Information processing device, information processing method, and program

Abstract

To provide an information processing device, an information processing method, and a program capable of making suitable recommendations related to electronic payment. [Solution] An information processing device for an electronic payment service provided in cooperation between an application program running on a user terminal device and a payment server that communicates with the application program, comprising: an information acquisition unit that acquires a user's usage history of the application program and the user's payment history; an identification unit that identifies one or more personas that represent the user's personality based on at least the usage history and the payment history; and a content provision unit that provides content corresponding to the identified personas to the user terminal device.

Description

[Technical Field]

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

[0002] Electronic payment services using terminal devices are becoming widespread. Electronic payment services provide recommendations tailored to the preferences of users. In order to understand these user preferences, attempts have been made to identify personas that represent the user's personality. In this regard, Patent Document 1 discloses an invention that generates persona information based on user reaction information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2023 / 233852 Summary of the Invention [Problem to be solved by the invention]

[0004] In the invention described in Patent Document 1, information related to electronic payments is not used as the source information for generating personas, so there are cases where it is not possible to make suitable recommendations related to electronic payments.

[0005] The present invention has been made in consideration of these circumstances, and one of its objects is to provide an information processing device, an information processing method, and a program that are capable of making suitable recommendations related to electronic payments. [Means for solving the problem]

[0006] One aspect of the present invention is an information processing device that, in an electronic payment service provided in cooperation between an application program running on a user terminal device and a payment server that communicates with the application program, comprises: an information acquisition unit that acquires a user's usage history of the application program and the user's payment history; an identification unit that identifies one or more personas that represent the user's personality based on at least the usage history and the payment history; and a content provision unit that provides content corresponding to the identified personas to the user terminal device. [Effects of the Invention]

[0007] According to one aspect of the present invention, it is possible to provide suitable recommendations related to electronic payments. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 illustrates basic aspects of brick-and-mortar electronic payment. [Figure 2] FIG. 1 is a diagram illustrating an example of a configuration for performing electronic payment (terminal payment) using a payment application. [Figure 3] FIG. 10 is a diagram showing an example of the contents of user information 172. [Figure 4] FIG. 10 is a diagram showing an example of the contents of affiliated store / shop information 174. [Figure 5] FIG. 10 is a diagram showing an outline of a processing flow when a user scan is performed. [Figure 6] FIG. 10 is a diagram showing an outline of the processing flow when a store scan is performed. [Figure 7] FIG. 1 is a diagram showing an example of a configuration for performing electronic payment (card payment) using a payment card. [Figure 8] FIG. 2 is a diagram illustrating functions of an information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] [overview] Hereinafter, with reference to the drawings, embodiments of an information processing device, an information processing method, and a program according to the present invention will be described. The information processing device operates in conjunction with an electronic payment service and provides customized information to users of the electronic payment service. The information processing device identifies a persona representing a user's personality based on information collected in connection with the electronic payment service, and provides the user with information corresponding to the identified persona. The electronic payment service is provided through collaboration between at least an application program and a payment server. The information processing device may be a device included in the payment server (i.e., a function of the payment server) or a device that communicates with the payment server. In the following description, the application program will be referred to as a payment app. The electronic payment service is a service that supports payments for the purchase of goods and services at a store. A store is, for example, a physical store (real store) existing in real space, but may also include a virtual store for e-commerce transactions. The virtual store may be provided by an entity other than the operator of the electronic payment service. In this case, control is exercised to transition to an interface screen for the electronic payment service when making a payment for a purchase at the virtual store. In electronic payment services, stores are treated as belonging to, for example, affiliated stores (brands), and when a purchase is made at a store, processing such as payment is primarily carried out between the user and the affiliated store. Alternatively, processing such as payment may be carried out between the user and the store. First, an overview of the electronic payment service will be explained, followed by an explanation of the functions of the information processing device.

[0010] [Electronic payment methods at brick-and-mortar stores] FIG. 1 illustrates the basic aspects of brick-and-mortar electronic payments. Electronic payments are generally carried out by three parties: a medium M held by a user U, store equipment E, and a payment system S. The medium M may be a portable computer device such as a smartphone or a credit card. The store equipment E resides in a physical store (hereinafter simply referred to as the store) in real space and may include a POS device, a wireless communication device, a credit card reader, a printed code image such as a QR Code (registered trademark), or a display device displaying the code image. In brick-and-mortar electronic payments, information that can identify the user and information about the payment amount are first shared unidirectionally or bidirectionally between the medium M and the store equipment E. At this time, either the medium M or the store equipment E optically reads various information from a code image displayed by the other, provides information via near-field communication (NFC), or reads the PAN (primary account number) using a credit card reader. Then, either the medium M or the store equipment E (the party that obtains information from the other) transmits the payment information required for the payment to the payment system S via a network NW. Both the medium M and the store equipment E may send some information to the payment system S. The payment system S manages various information about the user U and performs electronic payments between the store and the user U in various ways. Electronic payments are performed using either or both of a prepaid system and a postpaid system, or by other methods. In addition, electronic payments may also include so-called online shopping, which is performed between the user's terminal device and the payment system. The network NW includes, for example, the Internet, a LAN (Local Area Network), a wireless base station, a provider device, etc. The various devices that communicate via the network NW, which will be described below, are assumed to have communication devices such as network cards and wireless communication modules.

[0011] [Configuration (Terminal Payment)] 2 is a diagram showing an example of the configuration for performing electronic payment (terminal payment) using a payment app. This electronic payment is performed mainly by a payment app 20 running on a user terminal device 10, which is one of the media M, one or more store payment terminals 30 and one or more store code images 40, which are one of the store facilities E, and a payment server 100, which constitutes part of a payment system S. The payment server 100 communicates with the user terminal device 10, the store payment terminal 30, and one or more information terminals 50 via a network NW.

[0012] The user terminal device 10 is a portable terminal device such as a smartphone or tablet. The user terminal device 10 is a computer device having at least an optical reading function, a communication function, a display function, an input acceptance function, and a program execution function. In the following description, components for realizing these functions are referred to as a camera, a communication device, a touch panel, a central processing unit (CPU), etc. In the user terminal device 10, a processor such as a CPU executes a payment application 20, which operates in cooperation with a payment server 100 to provide electronic payment services to users. The payment application 20 is installed on the user terminal device 10 from, for example, an application distribution server (not shown) and controls the camera, communication device, touch panel, etc. of the user terminal device 10. In the following description, the terms "send information to the user terminal device 10 (or receive / acquire information from the user terminal device 10)" and "send information to the payment application 20 (or receive / acquire information from the payment application 20)" may be used interchangeably, but these terms are merely different expressions and are not intended to distinguish between them.

[0013] The store payment terminal 30 is installed, for example, in a store. The store payment terminal 30 is a computer device (or a collection of these) that has at least a product price acquisition function, an optical reading function, a program execution function, and a communication function. The store payment terminal 30 includes a so-called POS (Point of Sale) device, and the POS device may have a product price acquisition function and an optical reading function.

[0014] The store code image 40 is placed in a store and is a code image such as a QR code (registered trademark) printed on a paper or plastic medium. The store code image 40 may be displayed on a display placed in the store (or on a display of a terminal device such as a smartphone or tablet terminal).

[0015] The information terminal 50 is used by the operator of the affiliated store who oversees the stores. In electronic payment services, customers who provide goods or services are treated as affiliated stores (brands), and one or more stores exist under the affiliated store. An affiliated store may operate only one store. The information terminal 50 is a smartphone, tablet terminal, personal computer, etc. An affiliated store interface 55 runs on the information terminal 50. The affiliated store interface 55 may be an affiliated store app or a web page displayed by a general-purpose browser. The affiliated store interface 55 accepts coupon settings and the like from the affiliated store operator and transmits them to the payment server 100. By executing the affiliated store interface 55, the information terminal 50 may have the function of displaying a code image corresponding to the store code image 40 or reading a code image displayed by the user terminal device 10 (in the latter case, an optical reading function is required).

[0016] The payment server 100 communicates with the credit card server 200 via a network NW. The payment server 100 includes, for example, a content provider 110, an information manager 120, a payment processor 130, an information acquirer 140, an identifier 150, and a memory 170. The components other than the memory 170 are realized by a hardware processor such as a CPU executing a program (software). Some or all of these components may be implemented using a large scale integration (LSI), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like. The program may be realized by hardware (including circuitry) such as a Gate Array (GPU) or a Graphics Processing Unit (GPU), or may be realized by a combination of software and hardware. The program may be stored in advance in a storage device (a storage device with a non-transitory storage medium) such as a hard disk drive (HDD) or flash memory, or may be stored in a removable storage medium (a non-transitory storage medium) such as a DVD or CD-ROM, and installed in the storage device by inserting the storage medium into a drive device.

[0017] The storage unit 170 is a HDD, flash memory, RAM (Random Access Memory), etc. The storage unit 170 may be a NAS (Network Attached Storage) device that the payment server 100 can access via a network. The storage unit 170 stores information such as user information 172, affiliated store / shop information 174, and persona reference data 176.

[0018] The content providing unit 110 has, for example, a web server function, and provides information (content) for displaying various screens of the electronic payment service to the user terminal device 10. The content providing unit 110 provides the content to the user terminal device 10 in the form of a web page, and provides the user terminal device 10 with parameters required for the payment application 20 to render images. The content providing unit 110 also delivers content customized according to a persona identified for each user, as will be described later.

[0019] The information management unit 120 edits, adds, deletes, etc., user information 172 and affiliated store / shop information 174, and manages them.

[0020] 3 is a diagram showing an example of the contents of user information 172. User information 172 is information in which, for example, user URL, account ID, phone number, password, registration date, charge balance, electronic money type, terminal payment method, card payment method, various history information, identity verification flag, name, address, date of birth, email address, bank account, deferred payment settings, deferred payment condition information, etc. are associated with each other. Hereinafter, a user instance (electronic payment account) in which this information is associated may be referred to as an account. In the figure, items marked with "-" indicate that they are not set.

[0021] The user URL is used for remittance processing between users. When registering for the electronic payment service, registration of a phone number and password is required. The account ID is issued to the user by the payment server 100. The registration date is the date on which the user registered for the electronic payment service (the date on which the account was created). The charge balance is information indicating the balance of electronic money that the user has set by transferring money to the account in advance. Remittance methods include depositing money into an ATM (Automatic Teller Machine) of a designated service provider (bank) or transferring money from a registered bank account. The type of electronic money is information indicating, for example, whether the electronic money can be withdrawn or can only be used for electronic payments. The terminal payment method is setting information indicating whether the user will make electronic payment using the charge balance (balance payment) or by deferred payment in terminal payment. The card payment method is setting information indicating whether the user will make electronic payment using the charge balance (balance payment) or by deferred payment in card payment. The various history information includes a charge history, which is a history of the user transferring money to the electronic payment service in advance to increase the charge balance, and a payment history, which shows the details of each payment made by the user (date and time, store ID of the store where the purchase was made, affiliated store ID, payment amount, payment method, payment method, etc.). The various history information also includes a usage history of the payment app 20, such as the functions used in the payment app 20, the frequency of sessions, and the duration of sessions. A session is a period of time during which the payment app 20 is used. The start and end timings of a session may be determined arbitrarily.

[0022] The identity verification flag is information indicating whether or not the user has completed identity verification using an ID document. Deferred payment can be selected if identity verification has been completed, and the user with account ID "002" in the figure has not completed identity verification and can only select balance payment as the terminal payment method. The bank account is the account number of a bank account that can be used to deposit funds into the electronic payment service. Deferred payment settings is information indicating whether or not the settings have been completed to make deferred payment selectable. Deferred payment condition information is information indicating various conditions such as the deferred payment limit and the amount used for the current month.

[0023] 4 is a diagram showing an example of the contents of affiliated store / store information 174. The affiliated store / store information 174 includes, for example, a first table 174A in which an affiliated store ID and a store ID are associated with a store URL, a second table 174B in which an affiliated store ID is associated with an affiliated store name and sales amount (described above), and a third table 174C in which a store ID is associated with a store ID. In addition to this information, the affiliated store / store information 174 may also include information such as the category of the affiliated store or store, the store's location, and payment patterns.

[0024] The payment processing unit 130 performs various processes for electronic payment. There are two methods for terminal payment: a first method (user scan) and a second method (store scan), which will be explained below.

[0025] FIG. 5 shows an overview of the process flow when a user scan is performed. First, the user terminal device 10, with the payment application 20 running, reads and decodes the store code image 40 using its optical reading function (S1). The store code image 40 contains store URL information. The payment application 20 sends first payment information, including the store URL and the user's account ID, to the payment server 100 (S2). The payment server 100 searches the affiliated store / store information 174 using the affiliated store ID and store ID corresponding to the store URL, acquires information about the affiliated store name and store name (S3), and sends this to the payment application 20 (S4). The user enters the payment amount into the payment application 20 on the screen displaying the affiliated store name and store name (S5). The payment application 20 then generates second payment information including at least the payment amount and sends it to the payment server 100 (S6).

[0026] If the "Terminal Payment Method" in the user information 172 of the user is set to "Balance Payment," the payment processing unit 130 of the payment server 100 performs electronic payment based on the received second payment information (S7-1). At this time, the payment processing unit 130 performs electronic payment by, for example, decreasing the charge balance managed in association with the user ID and increasing the item value of the affiliated store's sales proceeds. The item value of the affiliated store's sales proceeds is not used as electronic money itself, for example, but rather the amount corresponding to the item value of the sales proceeds is transferred to a bank account in a cycle determined by an agreement between the affiliated store and the electronic payment service. On the other hand, if the "Terminal Payment Method" is set to "Deferred Payment," the payment processing unit 130 transmits the first payment information and the second payment information to the credit card server 200 to request electronic payment (S7-2). The credit card server 200 performs electronic payment by adding the payment amount to the user's monthly usage amount based on the received information and deducting the monthly usage amount from the user's bank account after the closing date (S7-3).

[0027] Then, the payment processing unit 130 sends a payment completion notice (information for displaying a payment completion screen) to the payment app 20 via the content providing unit 110 (S8), and the payment app 20 displays the payment completion screen (S9). When the store code image 40 is displayed on a display installed in the store, the store code image 40 may include information on the payment amount in addition to the store URL. In this case, the procedure for the user to input the payment amount is omitted, and the information on the payment amount is included in the first payment information and sent to the payment server 100. Information on the affiliated store name and store name may be included and displayed on the payment completion screen.

[0028] FIG. 6 is a diagram showing an overview of the processing flow when a store scan is performed. First, when the payment app 20 is launched, when a payment operation is performed using the payment app 20, when an automatic update timing (e.g., every minute) occurs, and at other timings, the payment app 20 sends a request to issue a one-time code to the payment server 100 (S11). The payment processing unit 130 of the payment server 100 generates a one-time code (S12) and sends it to the payment app 20 (S13). The payment app 20 displays a code image, such as a QR code or barcode, generated based on the one-time code (S14). The user holds (presents) the display surface of the user terminal device 10 over the store payment terminal 30, and the store payment terminal 30 reads and decodes the code image using its optical reading function to obtain the one-time code, etc. (S15). The store payment terminal 30 then generates payment information including the one-time code, payment amount, affiliated store ID, store ID, etc., and sends it to the payment server 100 (S16). The payment amount information is acquired in advance by reading a barcode or manually entering it.

[0029] The payment processing unit 130 of the payment server 100 identifies the user corresponding to the one-time code based on the received information, and if the "terminal payment method" in the user information 172 of the user is set to "balance payment," it performs electronic payment based on the received second payment information (S17-1). The processing content at this time is the same as the processing of S7-1 in FIG. 5. On the other hand, if the "terminal payment method" is set to "post-payment," the payment server 100 transmits the first payment information and the second payment information to the credit card server 200 to request electronic payment (S17-2). The credit card server 200 adds the payment amount to the user's monthly usage amount based on the received information, and performs electronic payment by deducting the monthly usage amount from the user's bank account after the closing date (S17-3).

[0030] Then, the payment processing unit 130 transmits a payment completion notification to the payment application 20 via the content providing unit 110 (S18), and the payment application 20 displays a payment completion screen (S19).

[0031] Note that electronic payment may be performed using only one of the above patterns. Furthermore, the "account ID" described in FIG. 2 may be other information (e.g., a phone number) that can be used as user identification information. Furthermore, issuing a one-time code may be omitted in store scanning, and the payment application 20 may display a code image generated based on the user's account ID. In this case, the payment server 100 identifies the user corresponding to the account ID instead of identifying the user corresponding to the one-time code.

[0032] It should be noted that the "post-payment" settlement may be performed within the settlement server 100, rather than being managed by the credit card server 200. In this case, the components such as the settlement card 60 and the credit card server 200 may be omitted.

[0033] [Configuration (Card Payment)] 7 is a diagram showing an example of a configuration for performing electronic payment (card payment) using a payment card. This electronic payment is performed mainly using a payment card 60, which is one of the media M, a credit card processing terminal 70, which is one of the store facilities E, a payment server 100, which constitutes part of a payment system S, and a credit card server 200. The credit card server 200 communicates with the credit card processing terminal 70 via a network NW.

[0034] The credit processing terminal 70 is installed in the store, similar to the in-store payment terminal 30. The credit processing terminal 70 includes, for example, a credit card reader and a POS device. The credit card terminal reads a personal identification number (PIN) from an inserted or held-up credit card and compares it with the PIN entered by the user. It also transmits a primary account number (PAN) read from the credit card to the credit card server 200 via the POS device. The POS device cooperates with the credit card terminal to transmit information such as the payment amount to the credit card server 200. A payment agent (acquirer) server may be interposed between the credit card processing terminal 70 and the credit card server 200; however, for simplicity, the following description omits the server. The payment card 60 is, for example, similar to a commonly used credit card, with a communication chip embedded in the card substrate. The communication chip incorporates a storage medium storing the PIN and communicates with an external device via a contactor (or a wireless antenna). Alternatively, the payment card 60 may be a magnetic card. The information (messages) sent and received when using a credit card include an authorization message for authentication and a sales message for conveying the payment amount, but detailed explanations distinguishing between these will be omitted below.

[0035] The credit card server 200 communicates with the payment server 100 via a network NW. The credit card server 200 includes, for example, an information management unit 210, a credit interface 220, a payment allocation unit 230, a credit payment processing unit 240, and a memory unit 270. The components other than the memory unit 270 are implemented by, for example, a hardware processor such as a CPU executing a program (software). Some or all of these components may be implemented by hardware (including circuitry) such as an LSI, ASIC, FPGA, or GPU, or may be implemented by a combination of software and hardware. The program may be stored in advance in a storage device such as an HDD or flash memory (a storage device with a non-transitory storage medium), or may be stored in a removable storage medium (a non-transitory storage medium) such as a DVD or CD-ROM, and installed in the storage device by inserting the storage medium into a drive device. The memory unit 270 stores information such as card user information 272.

[0036] The information management unit 210 edits, adds, deletes, etc., and manages the card user information 272. The card user information 272 is information in which, for example, information unique to a user (e.g., PAN), a card payment method, and the user's account ID (used by the payment server 100) are associated with one another. The card payment method is setting information that indicates whether the user will make electronic payment using the charged balance (balance payment) or deferred payment when making a card payment.

[0037] The credit interface 220 determines whether the BIN (Bank Identification Number) in the PAN included in the message received from the credit processing terminal 70 is a code for the company, and if it is a code for the company, passes the message received from the credit processing terminal 70 to the payment allocation unit 230, and if it is not a code for the company, discards the received message.

[0038] The payment allocating unit 230 refers to the card user information 272 of the user corresponding to the message obtained from the credit interface 220, and determines whether the "card payment method" is set to "post-payment." If the "card payment method" is set to "post-payment," the payment allocating unit 230 notifies the credit interface 220 of this and passes the message obtained from the credit interface 220 to the credit payment processing unit 240. On the other hand, if the "card payment method" is set to "balance payment," the payment allocating unit 230 adds the user's account ID to the message obtained from the credit interface 220 and sends it to the payment server 100, requesting electronic payment. When requested to make electronic payment, the payment server 100 performs the same processes as S7-1 in Figure 5 and S17-1 in Figure 6.

[0039] The credit interface 220 checks the PAN and expiration date, and verifies whether the cumulative payment amount exceeds the current month's upper limit, etc. The credit payment processing unit 240 adds the payment amount to the user's monthly usage amount based on the information contained in the message obtained from the payment allocation unit 230, and performs electronic payment by deducting the monthly usage amount from the user's bank account after the closing date.

[0040] [Information processing device] The functions of the information processing device realized by the content providing unit 110, the information acquiring unit 140, and the identifying unit 150 will be described below.

[0041] Information acquisition unit 140 acquires the user's payment application 20 usage history and the user's payment history in the electronic payment service, and stores them in storage unit 170 as persona reference data 176. Identification unit 150 identifies a persona that represents the user's personality based on persona reference data 176 that includes at least the payment application 20 usage history and payment history. Content provision unit 110 then provides content corresponding to the identified persona to user terminal device 10.

[0042] As shown in FIG. 2, the identification unit 150 inputs, for example, a prompt including persona reference data 176 and instruction information for identifying a persona into a large-scale language model (LLM) provided by an LLM (Large Language Model) server 300, and acquires the output of the LLM to identify the persona. LLM is known under names such as ChatGPT (registered trademark) and BERT, and is sometimes referred to as generative AI. The LLM divides input text data into tokens (morphemes), vectorizes them, and inputs the vectors into a trained model to return an answer based on the contextual understanding obtained. In the example of FIG. 2, the LLM is provided by an LLM server 300 separate from the payment server 100. However, the payment server 100 itself may be equipped with an LLM function. The identification unit 150 may perform processing using other reinforcement learning models in addition to the LLM.

[0043] Furthermore, the identification unit 150 may identify a persona that represents the user's profile by inputting the persona reference data 176 into an algorithm capable of adaptive learning, such as a multilateral bandit (MAB) algorithm, instead of (or in addition to) the LLM. Hereinafter, a model for identifying a persona, including the LLM or MAB algorithm, will be referred to as a persona classification model.

[0044] 8 is a diagram illustrating the functions of the information processing device. First, the information acquisition unit 140 acquires persona reference data 176. The persona reference data 176 may include other user information in addition to the usage history and payment history of the payment application 20. The other user information may include, for example, demographic information such as the user's date of birth, and past engagement information (including tracking indicators, which will be described later).

[0045] The identification unit 150 identifies a user's persona based on this persona reference data 176. The persona is selected, for example, from predetermined candidates (in this case, information on the candidates is provided to the persona classification model). For example, persona candidates such as gourmet, travel lover, saver, enjoyer, and fashion lover are prepared in advance. For example, because the engagement information in the other user information 176 is updated in real time, the identification of the persona by the identification unit 150 is also fine-tuned in real time.

[0046] The content providing unit 110 creates content personalized for the identified persona. For example, the content providing unit 110 generates content using the LLM or MAB algorithm, similar to the identifying unit 150. Hereinafter, a processing entity for content generation, including the LLM or MAB algorithm, is referred to as a content generation engine. The content generation engine receives real-time situation data and offer specification information along with persona information. The real-time situation data includes information such as the current time, location, and recent activity. The offer specification information indicates the content and conditions of offers available at affiliated stores or shops where the user makes purchases. The offer specification information is obtained from a database or service server that provides offers. The content generated by the content generation engine is categorized into categories such as usage status information, action suggestions, and offer information. Offers are customized within predefined parameters and dynamically selected based on the user's persona. This allows these offers to be included in personalized content.

[0047] The content provider 110 performs content validation to ensure that the content meets standards for quality, compliance, relevance, and legality, thereby preventing inappropriate content from being distributed to users.

[0048] Then, the content providing unit 110 selects a channel for delivering the content from among push notification, in-app message, email, SMS, etc. based on the user's preferences, context, and past interaction history (the user's past behavioral history in electronic payment services), and provides the content to the user terminal device 10 using the selected channel.

[0049] To provide feedback on user responses, the information acquisition unit 140 acquires engagement information as follows and adds it to the persona reference data 176. The engagement information is various information that indicates user responses to content. This allows the persona identified by the identification unit 150 and the personalization of the content provided to adapt over time and become more consistent with the user's preferences and behavior.

[0050] Engagement information includes tracking metrics such as click-through rate (CTR), conversion rate, open rate, time spent viewing content, and behavioral data. CTR is the rate at which users interact with a link or a predetermined action. Conversion rate is the rate at which a desired action, such as redeeming an offer or signing up for a service, is completed. Open rate is the rate at which users open push notifications, emails, or SMS. Time spent viewing content is the amount of time users spend viewing content (for example, the amount of time they spend reading an email or viewing an in-app message). Behavioral data includes in-app navigation patterns, frequency of interaction with a particular content type, and post-interaction transaction data. These tracking metrics provide a comprehensive view of user interactions, preferences, and changes in behavior over time. Incorporating tracking metrics and the real-time contextual data mentioned above into content generation enhances the feedback of content generation.

[0051] The persona classification model is updated using aggregated engagement information. It employs machine learning algorithms, such as reinforcement learning models and clustering algorithms, to improve the accuracy of persona identification. The persona classification model analyzes patterns in user behavior and interaction data to identify changes in preferences or the emergence of new behaviors, which can determine the need to create new personas or merge existing ones.

[0052] The content generation engine utilizes the updated personas and real-time situational data to improve the relevance and appeal of the content it generates, which may include fine-tuning the LLM to reflect updated user preferences and trends, and readjusting the parameters of the content generation engine to prioritize elements that increase engagement with similar users.

[0053] The persona classification model and content generation engine are periodically retrained based on the latest engagement information. An automated retraining schedule is established to ensure the model is always up-to-date based on ever-changing user characteristics. In addition to periodic retraining, retraining may also be initiated if a significant change in user behavior or engagement patterns is detected. After retraining, the performance of the updated model is evaluated based on pre-defined benchmarks, such as improved tracking metrics and increased persona classification accuracy. The evaluation process includes A / B testing with control and experimental groups.

[0054] Below, examples showing the results of operation of the information processing device are listed.

[0055] (Case 1) User A frequently orders food online and frequently uses the electronic payment service to pay at restaurants. Through interactions within the payment app 20, User A has also shown interest in food-related content and offers. In this case, based on User A's frequent interactions with food-related services, such as payment transactions (frequent food-related payments), app usage history (engagement with restaurant-related content), and other user information (demographic information), the identification unit 150 identifies User A's initial persona as "foodie." Based on the persona "foodie," the content generation engine in the content providing unit 110 then generates personalized discount offers for popular nearby restaurants. These offers are provided as content highlighting new menu items that match User A's past food preferences. When the content providing unit 110 detects that User A is near a restaurant during lunchtime, it sends the offer via a push notification. User A receives the push notification, clicks it, and uses the payment app 20 to order the new menu item at the restaurant. Then, the information acquisition unit 140 acquires tracking indicators such as the click-through rate (CTR) of the push notification, the conversion rate (orders at the restaurant), and the viewing time of the offer as tracking information, and adds them to the persona reference information 176. This provides feedback on the positive reaction, strengthening the persona classification of "gourmet." Furthermore, the content provision unit 110 fine-tunes the content preferences of user A, taking into account that user A responded favorably to the new menu.

[0056] (Case 2) User B's persona is identified as "Spendinger" due to his high transaction amounts for luxury goods and services. Recently, User B began using an electronic payment service for travel-related expenses, such as booking airline tickets and hotels. The persona classification model detects this change in User B's behavior and dynamically adjusts User B to the "Travel Lover" persona, while maintaining the characteristics of the "Spendinger" persona. The content generation engine generates a personalized travel guide highlighting luxury hotels and premium experiences in User B's next destination and provides it to the user terminal device 10. Based on User B's past travel booking patterns, the content generation engine also adjusts the delivery time of this content to coincide with when User B is likely planning a trip. User B then reads the travel guide and books the recommended luxury hotel using an electronic payment service. Tracking indicators include the time spent viewing the content and the booking conversion rate. Based on this, the persona classification model reinforces User B's new persona, "Travel Lover," and the content generation engine emphasizes User B's luxury preferences and adjusts future content to combine luxury travel experiences with exclusive offers.

[0057] (Case 3) User C frequently searches for discounts and deals, frequently purchases small items, and his consumption patterns indicate a preference for budget-friendly options. In this case, payment history (small, frequent purchases), app usage history (discount searches), and other user information (past engagement with budget-related content) are acquired as persona reference data 176, and User C's persona is identified as "Saver." The content generation engine generates a weekly summary of discount deals available through electronic payment services and provides the content to the user terminal device 10 at the start of the weekend, when User C is likely to shop. Subsequently, tracking metrics are acquired, such as the open rate of the weekly summary, the click rate of the deals, and the frequency of purchases after viewing the summary. The content generation engine constantly improves the deal selection process and generates content to ensure User C receives the most relevant and attractive offers that fit his or her budget.

[0058] (Case 4) User D frequently purchases movie tickets through an electronic payment service and subscribes to various streaming services. User D's engagement with content indicates a strong preference for leisure activities. In this case, User D's persona is identified as "Enjoyment Type" based on his payment history (entertainment-related purchases) and app usage history (frequent interaction with entertainment content). The content generation engine generates personalized content for upcoming movie premieres, including ticket discounts and promotions for related streaming services, and sends it to User D, for example, just before he makes his weekend entertainment plans. Subsequently, tracking metrics include ticket purchase conversion rates, streaming service subscription rates, and viewing time for related content. The persona classification model updates User D's persona to reflect his interest in new movies, and the content generation engine adjusts future content to focus on more upcoming entertainment events.

[0059] (Case 5) User E is increasingly using electronic payment services to make fashion-related purchases. Initially, User E's persona was identified as a "general consumer." However, after detecting User E's purchasing habits for clothing and accessories and his engagement with fashion-related content within the app, the persona classification model reclassifies User E as a "fashion lover." The content generation engine creates personalized newsletters featuring the latest fashion trends and exclusive discounts on User E's favorite brands as content and delivers them during User E's typical online shopping hours. Engagement information, such as newsletter engagement, purchase conversion rate, and brand preferences, is obtained, and the persona classification model fine-tunes the "fashion lover" persona, while the content generation engine tailors future content to focus on User E's favorite brands and styles.

[0060] According to the embodiment described above, it is possible to provide suitable recommendations related to electronic payments.

[0061] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0062] 10 User terminal device 20. Payment App 100 Payment Server 110 Contents Provider 140 Information Acquisition Department 150 Specific section 176 Persona Reference Data 300 LLM Servers

Claims

1. an information acquisition unit that acquires a usage history of an application program, including some or all of the functions used, session frequency, and session duration of the application program used in an electronic payment service by a user, which is provided in cooperation between an application program running on a user terminal device and a payment server that communicates with the application program, and the user's payment history, which is a history of electronic payments made using the application program; an identification unit that identifies one or more personas that represent the user's personality based on at least the usage history and the payment history; a content providing unit that provides content corresponding to the identified persona to the user terminal device; An information processing device comprising:

2. the identification unit inputs at least the usage history, the payment history, and instruction information for identifying a persona into a large-scale language model, and acquires an output of the large-scale language model, thereby identifying the persona; 2. The information processing device according to claim 1.

3. The large-scale language model divides input text data into tokens, converts them into vectors, and inputs the vectors into a trained model to return an answer based on the context understanding obtained.

3. The information processing device according to claim 2.

4. The identification unit identifies the persona using an MAB algorithm.

2. The information processing device according to claim 1.

5. the identification unit corrects the identification of the persona by feeding back engagement information indicating the user's reaction to the content; 2. The information processing device according to claim 1.

6. the engagement information includes tracking metrics; The tracking indicators include some or all of the following: CTR (Click Through Rate), conversion rate, open rate, and content viewing time; 6. The information processing device according to claim 5.

7. the content providing unit selects a channel for delivering the content based on the user's past behavior in the electronic payment service, and provides the content using the selected channel.

2. The information processing device according to claim 1.

8. The information processing device In an electronic payment service provided in cooperation between an application program running on a user terminal device and a payment server communicating with the application program, a process of acquiring a usage history of the application program, including some or all of the functions used, session frequency, and session duration of the application program used for electronic payments by a user, and a payment history of the user, which is a history of electronic payments made using the application program; A process of identifying one or more personas representing the user's personality based on at least the usage history and the payment history; a process of providing content corresponding to the identified persona to the user terminal device; An information processing method that performs the above.

9. In the information processing device, In an electronic payment service provided in cooperation between an application program running on a user terminal device and a payment server communicating with the application program, a process of acquiring a usage history of the application program, including some or all of the functions used, session frequency, and session duration of the application program used for electronic payments by a user, and a payment history of the user, which is a history of electronic payments made using the application program; A process of identifying one or more personas representing the user's personality based on at least the usage history and the payment history; a process of providing content corresponding to the identified persona to the user terminal device; A program to execute.

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