Information processing device and information processing method

Abstract

To enhance the appeal of product proposals. [Solution] The information processing device 1 includes a reception unit 133 that receives product inquiries from a user terminal 2, a first acquisition unit 134 that refers to a product DB 121 that stores product information and acquires product information for the product corresponding to the inquiry, a identification unit 135 that refers to a customer service method DB 122 that stores customer service method information for each of multiple products, which associates multiple products with products related to each of the multiple products, identifies customer service method information corresponding to the product indicated by the acquired product information, and identifies related products related to the product indicated by the product information based on the identified customer service method information, a second acquisition unit 136 that refers to the product DB 121 and acquires product information corresponding to related products, and an output unit 138 that outputs the product information acquired by the first acquisition unit 134 and the product information acquired by the second acquisition unit 136 to the user terminal 2.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus and an information processing method.

Background Art

[0002] In recent years, systems for chatting with users using large language models (LLMs) have been provided. For example, Patent Document 1 discloses a system that conducts conversations with users and proposes products to the users.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional method of proposing products using large language models, in response to a product inquiry from a user, it simply stops at introducing the product. Therefore, like a store clerk who is good at selling products, in addition to the specifications such as the size of the product in response to an inquiry from the user, explanations such as how to use the product that can make the user recall the usage image of the product and lead to higher purchasing motivation are added for the proposal, or products other than the product in response to an inquiry from the user are also proposed, and it is required to enhance the appeal power at the time of product proposal.

[0005] Therefore, the present invention has been made in view of these points, and an object thereof is to enhance the appeal power at the time of product proposal.

Means for Solving the Problems

[0006] A first aspect of the present invention is an information processing device. This information processing device includes: a reception unit that receives inquiries about products from a user terminal used by a user; a first acquisition unit that refers to a product database that stores product information for each of a plurality of products and acquires product information for the product corresponding to the inquiry; a specification unit that refers to a customer service method database that stores customer service method information for each of a plurality of products, which associates a plurality of products with products related to each of the plurality of products, and identifies customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit, and identifies related products related to the product indicated by the product information acquired by the first acquisition unit based on the identified customer service method information; a second acquisition unit that refers to the product database and acquires product information corresponding to the related products identified by the specification unit; and an output unit that outputs the product information acquired by the first acquisition unit and the product information acquired by the second acquisition unit to the user terminal.

[0007] The first acquisition unit may acquire product information for a product corresponding to an inquiry by inputting the inquiry into a large-scale language model that can refer to the product database and the customer service method database, and acquiring a response from the large-scale language model that includes the product information corresponding to the inquiry. The identification unit may identify customer service method information corresponding to a product indicated by the product information acquired by the first acquisition unit by inputting instruction information into the large-scale language model that instructs the large-scale language model to acquire customer service method information corresponding to the product acquired by the first acquisition unit, and acquiring a response from the large-scale language model that includes customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit. The second acquisition unit may acquire product information corresponding to a related product by inputting instruction information into the large-scale language model that instructs the large-scale language model to acquire product information corresponding to a related product identified by the identification unit, and acquiring a response from the large-scale language model that includes the product information.

[0008] The information processing device may have a generation unit that generates the response text by receiving instruction information from the large-scale language model, which instructs the large-scale language model to create a response text corresponding to the inquiry, which includes the product information obtained by the first acquisition unit and the product information obtained by the second acquisition unit, and prompts the purchase of the product indicated by the product information obtained by the first acquisition unit and related products indicated by the product information obtained by the second acquisition unit, and the output unit may output the response text generated by the generation unit.

[0009] The customer service method information may be associated with employee identification information for identifying the employee who performed the customer service corresponding to the customer service method, and the identification unit may identify the employee identification information associated with the identified customer service method information, and may associate the identified employee identification information with usage records indicating that the customer service method information was used.

[0010] The customer service method database may store customer service method information in association with attribute information indicating the attributes of a user corresponding to the customer service method corresponding to the customer service method information, and the identification unit may identify the attributes of a user using the user terminal and, by referring to the customer service method database, identify customer service method information corresponding to the identified user's attributes and the product indicated by the product information acquired by the first acquisition unit.

[0011] The identifying unit may identify the user's attributes by having a large-scale language model estimate the user's attributes based on the dialogue history between the large-scale language model and the user using the user terminal.

[0012] The information processing device may include an extraction unit that acquires text information indicating statements made by store employees in a store, and extracts text information corresponding to customer service methods from the acquired text information, and a storage control unit that stores the text information extracted by the extraction unit as customer service method information in the customer service method database.

[0013] The memory control unit may identify the category of goods or services handled by the store clerk, identify the category of goods or services corresponding to the extracted text information, and, on the condition that the category of goods or services handled by the store clerk matches the category of goods or services corresponding to the extracted text information, store the extracted text information in the customer service method database as customer service method information.

[0014] The extraction unit may extract information for identifying a product from the acquired text information, and the storage control unit may associate the information for identifying a product extracted by the extraction unit with text information corresponding to a customer service method and store it in the customer service method database as customer service method information.

[0015] The memory control unit may refer to user information, which is a combination of user identification information for identifying each of a plurality of users and attribute information indicating the user's attributes, identify the attribute information associated with the user identification information of a user served by a store employee at the store, and store the customer service method information and the identified attribute information in the customer service method database.

[0016] A second aspect of the present invention is an information processing method. This information processing method includes the steps of: receiving an inquiry about a product from a user terminal used by a user, which is executed by a computer; referring to a product database that stores product information for each of a plurality of products and obtaining product information for the product corresponding to the inquiry; referring to a customer service method database that stores customer service method information for each of a plurality of products, which associates the plurality of products with products related to each of the plurality of products, identifying customer service method information corresponding to the product indicated by the obtained product information, and identifying related products related to the product indicated by the obtained product information based on the identified customer service method information; referring to the product database and obtaining product information corresponding to the identified related products; and outputting the obtained product information for the product corresponding to the inquiry and the obtained product information corresponding to the related products to the user terminal. [Effects of the Invention]

[0017] According to the present invention, the appeal of a product when it is proposed can be enhanced. [Brief explanation of the drawing]

[0018] [Figure 1] This is a diagram illustrating the overview of an information processing device. [Figure 2] This diagram shows the functional configuration of an information processing device. [Figure 3] This figure shows an example of a product database. [Figure 4] This figure shows an example of a customer service method database. [Figure 5] This is a sequence diagram showing the process flow in which an information processing device provides product information. [Modes for carrying out the invention]

[0019] [Overview of Information Processing Device 1] FIG. 1 is a diagram showing an overview of the information processing apparatus 1. The information processing apparatus 1 is a computer for serving users who use a store in a store or the like that sells products. The information processing apparatus 1 is communicably connected to a user terminal 2 used by the user.

[0020] First, the information processing apparatus 1 receives an inquiry about a product from the user ((1) in FIG. 1). The information processing apparatus 1 refers to a product DB (database) that stores product information about each of a plurality of products, and acquires the product information of the product corresponding to the inquiry ((2) in FIG. 1).

[0021] The information processing apparatus 1 refers to a customer service method DB that stores customer service method information regarding a customer service method corresponding to a product that associates a product with related products related to the product, and identifies the customer service method information corresponding to the product indicated by the acquired product information ((3) in FIG. 1). The information processing apparatus 1 identifies related products related to the product corresponding to the inquiry based on the identified customer service method information ((4) in FIG. 1).

[0022] The information processing apparatus 1 refers to the product DB and acquires the product information of the identified related products ((5) in FIG. 1). The information processing apparatus 1 outputs the product information of the product and the related products to the user terminal 2 ((6) in FIG. 1). By doing so, the information processing apparatus 1 can propose not only the specifications such as the size of the product in response to the inquiry from the user, but also explanations such as how to use the product that can lead the user to recall the usage image of the product and enhance the purchase intention, or can also propose products other than the product in response to the inquiry from the user. Therefore, the information processing apparatus 1 can enhance the appeal power when proposing products.

[0023] [Functional Configuration of Information Processing Apparatus 1] Subsequently, the functions of the information processing apparatus 1 will be described. FIG. 2 is a diagram showing the functional configuration of the information processing apparatus 1. The information processing apparatus 1 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0024] The communication unit 11 is a communication interface for sending and receiving data with external devices such as the user terminal 2 via a communication network such as the internet or a mobile phone line. The memory unit 12 is a storage medium for storing various types of data, and includes ROM (Read Only Memory), RAM (Random Access Memory), and hard disks. The memory unit 12 stores programs to be executed by the control unit 13. The memory unit 12 stores programs that cause the control unit 13 to function as an extraction unit 131, a memory control unit 132, a receiving unit 133, a first acquisition unit 134, a specific unit 135, a second acquisition unit 136, a generation unit 137, and an output unit 138.

[0025] Furthermore, the storage unit 12 stores the product DB 121 and the customer service method DB 122. The product DB 121 is a database that stores product information for each of multiple products, and is configured to be accessible by the large-scale language model described later. Specifically, the product DB 121 stores product identification information for identifying products in association with product information. Figure 3 is a diagram showing an example of the product DB 121. As shown in Figure 3, the product DB 121 stores product codes as product identification information, and product information such as product names, product categories, product prices, sizes, product descriptions including how to use the product and usage scenarios, and product images, in association with each other.

[0026] The Customer Service Method DB122 is a database that stores customer service method information corresponding to each of several products, and accumulates customer service method information based on statements made by store staff. Like the Product DB121, the Customer Service Method DB122 is configured to allow referencing of the large-scale language model described later. The Customer Service Method DB122 stores customer service method information that associates multiple products with products related to each of those products.

[0027] Figure 4 shows an example of the customer service method DB122. As shown in Figure 4, the customer service method DB stores a customer service method ID (Identification) for identifying a customer service method, a customer service method associated with at least two products, and a staff member ID for identifying the staff member who suggested the customer service method. Here, it is assumed that the customer service method is associated with at least two product categories in order to associate at least two products, but it is not limited to this, and at least two products may be associated by including at least two product names or product codes.

[0028] The control unit 13 is, for example, a CPU (Central Processing Unit). By executing the program stored in the storage unit 12, the control unit 13 functions as an extraction unit 131, a storage control unit 132, a reception unit 133, a first acquisition unit 134, a specification unit 135, a second acquisition unit 136, a generation unit 137, and an output unit 138.

[0029] [Customer service method information registration] First, let's explain the function for registering customer service method information. The extraction unit 131 and the memory control unit 132 work together to register customer service method information based on statements made by store employees in the store into the customer service method database.

[0030] Specifically, the extraction unit 131 acquires text information indicating what the store clerk said in the store. For example, a store clerk may be fitted with a microphone, and a storage device (not shown) may be provided that converts the audio information indicating the voice picked up by the microphone into text information, and stores the converted text information in association with a store clerk ID to identify the clerk wearing the microphone. The extraction unit 131 accesses the storage device and acquires the text information indicating what the clerk said and the store clerk ID. Then, the extraction unit 131 extracts from the acquired text information text information corresponding to the customer service method and product identification information which is information for identifying products.

[0031] For example, the extraction unit 131 inputs a prompt to the large-scale language model instructing it to include the acquired text information, classify the text information into customer service methods, product information, and other information, and to extract one or more product identification information from the text information classified as customer service methods. The extraction unit 131 then acquires the text information classified as customer service methods and one or more product identification information, as classified by the large-scale language model, thereby extracting the text information corresponding to customer service methods and the product identification information from the acquired text information. Here, the extraction unit 131 may extract the product category associated with the product identification information instead of the product identification information.

[0032] The memory control unit 132 stores the text information extracted by the extraction unit 131 in the customer service method DB 122 as customer service method information. Specifically, first the memory control unit 132 identifies the category of products handled by the store clerk. For example, the memory unit 12 stores store clerk information that associates the store clerk's clerk ID with the category of products handled by the clerk. The memory control unit 132 refers to the store clerk information and identifies the category associated with the clerk ID obtained by the extraction unit 131, thereby identifying the category of products handled by the clerk.

[0033] Furthermore, the memory control unit 132 identifies the product category corresponding to the extracted text information. If multiple product identification pieces are extracted from the text information, the memory control unit 132 identifies the category corresponding to each of the multiple product identification pieces. For example, the memory control unit 132 identifies the category included in the product information indicated by the product identification piece corresponding to the extracted text information.

[0034] Then, the memory control unit 132 stores the extracted text information as customer service method information in the customer service method DB 122, provided that the category of product handled by the store clerk matches the category of product corresponding to the extracted text information.

[0035] For example, if multiple product identification pieces are extracted from the text information, the memory control unit 132 stores the multiple product identification pieces extracted by the extraction unit 131, along with the customer service method information and the employee ID, in the customer service method DB 122, provided that the category of the product handled by the employee matches at least one of the categories corresponding to each of the multiple product identification pieces. Here, the memory control unit 132 may also store the customer service method DB 122 by associating the category of each of the multiple products extracted by the extraction unit 131 with the customer service method information and the employee ID. Furthermore, if the customer service method information includes multiple product identification pieces or categories for each of the multiple products, the memory control unit 132 may associate the customer service method information with the employee ID and store it in the customer service method DB 122, thereby associating the product identification information with the customer service method information. In this way, the information processing device 1 can register the customer service methods of experienced employees who are familiar with handling products as customer service method information in the customer service method DB 122.

[0036] Furthermore, the memory control unit 132 may store customer service method information in the customer service method DB 122 on the condition that the employee is a veteran employee accustomed to customer service. In this case, for example, the memory unit 12 stores the employee ID and the employee's level of proficiency in customer service in association with each other. The level of proficiency may be determined based on, for example, the user's length of time handling the product, evaluations of the customer service from other users, and the user's job rank at the store. Here, the level of proficiency may be determined based on the number of positive evaluations received from other users regarding the customer service method information, or based on the number of times the customer service method information has been viewed.

[0037] Then, if multiple product identification pieces are extracted from the text information, the memory control unit 132 stores the customer service method information in the customer service method DB 122, provided that the category of the product handled by the store clerk matches at least one of the categories corresponding to each of the multiple product identification pieces, and the store clerk's skill level is above a predetermined skill level. In this way, the information processing device 1 can register only refined customer service method information in the customer service method DB 122.

[0038] Furthermore, the memory control unit 132 may refer to user information that associates a user ID, which is user identification information for identifying each of several users who have used the store, with attribute information that indicates the user's attributes, and identify the attribute information associated with the user ID of a user who was served by a store employee at the store.

[0039] In this case, the user's user ID and the user's attribute information are associated and stored in the storage unit 12. Furthermore, in the storage device that stores text information converted from audio collected by a microphone attached to the store clerk, the user ID of the user served by the clerk is associated and stored with this text information. The user ID may be read from, for example, a point card or membership card presented by the user when purchasing goods at the store.

[0040] The memory control unit 132 identifies the user ID stored in the storage device in association with the text information acquired by the extraction unit 131, and identifies the attribute information associated with that user ID, thereby identifying the attribute information associated with the user ID of the user served by the store clerk at the store. Then, the memory control unit 132 associates the customer service method information extracted from the text information acquired by the extraction unit 131 with the identified attribute information and stores it in the customer service method DB 122. In this way, the information processing device 1 can store customer service method information that has a high probability of being effective for the attribute of the user who received the customer service method, in association with the attribute of that user.

[0041] [Providing product information] Next, we will explain the function that provides product information in response to product inquiries from users. The reception unit 133, the first acquisition unit 134, the identification unit 135, the second acquisition unit 136, the generation unit 137, and the output unit 138 work together to output product information for a product to the user terminal 2 in response to product inquiries received from the user terminal 2.

[0042] Figure 5 is a sequence diagram showing the processing flow of the information processing device 1 providing product information. The function of providing product information will be explained below, with reference to Figure 5 as appropriate.

[0043] First, the reception unit 133 receives product inquiries from the user terminal 2 used by the user (S1). For example, the reception unit 133 receives product inquiries from the user terminal 2 via a web page operated by a store or a business that provides product information services for providing product information.

[0044] The first acquisition unit 134 refers to the product database 121, which stores product information for each of multiple products, and acquires product information for the product corresponding to the inquiry. For example, the first acquisition unit 134 inputs the inquiry received by the reception unit 133 into a large-scale language model that can refer to the product database 121 and the customer service method database 122 (S2).

[0045] For example, if the inquiry received by the reception unit 133 is "What parasol do you recommend?", the first acquisition unit 134 inputs the inquiry into the large-scale language model. The large-scale language model accesses the product database 121 to search for product information and retrieves the product information corresponding to the inquiry (S3).

[0046] For example, if the inquiry received by the reception unit 133 is "What parasol do you recommend?", the large-scale language model acquires the following product information corresponding to the inquiry: Parasol A as a product name and a description of Parasol A, and Parasol B as a product name and a description of Parasol B. The large-scale language model may also acquire information different from the descriptions included in the product information. The large-scale language model outputs the response containing the acquired product information to the information processing device 1 (S4). The first acquisition unit 134 acquires the product information of the product corresponding to the inquiry by acquiring the response containing the product information corresponding to the inquiry output from the large-scale language model.

[0047] The identification unit 135 refers to the customer service method DB 122, identifies customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit 134, and identifies related products related to the product indicated by the product information acquired by the first acquisition unit 134 based on the identified customer service method information. For example, the identification unit 135 inputs a prompt to the large-scale language model instructing it to acquire customer service method information corresponding to the product information acquired by the first acquisition unit 134 (S5).

[0048] The large-scale language model accesses the customer service method DB122 based on the input prompt to retrieve customer service method information and obtains customer service method information corresponding to the product information obtained by the first acquisition unit 134 (S6). The large-scale language model outputs the response containing the acquired customer service method information to the information processing device 1 (S7).

[0049] For example, if the first acquisition unit 134 acquires the product name Parasol A and its description, and the product name Parasol B and its description, as product information, the identification unit 135 generates a prompt such as "Refer to the customer service method DB and acquire the customer service methods corresponding to Parasol A and Parasol B," and inputs this prompt into the large-scale language model. The identification unit 135 identifies the customer service method information corresponding to the product indicated by the product information by acquiring a response from the large-scale language model that includes customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit 134. Then, based on the identified customer service method information, the identification unit 135 identifies related products that are associated with the product indicated by the product information acquired by the first acquisition unit 134 (S8).

[0050] For example, if the first acquisition unit 134 acquires the product name "Parasol A" and its description, and the product name "Parasol B" and its description, as product information, the identification unit 135 identifies customer service information such as "When a customer searches for parasols or sunscreen, mention neck coolers as recommended products." Then, based on the identified customer service information, the identification unit 135 identifies neck coolers as related products to Parasol A and Parasol B.

[0051] Here, the identification unit 135 may identify the employee ID associated with the identified customer service method information and associate the identified employee ID with usage records indicating that the customer service method information was used. In this way, the information processing device 1 can evaluate the employee indicated by the employee ID based on the use of the customer service method information.

[0052] Furthermore, if the customer service method DB 122 has attribute information indicating the attributes of the user corresponding to the customer service method associated with the customer service method, the identification unit 135 may identify the attributes of the user using the user terminal 2.

[0053] The identification unit 135 may also identify the user's attributes by having the large-scale language model estimate the user's attributes based on the interaction history between the large-scale language model and the user using the user terminal 2.

[0054] For example, the storage unit 12 stores the dialogue history between the large-scale language model and the user using the user terminal 2, associated with the user ID. The dialogue history may include not only the direct dialogue history between the large-scale language model and the user, but also the dialogue history between the large-scale language model and the user using the user terminal 2 via the information processing device 1.

[0055] The identification unit 135 acquires the conversation history between the large-scale language model and the user using user terminal 2 based on the user's user ID. The identification unit 135 then includes the acquired conversation history and generates a prompt such as, "Using the following chat content between the AI ​​and the customer, infer and extract the customer's preferences and characteristics and profile them," and inputs this prompt into the large-scale language model. The large-scale language model estimates the user's attributes based on the input prompt and outputs them to the information processing device 1. By acquiring the user's attributes output from the large-scale language model, the identification unit 135 obtains the user's attributes based on the conversation history between the large-scale language model and the user using user terminal 2.

[0056] Then, the identification unit 135 refers to the customer service method DB 122 to identify customer service method information corresponding to the attributes of the identified user and the product indicated by the product information acquired by the first acquisition unit 134. In this way, the information processing device 1 can identify effective customer service method information for the user.

[0057] The second acquisition unit 136 refers to the product information and acquires product information corresponding to the related product identified by the identification unit 135. For example, the second acquisition unit 136 inputs a prompt to the large-scale language model instructing it to acquire product information corresponding to the related product identified by the identification unit 135 (S9). Based on the input prompt, the large-scale language model accesses the product DB 121, searches for product information, and acquires product information corresponding to the prompt, i.e., product information corresponding to the related product (S10). The large-scale language model outputs a response containing the acquired product information to the information processing device 1 (S11). The second acquisition unit 136 acquires product information corresponding to the related product by acquiring the response containing the product information output from the large-scale language model.

[0058] If the identification unit 135 identifies a neck cooler as a related product, the second acquisition unit 136 generates a prompt such as, "Get product information for neck coolers," and inputs this prompt into the large-scale language model. The second acquisition unit 136 then retrieves product information for neck coolers from the large-scale language model as product information corresponding to the related product.

[0059] The generation unit 137 inputs a prompt to the large-scale language model instructing it to create a response document that responds to a user inquiry, including the product information acquired by the first acquisition unit 134 and the product information acquired by the second acquisition unit 136, which encourages the purchase of the product indicated by the product information acquired by the first acquisition unit 134 and related products indicated by the product information acquired by the second acquisition unit 136 (S12). The large-scale language model generates a response document that responds to a user inquiry, including the product information acquired by the first acquisition unit 134 and the product information acquired by the second acquisition unit 136, and outputs the response document to the information processing device 1 (S13). The second acquisition unit 136 acquires the response document output from the large-scale language model.

[0060] For example, the generation unit 137 generates a prompt such as, "Based on the descriptions of parasol A, parasol B, and neck cooler, create a sentence that encourages the user to purchase parasol A or parasol B and the neck cooler together," and inputs this prompt into the large-scale language model. The second acquisition unit 136 then retrieves a response sentence from the large-scale language model that corresponds to the user's inquiry.

[0061] The output unit 138 outputs the product information acquired by the first acquisition unit 134 and the product information acquired by the second acquisition unit 136 to the user terminal 2. Specifically, the output unit 138 outputs to the user terminal 2 a response document generated by the generation unit 137, which includes the product information acquired by the first acquisition unit 134 and the product information acquired by the second acquisition unit 136 (S14).

[0062] [Effects of Information Processing Device 1] As described above, when the information processing device 1 according to this embodiment receives an inquiry about a product from the user terminal 2, it refers to the product DB 121 to obtain product information for the product corresponding to the inquiry, and refers to the customer service method DB 122, which stores customer service method information for each of the multiple products, associating multiple products with products related to each of the multiple products, and identifies the customer service method information corresponding to the product indicated by the obtained product information. Then, based on the identified customer service method information, the information processing device 1 identifies related products related to the product indicated by the product information, refers to the product DB 121 to obtain product information corresponding to the related products, and outputs the product information for the product corresponding to the inquiry and the product information for the related products to the user terminal 2. In this way, the information processing device 1 can enhance the appeal when proposing products.

[0063] Furthermore, this invention will make it possible to contribute to Goal 9 of the United Nations-led Sustainable Development Goals (SDGs), "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation."

[0064] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of its gist. For example, all or part of the apparatus can be configured by functionally or physically distributing and integrating in any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combinations are combined with the effects of the original embodiments. [Explanation of symbols]

[0065] 1. Information Processing Device 2 User terminals 11 Communications Department 12 Storage section 13 Control Unit 131 Extraction part 132 Memory Control Unit 133 Reception Department 134 First acquisition part 135 Specific part 136 Part 2 137 Generation Department 138 Output Department

Claims

1. A reception desk that receives product-related inquiries from user terminals used by users, A first acquisition unit retrieves product information for a product that corresponds to the query by referring to a product database that stores product information for each of multiple products, A customer service method database is used to store customer service method information for each of the multiple products, which is a database that stores customer service method information for each of the multiple products, which is a database that associates multiple products with products related to each of the multiple products, and the first acquisition unit identifies the customer service method information corresponding to the product indicated by the product information obtained by the first acquisition unit, and the identification unit identifies related products related to the product indicated by the product information obtained by the first acquisition unit based on the identified customer service method information, A second acquisition unit obtains product information corresponding to the related products identified by the identification unit by referring to the aforementioned product database, An output unit that outputs the product information acquired by the first acquisition unit and the product information acquired by the second acquisition unit to the user terminal, An information processing device having

2. The first acquisition unit inputs the inquiry into a large-scale language model that can refer to the product database and the customer service method database, and acquires the product information of the product corresponding to the inquiry by obtaining the response output from the large-scale language model, which includes the product information corresponding to the inquiry. The identification unit inputs instruction information to the large-scale language model instructing it to acquire customer service method information corresponding to the product information acquired by the first acquisition unit, and acquires a response from the large-scale language model that includes customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit, thereby identifying the customer service method information corresponding to the product indicated by the product information acquired by the first acquisition unit. The second acquisition unit inputs instruction information to the large-scale language model that instructs the acquisition of product information corresponding to the related product identified by the identification unit, and acquires the product information corresponding to the related product by acquiring the response containing the product information output from the large-scale language model. The information processing apparatus according to claim 1.

3. The generation unit receives instruction information from the large-scale language model that instructs it to create a response document corresponding to the inquiry, which includes the product information acquired by the first acquisition unit and the product information acquired by the second acquisition unit, and prompts the purchase of the product indicated by the product information acquired by the first acquisition unit and related products indicated by the product information acquired by the second acquisition unit, and generates the response document by acquiring the response document from the large-scale language model. The output unit outputs the response text generated by the generation unit. The information processing apparatus according to claim 2.

4. The customer service method information is associated with employee identification information for identifying the employee who performed the customer service corresponding to the customer service method. The identification unit identifies employee identification information associated with the identified customer service method information, and associates the identified employee identification information with usage records indicating that the customer service method information was used. The information processing apparatus according to claim 1.

5. The customer service method database stores customer service method information and attribute information indicating user attributes corresponding to the customer service method corresponding to the customer service method information, in association with each other. The identification unit identifies the attributes of the user using the user terminal, and by referring to the customer service method database, identifies customer service method information corresponding to the attributes of the identified user and the product indicated by the product information acquired by the first acquisition unit. The information processing apparatus according to claim 1.

6. The identification unit identifies the user's attributes by having the large-scale language model estimate the user's attributes based on the dialogue history between the large-scale language model and the user using the user terminal. The information processing apparatus according to claim 5.

7. An extraction unit that acquires text information representing statements made by store employees in a store, and extracts text information corresponding to customer service methods from the acquired text information, A storage control unit that stores the text information extracted by the extraction unit as customer service method information in the customer service method database, Having, The information processing apparatus according to claim 1.

8. The memory control unit identifies the category of goods or services handled by the store clerk, identifies the category of goods or services corresponding to the extracted text information, and stores the extracted text information in the customer service method database as customer service method information, provided that the category of goods or services handled by the store clerk matches the category of goods or services corresponding to the extracted text information. The information processing apparatus according to claim 7.

9. The extraction unit extracts information for identifying the product from the acquired text information, The memory control unit associates the information for identifying the product extracted by the extraction unit with text information corresponding to the customer service method, and stores it in the customer service method database as the customer service method information. The information processing apparatus according to claim 7.

10. The memory control unit refers to user information which is a combination of user identification information for identifying each of several users and attribute information indicating the user's attributes, identifies the attribute information associated with the user identification information of a user served by a store employee at the store, and stores the customer service method information and the identified attribute information in the customer service method database. The information processing apparatus according to claim 7.

11. A computer executes Steps for receiving product inquiries from the user's terminal, The steps include: referring to a product database that stores product information for each of multiple products, and obtaining product information for the product corresponding to the query; The process involves referring to a customer service method database that stores customer service method information corresponding to each of multiple products, which associates multiple products with related products, identifying the customer service method information corresponding to the product indicated by the acquired product information, and then identifying related products related to the product indicated by the acquired product information based on the identified customer service method information. The steps include: referring to the aforementioned product database and obtaining product information corresponding to the identified related product; The steps include outputting product information for the product corresponding to the acquired inquiry and product information for the acquired related product to the user terminal, An information processing method having

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