aforementioned generation step is
Depending on the industry type set by the user, a pre-prepared model case of the aforementioned action process is automatically selected for each industry type.
Depending on the industry type, the system automatically selects a model case of the service provider's operational structure that has been prepared in advance for each industry type.
An information processing method characterized by the following: On the computer,
A generation procedure for generating content that visualizes a sequence of actions or experiences taken by a user when using a specified service, by associating it with a second set of information consisting of measures taken by the service provider in response to those actions or experiences.
A calculation procedure for calculating indicator values for each of the aforementioned measures in order to measure the effectiveness of the aforementioned measures,
A configuration procedure for arranging the indicator values calculated from the above calculation procedure in relation to the above measures,
The procedure for providing the content on which the aforementioned index values are placed to the user is performed ,
The aforementioned generation procedure is:
Depending on the industry type set by the user, a pre-prepared model case of the aforementioned action process is automatically selected for each industry type.
An information processing program characterized by automatically selecting a model case of the service provider's operational structure, which is prepared in advance for each industry type, according to the aforementioned industry type .