Information processing device, information processing method, and information processing program

Abstract

To provide operators with an objective evaluation of the trends in the reasons why buyers select products traded online. [Solution] The information processing device according to the present invention comprises a reception unit, an acquisition unit, an extraction unit, a generation unit, and a provision unit. The reception unit receives from the operator the product category to which the target product belongs, the values ​​to be analyzed, and a description of said values. The acquisition unit acquires posted information for the target product belonging to the product category. The extraction unit estimates the values ​​suggested by the content of each piece of posted information based on the content of the acquired posted information and the description of the values, and extracts the estimated values ​​as the reasons for selection by the purchaser of the target product. The generation unit generates first content showing the trends in the reasons for selection of the target product based on the aggregated results of the values ​​and the content generation conditions. The provision unit provides the generated first content to the operator.

Description

[Technical Field]

[0001] The present application relates to an information processing apparatus, an information processing method, and an information processing program. [Background Art]

[0002] Conventionally, technologies for supporting content providers who provide users with optimal content regarding transaction targets such as goods and services based on information acquired from users have been widely spread. In relation to such technologies, there have also been proposed technologies that accept feature information associated with clusters, classify content based on the feature information, and classify users based on the user's access information to the classified content (see, for example, Patent Document 1). [Prior Art Literature] [Patent Literature]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2017-21469 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] However, conventional techniques have room for improvement in providing operators with an objective evaluation regarding the tendency of selection reasons for which products traded online are selected by purchasers.

[0005] The present application has been made in view of the foregoing, and an object of the present application is to provide an operator with an objective evaluation regarding the tendency of selection reasons for which products traded online are selected by purchasers. [Means for Solving the Problem]

[0006] The information processing device according to the present application comprises a reception unit, an acquisition unit, an extraction unit, a generation unit, and a provision unit. The reception unit receives setting information from an operator regarding the product category to which the target product to be processed belongs among the products traded online, the values ​​to be analyzed, and the setting of the description of said values. The acquisition unit acquires posted information for the target product belonging to the product category received by the reception unit. The extraction unit estimates the values ​​suggested by the content of the posted information from each piece of posted information based on the content of the posted information acquired by the acquisition unit and the description of the values, and extracts the estimated values ​​as the reasons for selection by the buyer. The generation unit generates first content showing the trends of the reasons for selection of the target product based on the aggregated results of the values ​​extracted as reasons for selection of the target product by the extraction unit and pre-set content generation conditions. The provision unit provides the first content generated by the generation unit to the operator. [Effects of the Invention]

[0007] According to one embodiment of the system, an objective evaluation of the trends in the reasons why buyers select products traded online can be provided to the operator. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a diagram illustrating the overview of the information processing according to the embodiment. [Figure 2] Figure 2 shows an example of instruction information input to the generation AI according to the embodiment. [Figure 3] Figure 3 shows another example of content according to this embodiment. [Figure 4] Figure 4 is a diagram illustrating the overview of information processing in response to a value verification request according to the embodiment. [Figure 5] Figure 5 is a diagram showing an example of content illustrating the time-series changes in values ​​according to this embodiment. [Figure 6]Figure 6 is a diagram illustrating an example of content showing the relationship between the determinants of product purchase by a specific service user according to the embodiment and their response to advertising creatives. [Figure 7] Figure 7 shows another example of content illustrating the relationship between the determinants of product purchases by a specific service user according to the embodiment and their response to advertising creatives. [Figure 8] Figure 8 shows an example of the system configuration of an information processing system according to the embodiment. [Figure 9] Figure 9 shows an example of the configuration of an information processing device according to the embodiment. [Figure 10] Figure 10 is a diagram showing an overview of the product information stored in the product information storage unit according to this embodiment. [Figure 11] Figure 11 is a diagram showing an overview of the user information stored in the user information storage unit according to the embodiment. [Figure 12] Figure 12 is a diagram showing an overview of the advertising information stored in the advertising information storage unit according to the embodiment. [Figure 13] Figure 13 is a flowchart showing an example of the processing procedure for information processing performed by the information processing device according to the embodiment. [Figure 14] Figure 14 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device according to the embodiment. [Modes for carrying out the invention]

[0009] The following describes in detail, with reference to the drawings, the embodiments for implementing the information processing apparatus, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments"). Note that these embodiments do not limit the information processing apparatus, information processing method, and information processing program according to the present application. Furthermore, each embodiment can be appropriately combined as long as the processing content is not inconsistent. Also, the same parts are denoted by the same reference numerals in each of the following embodiments, and redundant explanations are omitted.

[0010] [Embodiment] [1-1. Example of information processing] Hereinafter, an example of information processing according to an embodiment will be described with reference to the drawings. FIG. 1 is a diagram for explaining an outline of information processing according to an embodiment. The information processing according to the embodiment described below aims to provide users with objective evaluations of transaction objects and service users in online services.

[0011] The information processing according to the embodiment is implemented by an information processing system SYS including a terminal device 10 shown in FIG. 1 and an information processing device 100 shown in FIG. 1 (see FIG. 8, for example). The terminal device 10 and the information processing device 100 are each connected to a network N (see FIG. 8, for example) via wired or wireless connection. The terminal device 10 and the information processing device 100 can communicate with other devices through the network N.

[0012] The terminal device 10 is used by an operator OP. The operator OP analyzes transaction status in an electronic commerce service that enables trading of various products online (referred to as "EC (Electronic Commerce) service"). The operator OP may be, for example, a business operator that lists its own products (an example of "target products") on the EC service. Note that the EC service in the embodiment described below is assumed to be a marketplace-type platform.

[0013] The information processing device 100 is managed by a service provider that operates the EC service. As the information processing related to the embodiment, the information processing device 100 uses various types of information accumulated through the provision of the EC service to generate and provide content indicating trends in selection reasons for why a target product to be processed is selected by a purchaser.

[0014] For example, when performing analysis such as analysis of objective evaluations of the company's own products on an EC site, or analysis of transaction-related behaviors of users of the EC site service who follow the company's official account (hereinafter referred to as "followers"), an operator OP accesses a dedicated site for analyzing the company's own products or followers. The dedicated site is managed by the information processing apparatus 100.

[0015] The terminal device 10 displays a setting screen G-1 provided on the dedicated site on a display D in accordance with an operation by the operator OP. Then, the operator OP sets the product category to which the target product belongs in a setting area B-1 of the setting screen G-1 displayed on the display D. For example, the operator OP can set the product category by selecting the product category corresponding to the target product from a pull-down menu displayed in the setting area B-1.

[0016] Further, the operator OP sets values to be analyzed in a setting area B-2 of the setting screen G-1. For example, the operator OP can set the values by individually inputting one value to be analyzed into each of a plurality of sub-areas provided in the setting area B-2. The values set in the setting area B-2 are analysis items for analyzing what kind of value purchasers find in the target product when selecting the product. That is, the values are analysis items for analyzing for what reason the target product is selected by purchasers.

[0017] Further, the operator OP sets descriptions of the values in a setting area B-3 of the setting screen G-1. For example, the operator OP can set the descriptions of the values by inputting a description of each value into each of sub-areas provided for respective values in the setting area B-3. The descriptions of the values set in the setting area B-3 correspond to information for concretely specifying the meaning of the values set by the operator OP.

[0018] Furthermore, the information processing device 100 can provide the operator OP with information J-1 indicating candidate values, in accordance with the product category setting for the setting area B-1 on the setting screen G-1. This allows the information processing device 100 to support the operator OP in setting values.

[0019] When the terminal device 10 detects an operation by operator OP on the analysis button OB-1 provided on the setting screen G-1, it transmits setting information regarding the product category, values, and description of values ​​set by operator OP to the information processing device 100 (step S1).

[0020] When the information processing device 100 receives setting information regarding product categories, values, and descriptions of values ​​from the terminal device 10, it obtains product reviews (an example of "posted information") posted for target products belonging to the received product category (step S2).

[0021] The information processing device 100 estimates the values ​​suggested by the content of each product review for the target product based on the acquired product review content and the value descriptions received in step S1, and extracts the estimated values ​​as reasons for selecting the target product (step S3). For example, the information processing device 100 can use artificial intelligence (AI) to extract the reasons for selecting the target product. Specifically, by inputting the product review information and instruction information instructing the AI ​​to extract the reasons for selecting the target product, the information processing device 100 can obtain the inference result of the values ​​suggested by the content of each product review from the AI.

[0022] Figure 2 shows an example of instruction information input to the generating AI according to the embodiment. As shown in Figure 2, the instruction information P according to the embodiment includes information corresponding to "system_prompt", information for specifying the "answer format", and information for specifying "matters to be strictly observed". For example, the information processing device 100 includes information showing the correspondence between values ​​set by the operator OP and explanations of those values ​​as a purchase decision factor list included in "system_prompt".

[0023] The generative AI used by the information processing device 100 includes text generation AI, image generation AI, and multimodal AI. Text generation AI, for example, corresponds to a language model trained to estimate and output the next token from an input sequence of tokens. Such language models could include transfer-based models or RNN (Recurrent Neural Network)-based models.

[0024] Transfer-based models such as GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers) are conceivable, but the model is not limited to these examples. Similarly, RNN-based models such as RWKV (Receptance Weighted Key Value) are conceivable, but the model is not limited to these examples. Furthermore, it is desirable that the input information be kept confidential by training the model so that it is not used as a new answer, thereby protecting personal information and other sensitive data.

[0025] Examples of image generation AI include StackGAN (Generative Adversarial Networks), AttnGAN, T2I (Text-to-Image) with Transformers, and DALL-E, but the examples are not limited to these.

[0026] Multimodal AI includes generative models that, for example, generate images from text or text from images. Examples of such generative models include GPT-4V and CM3Leon (Chameleon Multimodal Model), but the definition is not limited to these examples.

[0027] Furthermore, the generation AI used by the information processing device 100 may be located on an external device. In this case, the information processing device 100 can obtain the inference results of the generation AI via an API (Application Programming Interface) provided by the external device.

[0028] After extracting the reasons for selecting the target product, the information processing device 100 generates a first content (step S4) that shows the trends in the reasons why the target product is selected by the purchaser, based on the aggregated results of the values ​​extracted as reasons for selection and the pre-set content generation conditions. This allows the information processing device 100 to provide the operator OP with information showing what value the purchaser finds in the target product and why they choose it. The information processing device 100 may accept the setting of the content generation conditions from the operator OP in advance, or it may accept them at the same time as setting them in step S1.

[0029] The information processing device 100 can accept conditions for content generation, which include conditions for analyzing the trends in the reasons why a target product is selected by a purchaser on a product-by-product basis (product axis). For example, the information processing device 100 can accept a condition for content generation that specifies each product manufactured and sold by a certain home appliance manufacturer, Company A. In this case, the information processing device 100 can generate first content that includes statistical information showing the average value based on product reviews for each product manufactured and sold by Company A.

[0030] Furthermore, the information processing device 100 can also accept multiple conditions as content generation conditions for analyzing the trends in the reasons why a target product is selected by a purchaser, on a product-by-product basis (product axis). In this case, the information processing device 100 can generate statistical information for each of the multiple different conditions accepted as content generation conditions, and generate a first content containing each of the generated statistical information.

[0031] For example, the information processing device 100 can accept, as the first content generation condition, the condition that each product is manufactured and sold by a certain home appliance manufacturer, Company A, and as the second content generation condition, the condition that each product is distributed throughout the entire home appliance manufacturer industry to which Company A belongs. In this case, the information processing device 100 can generate first content that includes statistical information showing the average value based on product reviews of each product manufactured and sold by Company A, and statistical information showing the average value based on product reviews of each product distributed throughout the entire home appliance manufacturer industry.

[0032] The information processing device 100 then provides the generated first content to the operator OP by transmitting it to the terminal device 10 (step S5).

[0033] The terminal device 10 displays the content received from the information processing device 100 on the display D. Figure 1 shows an example in which content C1-1 and content C1-2 are displayed on the display D. For example, content C1-1 and content C1-2 are content generated from the same data. In the following description, content C1-1 and content C1-2 will be collectively referred to as "content C1" as needed.

[0034] Content C1-1 includes statistical information corresponding to content generation condition "Condition 1" (solid line) and statistical information corresponding to content generation condition "Condition 2" (dotted line). For example, "Condition 1" could be each product manufactured and sold by Company A, and "Condition 2" could be each product distributed across the entire home appliance industry.

[0035] Furthermore, content C1-2 is an example of content generated using a correspondence analysis method. For example, the information processing device 100 can provide the operator OP with content C1-1 and content C1-2, which have different display formats, and can be switched between and displayed. Alternatively, the information processing device 100 may provide the operator OP with content that displays both content C1-1 and content C1-2 simultaneously.

[0036] Thus, the information processing device 100 according to this embodiment estimates the values ​​suggested by the content of product reviews based on product reviews of target products in a product category set by the operator OP and the value descriptions set by the operator OP, extracts the estimated values ​​as reasons for selecting the target product, aggregates the extracted values ​​as reasons for selection, and provides the operator OP with a first content that shows the trend of reasons for selecting the target product by the buyer, as information that shows an objective evaluation of the target product. In this way, the information processing device 100 can provide the operator OP with an objective evaluation regarding the trend of reasons for selecting products traded online by the buyer. Furthermore, the information processing device 100 can provide the operator OP with information that allows for comparison by extracting the trend of reasons for selecting products traded online by the buyer from different perspectives.

[0037] Furthermore, the information processing device 100 may generate a second content that shows the trends of determinants that a specific service user is estimated to consider important when deciding to purchase a product, using the aggregated results of values ​​extracted as reasons for selection for each product purchased by a specific service user selected from among the service users who conduct online product transactions.

[0038] In this case, the information processing device 100 receives user segmentation conditions from the operator OP to specify a particular service user. Possible user segmentation conditions include gender, age or age group, price range of the products purchased, and whether or not the user follows official accounts established within the communication service.

[0039] For example, if the information processing device 100 receives user segment conditions from operator OP, such as condition 1 specifying service users who follow an official account established in the communication service by company X where operator OP works, and condition 2 specifying service users who follow any of the official accounts of companies in the same industry as company A, it can generate second content including statistical information showing the average value based on product reviews for products purchased by each service user who follows company A's official account, and statistical information showing the average value based on product reviews for products purchased by each service user who follows any of the official accounts of companies in the same industry as company A.

[0040] This allows the information processing device 100 to provide the operator OP with an objective evaluation of the determinants that are estimated to be important to a specific service user when deciding to purchase goods traded online. Furthermore, the information processing device 100 can provide the operator OP with comparable information by extracting trends in the determinants that are estimated to be important to a specific service user when deciding to purchase goods traded online from different perspectives. Figure 3 shows another example of content according to the embodiment.

[0041] Figure 3 shows an example of content C2-1 and content C2-2 being displayed on display D. For example, content C2-1 and content C2-2 are generated from the same data. In the following explanation, content C2-1 and content C2-2 will be collectively referred to as "content C2" as needed.

[0042] Content C2-1 includes statistical information corresponding to content generation condition "Condition 1" (solid line) and statistical information corresponding to content generation condition "Condition 2" (dotted line). For example, "Condition 1" could be following company A's official account, and "Condition 2" could be following any of the official accounts of companies in the same industry as company A.

[0043] Furthermore, content C2-2 is an example of content generated using a correspondence analysis method. For example, the information processing device 100 can provide the operator OP with content C2-1 and content C2-2, which have different display formats, and can be switched between and displayed. Alternatively, the information processing device 100 may provide the operator OP with content that displays both content C2-1 and content C2-2 simultaneously.

[0044] Alternatively, the information processing device 100 may provide the operator OP with both content C1 shown in Figure 1 and content C2 shown in Figure 3. In this case, the information processing device 100 receives from the operator OP the content generation conditions for generating content C1 shown in Figure 1 and the content generation conditions for generating content C2 shown in Figure 3 as separate conditions that are not combined.

[0045] Thus, the information processing device 100 according to this embodiment can provide the operator OP with a second content that shows the trends of determinants that a specific service user is estimated to consider important when deciding to purchase a product, using the aggregated results of values ​​extracted as reasons for selection for each product purchased by a specific service user selected from among the service users who conduct online product transactions. In this way, the information processing device 100 can provide the operator with an objective evaluation of a specific service user who conducts online product transactions.

[0046] Furthermore, the information processing device 100 may, upon request from the operator OP, perform a verification process of the values ​​set by the operator OP. Figure 4 is a diagram showing an overview of the information processing in response to a value verification request according to the embodiment.

[0047] As shown in Figure 4, after setting the product category, values, and description of values, the operator OP operates the verification button OB-2 located on the setting screen G-1. In response to the operation of the verification button OB-2, the terminal device 10 transmits a value verification request to the information processing device 100, along with the information on the product category, values, and description of values ​​set by the operator OP.

[0048] When the information processing device 100 receives a verification request from the terminal device 10, it estimates the values ​​suggested by the content of each product review for the target product, similar to step S3 described above, and extracts the estimated values ​​as the reasons for selecting the target product. At this time, if there are unclassified product reviews that do not fall into any of the values ​​set by the operator OP, the information processing device 100 performs estimation of the values ​​suggested by the content of the unclassified product reviews. For example, the information processing device 100 can cause the generating AI to perform estimation of the values ​​suggested by the content of the unclassified product reviews by including an additional list showing the correspondence between values ​​not set by the operator OP and explanations of those values ​​in the purchase decision factor list included in the "system prompt" of the instruction information P (see, for example, Figure 2) input to the generating AI. The information processing device 100 then provides the operator OP with information indicating the results of the verification process by transmitting it to the terminal device 10.

[0049] The terminal device 10 displays the number of product reviews corresponding to the values ​​set by the operator OP, the number of unclassified product reviews, and information on newly detected values ​​from the content of the unclassified product reviews as information J-2 indicating the verification results on the inspection result display screen G-2. This allows the information processing device 100 to support the operator OP in setting values.

[0050] Furthermore, if the information processing device 100 includes a time condition for identifying a time series as a content generation condition, it may generate statistical information showing the time-series changes in the aggregated results of values ​​and generate content that includes each of the generated statistical pieces of information. Figure 5 is a diagram showing an example of content showing the time-series changes in values ​​according to the embodiment. Figure 5 also shows an example of content for analyzing the time-series changes in the reasons for selecting a target product by purchasers on a service user basis (consumer axis). As a result, the information processing device 100 can provide the operator OP with information showing the changes in the reasons for selection over time as a trend in the reasons for selecting a product when purchasing it.

[0051] The information processing device 100 can generate content C4 shown in Figure 5 by, for example, receiving user segment conditions and time conditions from the operator OP as content generation conditions. For example, the operator OP can receive the content shown in Figure 5 by specifying service users who follow Company X's official account as the user segment condition, and specifying the start: "January 2023", end: "December 2023", and interval: "each month" as the time conditions. Similar to content C4 shown in Figure 5, the information processing device 100 can generate content for analyzing the time-series changes in the reasons for selecting a target product on a product-by-product basis (product axis). This allows the information processing device 100 to provide the operator OP with information showing how the reasons for selecting a product change over time.

[0052] Furthermore, the information processing device 100 may combine the aggregated results of values ​​extracted as reasons for selecting products purchased by specific service users with information on the specific service users' reactions to advertising creatives to generate content showing the relationship between the trends in determinants estimated to be important when a specific service user decides to purchase a product and the trends in reactions to advertising creatives, and provide this content to the operator OP. Figure 6 is a diagram showing an example of content showing the relationship between the determinants of product purchases of a specific service user and their reactions to advertising creatives according to the embodiment. A specific service user is identified by user segment conditions and, for example, is a service user who follows the official account of Company X.

[0053] Content C5, shown in Figure 6, includes classification items that categorize specific service users based on their purchasing decisions, such as "High Cost-Performance Segment," "High Quality Segment," "High Brand Segment," "High Design Segment," and "High Functionality Segment." For example, the "High Cost-Performance Segment" refers to users who prioritize cost performance over other purchasing decisions. Similarly, the "High Quality Segment" refers to users who prioritize quality, the "High Brand Segment" refers to users who prioritize brand, the "High Design Segment" refers to users who prioritize design, and the "High Functionality Segment" refers to users who prioritize functionality.

[0054] Content C5 in Figure 6 lists the advertising creatives with the highest click-through rates (an example of "response information") among service users for each tier. For example, the advertising creative with the highest click-through rate among users in the "high cost-performance tier" is "Creative CA". Similarly, Content C5 in Figure 6 also shows the advertising creatives with the highest click-through rates among users in the "high quality tier", "high brand tier", "high design tier", and "high functionality tier".

[0055] In this way, the information processing device 100 can provide the operator OP with information showing the relationship between the trends in determinants that a particular service user is estimated to consider important when deciding to purchase a product, and the trends in responses to advertising creatives. While the response information shown here is the click-through rate, this example is not limited to this; the number of clicks or the average number of clicks could also be used.

[0056] Figure 7 shows another example of content illustrating the relationship between the determinants of product purchases by a specific service user according to the embodiment and their response to advertising creatives. Content C5 in Figure 7 shows information regarding the click-through rate for each top tier and the click-through rate for the advertising creative as a whole, for each advertising creative.

[0057] Specifically, for example, Content C5 shows statistical information regarding Creative CA, including the average click-through rate of service users belonging to the "high cost-performance tier," the average click-through rate of service users belonging to the "high quality tier," the average click-through rate of service users belonging to the "high brand tier," the average click-through rate of service users belonging to the "high design tier," and the average click-through rate of service users belonging to the "high functionality tier," as well as the average click-through rate of service users for Creative CA. Note that Content C5 does not have to be limited to the display format shown in Figure 7, and may also be composed in the form of a heatmap showing the click information of the top tier for each ad creative.

[0058] In this way, the information processing device 100 can provide the operator OP with information that allows them to quickly grasp the differences in responses from higher-level audiences for each advertising creative. While the response information shown here is the average click-through rate, this example is not limited to this; the average number of clicks, for example, could also be used.

[0059] [2. System Configuration] The configuration of the information processing system SYS according to this embodiment will be described in detail below with reference to Figure 8. Figure 8 is a diagram showing an example of the system configuration of the information processing system SYS according to this embodiment.

[0060] As shown in Figure 8, the information processing system SYS according to this embodiment includes a terminal device 10 and an information processing device 100. Note that Figure 8 is merely an example of the configuration of the information processing system SYS according to this embodiment, and it may also have other devices such as a service provision device that performs information processing related to a portal site that provides various online services, including e-commerce services.

[0061] The terminal device 10 and the information processing device 100 are connected to the network N (see, for example, Figure 8) by wired or wireless means, respectively. The terminal device 10 and the information processing device 100 can communicate with other devices through the network N.

[0062] Network N includes, for example, WANs (Wide Area Networks) such as the Internet, and mobile communication networks such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: 5th Generation Mobile Communication System).

[0063] The terminal device 10 connects to the network N via a mobile communication network or short-range wireless communication such as Bluetooth® or Wi-Fi (Local Area Network), and can communicate with other devices such as the information processing device 100 through the network N.

[0064] Furthermore, the terminal device 10 is used by the operator OP. The terminal device 10 may typically be a notebook PC (Personal Computer), a desktop PC, a smartphone, or a tablet PC. The Operator (OP) analyzes transaction status in an e-commerce service where various goods can be traded online. The Operator (OP) may, for example, be a business that lists its own products on the e-commerce service. The e-commerce service in the embodiments described below is assumed to be a marketplace-type platform.

[0065] Furthermore, the terminal device 10 may have a user-specific application program (hereinafter referred to as "dedicated app") installed that provides various functions to the operator OP. The operator OP can access the information processing device 100 by operating the dedicated app. The operator OP can also access the information processing device 100 using the web browser installed on the terminal device 10.

[0066] Furthermore, the terminal device 10 can display information received from the information processing device 100 (for example, content C1 to C6). When the terminal device 10 receives control information from the information processing device 100 to realize the information display process via a dedicated application or web browser, it realizes the display process according to the control information.

[0067] Control information is described using, for example, scripting languages ​​such as JavaScript (registered trademark), stylesheet languages ​​such as CSS (Cascading Style Sheets), programming languages ​​such as Java (registered trademark), or markup languages ​​such as HTML (HyperText Markup Language). Alternatively, a predetermined application distributed from the information processing device 100 may be considered as control information.

[0068] The information processing device 100 is managed by the service provider operating the e-commerce service. As information processing for the embodiment, the information processing device 100 uses various information accumulated through the provision of the e-commerce service to generate and provide content that shows the trends in the reasons why the target products to be processed are selected by purchasers.

[0069] The information processing device 100 is typically a server device, but it may also be implemented as a mainframe or workstation. Furthermore, when the information processing device 100 is implemented as a server device, it may be implemented as a single server device, or as a cloud system in which multiple server devices and multiple storage devices work together.

[0070] [3. Equipment configuration] Hereinafter, an example of the functional configuration of the information processing device 100 in the information processing system SYS according to the embodiment will be described using Figure 9. Figure 9 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Figure 9, the information processing device 100 has a communication unit 110, a storage unit 120, and a control unit 130.

[0071] (Communications Department 110) The communication unit 110 is implemented, for example, by a communication module or a NIC (Network Interface Card). The communication unit 110 is connected to the network N by wire or wireless connection. The information processing device 100 transmits and receives information with other devices, such as the terminal device 10, through the network N.

[0072] For example, the communication unit 110 can receive setting information regarding product categories, values, and descriptions of values ​​transmitted from the terminal device 10. The communication unit 110 then passes the received setting information to the control unit 130.

[0073] Furthermore, for example, the communication unit 110 can transmit to the terminal device 10 information indicating candidate values ​​(for example, information J-1 shown in Figure 1), various contents generated by the control unit 130 (for example, contents C1 to C5, etc.), and verification results of the value settings.

[0074] (Storage unit 120) The storage unit 120 stores, for example, programs and data used for control and calculations by the control unit 130. For example, the storage unit 120 can be implemented using semiconductor memory elements such as RAM (Random Access Memory) or flash memory, or storage devices such as hard disks or optical discs. For example, the storage unit 120 includes a product information storage unit 121, a user information storage unit 122, and an advertising information storage unit 123. Note that the storage unit 120 is not particularly limited to the example shown in Figure 9, and can appropriately store data necessary for executing the information processing according to the embodiment.

[0075] (Product information storage unit 121) The product information storage unit 121 stores product information related to products provided to service users in the e-commerce service. Figure 10 is a diagram showing an overview of the product information stored in the product information storage unit 121 according to this embodiment.

[0076] As shown in Figure 10, the product information stored in the product information storage unit 121 has multiple fields, such as "product ID," "category," and "review information." These fields of product information are interconnected.

[0077] The "Product ID" field stores the unique identifier assigned to each product to identify it. The "Category" field stores information indicating the product category to which the product belongs. The "Product Reviews" field stores information about reviews posted for the product.

[0078] For example, when the information processing device 100 performs information processing according to the embodiment, it can utilize the product reviews stored in the product information storage unit 121.

[0079] (User information storage unit 122) The user information storage unit 122 stores user information relating to users of the EC service. Figure 11 is a diagram showing an overview of the user information stored in the user information storage unit 122 according to this embodiment.

[0080] As shown in Figure 11, the user information stored in the user information storage unit 122 has multiple items, such as "User ID," "Purchase History," "Posting History," and "Followed Accounts." These items in the user information are interconnected.

[0081] The "User ID" field stores identification information uniquely assigned to each service user to identify them. The "Purchase History" field stores information showing the service user's purchase history in the e-commerce service. The "Posting History" field stores information showing the service user's posting history of product reviews in the e-commerce service. The "Followed Accounts" field stores information showing the official accounts that the service user follows in the communication service.

[0082] When the information processing device 100 performs information processing according to the embodiment, it can utilize information such as purchase history and official account information stored in the user information storage unit 122.

[0083] (Advertising information storage unit 123) The advertising information storage unit 123 stores advertising information related to advertisements delivered to users of the e-commerce service. Figure 12 is a diagram showing an overview of the advertising information stored in the advertising information storage unit 123 according to this embodiment.

[0084] As shown in Figure 12, the advertising information stored in the advertising information storage unit 123 has multiple items, such as an "advertising ID," an "creative," and an "click information" item. These items in the advertising information are interconnected.

[0085] The "Ad ID" field stores unique identifiers assigned to each ad to identify it. The "Creative" field stores information indicating the ad creative used for the ad. The "Click Information" field stores information about clicks on the ad creative. This click information includes the user ID of the service user who clicked on the ad creative and the number of clicks on the ad creative.

[0086] When the information processing device 100 performs information processing according to the embodiment, it can utilize information related to clicks on advertising creatives stored in the advertising information storage unit 123.

[0087] (Control unit 130) The control unit 130 is a controller, and is realized by the execution of various programs (an example of an "information processing program") stored in the memory device inside the information processing device 100 by a CPU (Central Processing Unit) or MPU (Micro Processing Unit), using RAM as the working area.

[0088] Furthermore, the control unit 130 may be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a GPGPU (General Purpose Graphic Processing Unit).

[0089] As shown in Figure 3, the control unit 130 includes a receiving unit 131, an acquisition unit 132, an extraction unit 133, a generation unit 134, and a providing unit 135. Each of these units realizes or executes the information processing functions and operations described below.

[0090] The control unit 130 may have multiple internal configurations divided into processing units that realize or execute the functions and operations of the information processing described below. Furthermore, the control unit 130 is not limited to the configuration shown in Figure 3, and may have other configurations as long as they perform the information processing described later, and may also have other functional units other than those shown in Figure 9, such as a verification unit that performs information processing in response to a value verification request.

[0091] (Reception desk 131) The reception unit 131 receives setting information from the operator OP regarding the product category to which the target product to be processed belongs among the products traded online, the values ​​to be analyzed, and the description of those values. For example, the reception unit 131 receives setting information regarding the product category, the values ​​to be analyzed, and the description of those values ​​from the communication unit 110. The reception unit 131 passes the product category information to the acquisition unit 132. The reception unit 131 also passes the information on the values ​​to be analyzed and the description of those values ​​to the extraction unit 133.

[0092] Furthermore, the reception unit 131 can receive content generation conditions set by the operator OP. For example, if the reception unit 131 receives content generation conditions from the communication unit 110, it passes the received content generation conditions to the generation unit 134.

[0093] Furthermore, when the reception unit 131 receives a verification request from the operator OP regarding the set values, it passes on to the extraction unit 133 information indicating that a verification request has been made, along with the values ​​to be analyzed and an explanation of those values.

[0094] (Acquisition part 132) The acquisition unit 132 acquires product reviews (an example of "posted information") posted for target products belonging to the product category received by the reception unit 131. For example, the acquisition unit 132 refers to the product information stored in the product information storage unit 1221 and acquires information on product reviews posted for products belonging to the product category received from the reception unit 131. The acquisition unit 132 then passes the acquired product review information to the extraction unit 133.

[0095] (Extraction part 133) The extraction unit 133 estimates the values ​​suggested by the content of each product review based on the content of the product reviews acquired by the acquisition unit 132 and the explanation of values, and extracts the estimated values ​​as the reasons why the target product is selected by the buyer.

[0096] For example, the extraction unit 133 can use artificial intelligence (AI) to extract the reasons for selecting a target product. Specifically, the extraction unit 133 inputs product review information and instruction information (see Figure 2, for example) that instructs the artificial intelligence to extract the reasons for purchasing the target product, and for each product review, it can obtain an inference result from the artificial intelligence regarding the values ​​suggested by the content of the product review.

[0097] Furthermore, when the extraction unit 133 receives a verification request from the operator OP from the reception unit 131, it can perform a verification process to verify the values ​​set by the operator OP. At this time, if the extraction unit 133 detects an unclassified product review that does not fall into any of the values ​​set by the operator OP, it can perform an estimation of the values ​​suggested by the content of the unclassified product review. The extraction unit 133 then passes the verification results of the verification process to the provision unit 135. If an unclassified product review is detected during the verification process, the verification results will include information about the unclassified product review.

[0098] (Generation unit 134) The generation unit 134 generates a first content (see, for example, Figure 1) that shows the trend of the reasons for selecting the target product, based on the aggregated results of values ​​extracted by the extraction unit 133 as reasons for selecting the target product and pre-set content generation conditions. The generation unit 134 may receive the content generation conditions in advance from the operator OP, or it may receive them along with setting information regarding the product category, values, and descriptions of values.

[0099] The generation unit 134 can, for example, accept conditions as content generation conditions for analyzing the trends in the reasons why a target product is selected by a purchaser on a product-by-product basis (product axis). For example, the generation unit 134 can accept a condition as content generation conditions that the products are manufactured and sold by a certain home appliance manufacturer, Company A. In this case, the generation unit 134 can generate first content that includes statistical information showing the average value based on product reviews for each product manufactured and sold by Company A.

[0100] Furthermore, the generation unit 134 can also accept multiple conditions as content generation conditions for analyzing the trends in the reasons why a target product is selected by a purchaser, on a product-by-product basis (product axis). In this case, the generation unit 134 can generate statistical information for each of the multiple different conditions accepted as content generation conditions, and generate a first content containing each of the generated statistical information.

[0101] For example, the generation unit 134 can accept, as the first content generation condition, the condition that each product is manufactured and sold by a certain home appliance manufacturer, Company A, and as the second content generation condition, the condition that each product is distributed throughout the entire home appliance manufacturer industry to which Company A belongs. In this case, the generation unit 134 can generate first content that includes statistical information showing the average value based on product reviews of each product manufactured and sold by Company A, and statistical information showing the average value based on product reviews of each product distributed throughout the entire home appliance manufacturer industry. As a result, the information processing device 100 can provide the operator OP with information that can be compared under different conditions regarding the reasons for selecting the target product.

[0102] Furthermore, the generation unit 134 may generate multiple first content items with different display modes that can be switched between and displayed.

[0103] Furthermore, if the content generation conditions include time conditions for identifying a time series, the generation unit 134 can generate statistical information showing the time-series changes in values ​​and generate a first content (see, for example, Figure 5) that includes the generated statistical information.

[0104] Furthermore, the generation unit 134 may generate a second content (see, for example, Figure 3) that shows the trends of determinants estimated to be important when a specific service user makes a purchase decision, using the aggregated results of values ​​extracted as reasons for selection for each product purchased by a specific service user selected from among the service users who conduct online product transactions. In this case, the generation unit 134 accepts user segment conditions from the operator OP to specify a particular service user. User segment conditions may include gender, age or age group, price range of the products purchased, and whether or not the user follows official accounts established in the communication service.

[0105] For example, if the generation unit 134 receives user segment conditions from operator OP, such as condition 1 that the operator OP follows an official account established in the communication service by company X where the operator OP works, and condition 2 that the operator follows one of the official accounts of companies in the same industry as company A, it can generate second content (see Figure 3) that includes statistical information showing the average value based on product reviews for products purchased by each service user who follows company A's official account, and statistical information showing the average value based on product reviews for products purchased by each service user who follows one of the official accounts of companies in the same industry as company A.

[0106] Furthermore, the generation unit 134 may generate content that shows the relationship between the trends in determinants that a particular service user is estimated to consider important when deciding to purchase a product and the trends in responses to advertising creatives, by combining the aggregated results of values ​​extracted as reasons for selecting a product purchased by a particular service user with information on the response of that particular service user to advertising creatives.

[0107] (Provider 135) The providing unit 135 provides the first content generated by the generation unit 134. For example, the providing unit 135 can provide the first content generated by the generation unit 134 to the operator OP by transmitting it to the terminal device 10 via the communication unit 110.

[0108] Furthermore, the providing unit 135 provides the second content generated by the generation unit 134. For example, the providing unit 135 can provide the second content generated by the generation unit 134 to the operator OP by transmitting it to the terminal device 10 via the communication unit 110.

[0109] Furthermore, the provisioning unit 135 may provide the operator with information indicating candidate values ​​(for example, information J-1 shown in Figure 1) according to the product category set by the operator OP. The provisioning unit 135 can, for example, store information on product categories, values, and descriptions of values ​​set by each operator OP up to date, and from the stored information, it can acquire values ​​that were set together with the product category set by the operator OP as setting candidates. The provisioning unit 135 can provide the operator OP with information indicating candidate values ​​by transmitting it to the terminal device 10 via the communication unit 110.

[0110] Furthermore, the providing unit 135 can provide the operator OP with information indicating the results of the verification process received from the extraction unit 133. For example, the providing unit 135 can provide the operator OP with information indicating the results of the verification process by transmitting it to the terminal device 10 via the communication unit 110.

[0111] Furthermore, the provisioning unit 135 can provide the operator OP with content (see, for example, Figure 6 or Figure 7) that shows the relationship between the trends in determinants estimated to be important to a specific service user when deciding to purchase a product and the trends in responses to the advertising creative, by combining the aggregated results of values ​​extracted as reasons for selecting a product purchased by a specific service user with information on the specific service user's response to the advertising creative. The provisioning unit 135 can provide such content to the operator OP by transmitting it to the terminal device 10 via the communication unit 110.

[0112] [4. Processing procedure according to the embodiment] The following describes the processing procedure of the information processing device 100 according to the embodiment, using Figure 13 as an example. Figure 13 is a flowchart of an example of the processing procedure of the information processing device executed by the information processing device according to the embodiment. The processing procedure shown in Figure 13 is executed by the control unit 130 of the information processing device 100. The processing procedure shown in Figure 13 is executed repeatedly while the information processing device 100 is running.

[0113] As shown in Figure 13, the reception unit 131 receives setting information from the operator OP regarding the setting of product categories, values, and descriptions of values ​​(step S101).

[0114] Furthermore, the acquisition unit 132 acquires product reviews posted for target products belonging to the product category (step S102).

[0115] Furthermore, the extraction unit 133 estimates the values ​​suggested by the content of each product review based on the content of the product review and the explanation of the values, and extracts the estimated values ​​as the reasons why the target product is selected by the buyer (step S103).

[0116] Furthermore, the generation unit 134 generates first content that shows the trends in the reasons for selecting the target product, based on the aggregated results of values ​​and pre-set content generation conditions (step S104).

[0117] Furthermore, the provisioning unit 135 provides the generated first content to the operator OP by transmitting it to the terminal device 10 via the communication unit 110 (step S105), and then terminates the processing procedure shown in Figure 13.

[0118] [5. Hardware Configuration] Furthermore, the information processing device 100 according to the above embodiment can be implemented by a computer 1000 having a configuration such as that shown in Figure 14. Figure 14 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device 100 according to the embodiment.

[0119] 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.

[0120] 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.

[0121] The output IF1060 is an interface for transmitting information to be output to output devices 1010, such as monitors and printers, and is implemented using connectors of standards such as USB (Universal Serial Bus), DVI (Digital Visual Interface), and HDMI (High Definition Multimedia Interface). The input IF1070 is an interface for receiving information from various input devices 1020, such as mice, keyboards, and scanners, and is implemented using, for example, USB.

[0122] The input device 1020 may also be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), DVD (Digital Versatile Disc), or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), tape media, magnetic recording media, or semiconductor memory. Furthermore, the input device 1020 may be an external storage medium such as a USB memory stick.

[0123] Network IF1080 receives data from other devices via network N and sends it to the arithmetic unit 1030, and also transmits data generated by the arithmetic unit 1030 to other devices via network N.

[0124] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0125] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the arithmetic unit 1030 of the computer 1000 realizes the same functions as the control unit 130 by executing a program (for example, an information processing program) loaded on the primary storage device 1040. That is, the arithmetic unit 1030 realizes the processing by the information processing device 100 according to the embodiment in cooperation with the program (for example, an information processing program) loaded on the primary storage device 1040.

[0126] [6. Others] In the above embodiment, an example of information processing in which the information processing device 100 posts a proxy comment has been described, but it is not limited to this example. For example, the information processing device 100 may select a proxy, and the selected proxy may create and post the proxy comment.

[0127] Of the processes described in the above embodiments, 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 documents and drawings can be changed at will unless otherwise specified.

[0128] 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, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0129] Furthermore, the embodiments described above can be combined as appropriate, provided that the processing content is not contradictory.

[0130] Although embodiments of the present 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 other forms with modifications and improvements based on the knowledge of those skilled in the art, starting with the embodiments described in the disclosure section of the invention.

[0131] Furthermore, the terms "section, module, unit" mentioned above can be replaced with "means" or "circuit," etc. For example, a control unit can be replaced with a control means or a control circuit.

[0132] [7. Effects] The information processing device 100 according to this embodiment includes a reception unit 131, an acquisition unit 132, an extraction unit 133, a generation unit 134, and a provision unit 135. The reception unit 131 receives from the operator the product category to which the target product belongs, the values ​​to be analyzed, and a description of those values. The acquisition unit 132 acquires posted information for the target product belonging to the accepted product category. The extraction unit 133 estimates the values ​​suggested by the content of each piece of posted information based on the content of the acquired posted information and the description of the values, and extracts the estimated values ​​as the reasons why the target product is selected by the purchaser. The generation unit 134 generates first content showing the trends in the reasons for selecting the target product based on the aggregated results of the values ​​extracted as reasons for selecting the target product and pre-set content generation conditions. The provision unit 135 provides the generated first content to the operator.

[0133] Therefore, the information processing device 100 according to this embodiment can provide the operator OP with an objective evaluation of the trends in the reasons why online traded goods are selected by buyers.

[0134] Furthermore, the generation unit 134 can generate statistical information based on the aggregated value results for each of the multiple different conditions accepted as content generation conditions, and generate a first content including each of the generated statistical information. As a result, the information processing device 100 can provide the operator OP with comparative information that extracts trends in the reasons why online traded products are selected by buyers from different perspectives.

[0135] Furthermore, if the content generation conditions include time conditions for identifying a time series, the generation unit 134 can generate statistical information showing the time-series changes in values ​​and generate first content including the generated statistical information. As a result, the information processing device 100 can provide the operator OP with information showing the trend of reasons for selecting a product over time.

[0136] Furthermore, the generation unit 134 can generate second content that shows the trends of determinants that a specific service user is estimated to consider important when deciding to purchase a product, using the aggregated results of values ​​extracted as reasons for selection for each product purchased by a specific service user selected from among the service users who conduct online product transactions. The provision unit 135 can provide the second content generated by the generation unit 134. As a result, the information processing device 100 can provide the operator OP with an objective evaluation of the determinants that a specific service user is estimated to consider important when deciding to purchase a product traded online.

[0137] Furthermore, the generation unit 134 can generate statistical information based on the aggregated results of values ​​for each user segment condition used to specify a group of users consisting of multiple specific service users, and generate a second content containing each of the generated statistical pieces of information. As a result, the information processing device 100 can provide the operator OP with comparable information by extracting trends in determinants that are estimated to be important when a specific service user who purchases goods traded online makes a purchase decision, from different perspectives.

[0138] Furthermore, if the content generation conditions include time conditions for identifying a time series, the generation unit 134 can generate statistical information showing the time-series changes in values ​​and generate a second content including each of the generated statistical pieces of information. As a result, the information processing device 100 can provide the operator OP with information showing the changes over time in the reasons for selection, as a trend of the determinants that a particular service user is estimated to consider important when deciding to purchase a product.

[0139] Furthermore, the provisioning unit 135 can provide the operator with information indicating candidate value settings according to the product category set by the operator. This allows the information processing device 100 to support the operator OP in setting values.

[0140] Furthermore, the extraction unit 133 can perform a verification process to verify the values ​​set by the operator OP in response to a request from the operator OP. In addition, the provision unit 135 can provide the operator OP with information indicating the results of the verification process.

[0141] Furthermore, the effects described above can also be achieved by any combination of the processes performed by each of the parts described above, or by any combination of the processes performed by each of the parts. [Explanation of Symbols]

[0142] SYS Information Processing System N Network 10 Terminal devices 100 Information Processing Devices 110 Communications Department 120 Storage section 121 Product information storage section 122 User information storage unit 123 Advertising Information Storage Unit 130 Control Unit 131 Reception Department 132 Acquisition Department 133 Extraction part 134 Generation part 135 Provision Department

Claims

1. A reception unit that receives setting information from operators regarding the product category to which the target product to be processed belongs among the products traded online, the values ​​to be analyzed, and the setting of the description of said values, An acquisition unit that acquires posted information for target products belonging to the aforementioned product category that are received by the aforementioned reception unit, An extraction unit that, based on the content of the posted information acquired by the acquisition unit and the description of the values, estimates the values ​​suggested by the content of the posted information from each of the posted information, and extracts the estimated values ​​as the reasons why the target product is selected by the purchaser. A generation unit generates first content that shows the trends of the reasons for selecting the target product, based on the aggregated results of the values ​​extracted by the extraction unit as reasons for selecting the target product and pre-set content generation conditions, A providing unit that provides the first content generated by the generation unit to the operator. An information processing device characterized by comprising:

2. The generating unit is For each of the multiple different conditions accepted as content generation conditions, statistical information based on the aggregated results of the values ​​is generated, and the first content including each of the generated statistical information is generated. The information processing apparatus according to feature 1.

3. The generating unit is If the content generation conditions include time conditions for identifying a time series, statistical information showing the time-series changes of the values ​​is generated, and the first content including the generated statistical information is generated. The information processing apparatus according to feature 2.

4. The generating unit is For each product purchased by a specific user selected from among users who conduct online product transactions, a second content is generated that shows the trends of the determinants estimated to be important to the specific user when deciding to purchase the product, using the aggregated results of the values ​​extracted as reasons for selection. The aforementioned supply unit is, The second content generated by the generation unit is provided to the operator. The information processing apparatus according to feature 1.

5. The generating unit is For each user segment condition used to specify a group of users consisting of multiple specific users, statistical information based on the aggregated results of the values ​​is generated, and the second content is generated that includes each of the generated statistical information. The information processing apparatus according to feature 4.

6. The generating unit is If the content generation conditions include time conditions for identifying a time series, statistical information showing the time-series changes of the values ​​is generated, and the second content is generated, which includes each of the generated statistical pieces. The information processing apparatus according to feature 4.

7. The aforementioned supply unit is, Information indicating candidate values ​​to be set by the operator is provided to the operator according to the product category set by the operator. The information processing apparatus according to feature 1.

8. The extraction unit is In response to a request from the operator, a verification process is performed to verify the values ​​set by the operator. The aforementioned supply unit is, Information indicating the results of the verification process is provided to the operator. The information processing apparatus according to feature 1.

9. A method of information processing performed on a computer, A receiving process in which the operator receives setting information regarding the product category to which the product to be processed belongs among the products traded online, the values ​​to be analyzed, and the setting of a description of said values, A collection step to obtain posted information for target products belonging to the product category received through the aforementioned acceptance step, An extraction step is performed to estimate the values ​​suggested by the content of the posted information obtained in the acquisition step and the description of the values, from each of the posted information, and to extract the estimated values ​​as the reasons for selection by the purchaser of the target product. A generation step generates first content that shows the trends of the reasons for selecting the target product, based on the aggregated results of the values ​​extracted as reasons for selecting the target product by the extraction step and pre-set content generation conditions, A provisioning step to provide the first content generated by the generation step to the operator. An information processing method characterized by including

10. On the computer, A receiving procedure for receiving setting information from an operator regarding the product category to which the product to be processed belongs among the products traded online, the values ​​to be analyzed, and the setting of a description of said values, A procedure for obtaining posted information for target products belonging to the aforementioned product category that are accepted by the aforementioned acceptance procedure, An extraction procedure which, based on the content of the posted information obtained by the acquisition procedure and the description of the values, estimates the values ​​suggested by the content of the posted information from each of the posted information, and extracts the estimated values ​​as the reasons why the target product is selected by the purchaser; A generation procedure for generating first content that shows the trends of the reasons for selecting the target product, based on the aggregated results of the values ​​extracted as reasons for selecting the target product by the extraction procedure and pre-set content generation conditions, A provisioning procedure for providing the first content generated by the generation procedure to the operator. An information processing program characterized by causing the execution of [a specific action].

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