Advertisement distribution device, advertisement distribution method, and advertisement distribution program

Abstract

To distribute advertisement of more effective content to a consumer.SOLUTION: An advertisement distribution device 100 includes an action content acquisition unit 121, a product information acquisition unit 122, and a distribution unit 124. The action content acquisition unit 121 acquires information regarding predetermined action content of a user. The product information acquisition unit 122 acquires information related to a product sold in a predetermined store. The distribution unit 124 inputs information on the action content and information on a sales product to a generation model, and distributes advertisement of the sales product output by the generation model to the user.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an advertisement distribution device, an advertisement distribution method, and an advertisement distribution program. [Background technology]

[0002] Conventionally, in the field of commodity trading, consumers have purchased the desired commodity by directly visiting a sales outlet such as a manufacturer, retail store, or supermarket to search for the commodity or by directly inquiring about the commodity at the sales outlet, thereby obtaining information about the commodity to be purchased.

[0003] In response to this, retail stores are conducting various sales promotions to increase sales of their products. For example, retail stores send direct mail (DM) to consumers and distribute flyers (newspaper inserts). With such sales promotions, consumers can obtain information about products they are planning to purchase without having to visit or inquire at the retail store directly. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-151856 Summary of the Invention [Problem to be solved by the invention]

[0005] However, conventional technologies are unable to deliver more effective advertisement content to consumers. For example, conventional technologies only deliver store location information and product information as advertisements in accordance with the content set in advance by the consumer, and are unable to deliver effective advertisements that are tailored to the consumer's behavior, such as the consumer's purchase history, meal history, or content posted on SNS (Social Networking Service). [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the advertising distribution device of this embodiment is characterized by having a behavioral content acquisition unit that acquires information about a user's specified behavioral content, a product information acquisition unit that acquires information about products for sale at a specified store, and a distribution unit that inputs the information about the behavioral content and the information about the products for sale into a generation model and distributes advertisements for the products for sale output by the generation model to the user. [Effects of the Invention]

[0007] According to the present invention, it is possible to deliver advertisements with more effective content to consumers. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing the overall configuration of an advertisement distribution system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of the advertisement distribution device according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating a specific example of data stored in the advertisement distribution device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating a specific example of a process for distributing a cooking recipe to a user according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating a specific example of an advertisement delivery process according to the content of a user's input to a chat according to the embodiment. [Figure 6] FIG. 6 is a flowchart illustrating an example of a processing procedure of the advertisement distribution device according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an advertisement delivery device, an advertisement delivery method, and an advertisement delivery program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the advertisement delivery device, the advertisement delivery method, and the advertisement delivery program according to the present application are not limited to these embodiments. Furthermore, the same components in the following embodiments will be assigned the same reference numerals, and duplicated descriptions will be omitted.

[0010] [Overall structure] First, the overall configuration of the system according to the present embodiment will be described. Fig. 1 is a diagram showing the overall configuration of the advertisement distribution system according to the embodiment. In the system shown in Fig. 1, an advertisement distribution device 100 according to the present embodiment, a user terminal 200 owned by a user to whom an advertisement is distributed, and a store server 300 owned by a store selling the advertised product are connected to each other via a network so as to be able to communicate with each other.

[0011] In addition, in the network configuration shown in Fig. 1, each device may communicate via any communication network, whether wired or wireless, such as the Internet, a LAN (Local Area Network), or a VPN (Virtual Private Network). Note that the configuration shown in Fig. 1 is merely an example, and the specific configuration and the number of devices are not particularly limited.

[0012] The advertisement distribution device 100 is an information processing device that distributes advertisements for products recommended to a user, output using a generative model based on information such as a user's eating history, purchase history, and store product flyers acquired from a user terminal 200, a store server 300, etc., and is realized by a server device, a cloud system, etc.

[0013] The user terminal 200 is a smart device such as a smartphone or tablet, and is a portable terminal device capable of communicating with other devices via a wireless communication network. The user terminal 200 can, for example, store images captured using a camera function in its own storage unit. The user terminal 200 also has, for example, a location information measurement function, and can grasp the location information of its own device.

[0014] The store server 300 is an information processing device owned by an advertising store that sells products related to the advertisements distributed to users, and is realized by a server device, a cloud system, etc. The store server 300 stores information such as basic product data of products sold by the store, data on advertising flyers that list special offers, etc., and purchase history of registered users.

[0015] The advertisement distribution device 100 acquires information about a predetermined behavioral content of a user and information about products for sale at a predetermined store, then inputs the acquired information into a generation model and distributes advertisements for the products for sale output by the generation model to the user.

[0016] For example, the advertisement distribution device 100 acquires information on the user's product purchase history and information such as advertising flyers related to products sold by a store that is an advertisement source, from the user terminal 200 and the store server 300. Then, the advertisement distribution device 100 uses a generation model that outputs information on products recommended to the user based on the user's purchase history and the advertising flyers for products sold by the store, and distributes advertisements for products recommended to the user based on the acquired information to the user terminal 200.

[0017] As a result, the advertisement distribution device 100 distributes advertisements for products that are considered to be in high demand by users, such as products that the user purchases regularly, products required for dishes recommended from the user's meal history, and discounted products with a high purchase history, based on information on user behavior such as the user's purchase history and meal history, and information on products on sale such as special offers at stores, and can therefore distribute advertisements with more effective content to consumers.

[0018] [Configuration of advertisement distribution device 100] An example of the functional configuration of the above-described advertisement distribution device 100 will be described below. Fig. 2 is a diagram illustrating an example of the configuration of the advertisement distribution device according to the embodiment. As shown in Fig. 2, the advertisement distribution device 100 includes a communication unit 110, a control unit 120, and a storage unit 130.

[0019] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. For example, the communication unit 110 controls communication regarding various information exchanged with connected devices, and mediates the processing of each processing unit included in the control unit 120, which will be described later.

[0020] The storage unit 130 is realized by a storage device such as a RAM (Random Access Memory) or a hard disk. The storage unit 130 stores data and programs required for various processes by the control unit 120. Note that the storage device may be realized by a storage system or the like installed outside the advertisement distribution device 100.

[0021] The storage unit 130 stores information about the user's behavior, such as the user's purchase history, meal history, content posted to the chat tool, etc. Specifically, the storage unit 130 stores images of receipts and photographed images of food, purchase history data stored in association with membership information, data of content entered into the chat tool related to a dedicated application, and the like, all of which are acquired from the user terminal 200 or the store server 300 by the behavior content acquisition unit 121 (described later), along with information about the date and time when the behavior was performed.

[0022] The storage unit 130 also stores, for example, information about products sold by the store that is the advertiser. Specifically, the storage unit 130 stores basic data about each product sold by the store, as well as information about the prices and sale periods of special sale products, which are acquired from the store server 300 by the product information acquisition unit 122 (described later).

[0023] Here, information on products for sale at the store that is the advertising source and stored in the storage unit 130 will be described with reference to Fig. 3. Fig. 3 is a diagram showing a specific example of data stored in the advertisement distribution device according to the embodiment. In the example shown in Fig. 3, the storage unit 130 stores the items of "product ID," "product name," "price," "weight," and "size."

[0024] "Product ID" stores the ID assigned to the product by the advertiser's store, and "product name" stores the name of the product. "Price" stores the price of the product, and "weight" and "size" store the weight and size (length x width x height) of the product. For example, for a product with product ID "I001," the storage unit 130 stores information such as the product name "dishwashing detergent," price "150 yen," weight "250g," and size "20 x 10 x 10."

[0025] In addition to the basic data of the products for sale shown in Figure 3, the memory unit 130 can also store the changed prices of special items that are on sale and information about the period during which the sale is held.

[0026] The storage unit 130 also stores information such as the user's family structure, etc. Specifically, the storage unit 130 stores information such as the user's family structure and the average number of people dining in the user's household, which information is input to the user terminal 200 by the user information acquisition unit 123 described later.

[0027] The control unit 120 is realized by a processor, such as an integrated circuit such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array), executing various programs stored in a storage device inside the advertisement distribution device 100 using a RAM or the like as a working area. For example, in the example shown in FIG. 2 , the control unit 120 includes a behavior content acquisition unit 121, a product information acquisition unit 122, a user information acquisition unit 123, and a distribution unit 124.

[0028] The behavioral content acquisition unit 121 acquires information about predetermined behavioral content of the user. For example, the behavioral content acquisition unit 121 acquires information about the user's product purchase history. Specifically, the behavioral content acquisition unit 121 acquires, from the user terminal 200, captured images of receipts showing the user's purchase history and information about purchased products entered into the user terminal 200, or acquires, from the store server 300, the purchase history stored in association with the user's membership information, and stores the acquired information in the storage unit 130 together with date and time information.

[0029] The behavioral content acquisition unit 121 also acquires information related to the user's meal history. For example, the behavioral content acquisition unit 121 acquires, from the user terminal 200, photographed images of the dishes eaten by the user, information such as the names of the dishes eaten that is input to the user terminal 200, and images of menus showing the dishes eaten, and stores these in the storage unit 130. Note that the behavioral content acquisition unit 121 can also estimate the user's meal contents from the purchase history information described above, and store the estimated information in the storage unit 130 as the meal history, for example.

[0030] Furthermore, the behavioral content acquisition unit 121 acquires information regarding the content input by the user into a predetermined application. For example, the behavioral content acquisition unit 121 acquires information regarding the input history, such as text input by the user into a chat tool related to a dedicated application downloaded in advance to the user terminal 200, and stores the information in the storage unit 130. Here, the chat tool may be, for example, a chat tool used only in a specific local area, such as within a company, or may be a social networking service used by an unspecified number of people.

[0031] The product information acquisition unit 122 acquires information about products for sale at a predetermined store. For example, the product information acquisition unit 122 acquires information about products for sale at the advertising store, such as basic product data such as product name, price, weight, and size, and information about the prices and sale periods of special sale items, from the store server 300, and stores the information in the storage unit 130. Here, the product information acquisition unit 122 can also acquire the information about the products for sale from product introduction pages and advertising flyers published on the Internet.

[0032] The user information acquisition unit 123 acquires information about the user's family structure. For example, the user information acquisition unit 123 acquires from the user terminal 200 information that can be used to understand the amounts of ingredients in an advertisement to be delivered to the user, such as information about the user's family structure and the standard number of people dining, which have been input into an application downloaded to the user terminal 200, and stores the information in the storage unit 130.

[0033] The aforementioned behavioral content acquisition unit 121, product information acquisition unit 122, and user information acquisition unit 123 can acquire image and text data input by the user to a dedicated application related to the advertising distribution service of this embodiment, and can also acquire image and text input data without the need for input operations by the user by linking with a pre-downloaded photo application or other application.

[0034] The distribution unit 124 inputs information about the behavioral content and information about the sales product into the generative model, and distributes the sales product advertisement output by the generative model to the user. For example, the distribution unit 124 inputs the above-mentioned information about the user's purchase history and meal history, information about the sales product of the store that is the advertiser, and information about the content entered into the chat tool into the generative model, and distributes the output sales product advertisement recommended to the user to the user terminal 200.

[0035] Here, the generative model is a model that generates a response sentence in natural language in response to a command sentence (prompt) set in natural language. The response sentence output by the generative model may include an image in addition to a sentence, or may be an image instead of a sentence. The distribution unit 124 sets a command sentence such as "You are an advertising creation expert. The given purchase product names are the purchase history of a specific user. Analyze the trends in these purchase histories and list appropriate products that you would recommend to the user from among the product names on sale." in the generative model, inputs the user's purchase history and information on the product on sale, and acquires the output product names. The advertisement distribution device 100 can automatically generate the command sentence and set it in the generative model.

[0036] The distribution unit 124 also distributes advertisements for products that are recommended to the user according to the user's purchase history and for which either or both of the weight and size of the products for sale are within a predetermined range. For example, the distribution unit 124 inputs information on the user's purchase history and basic information on the products for sale (see FIG. 3) into a generative model, and distributes the output product advertisements to the user terminal 200.

[0037] In this case, the distribution unit 124 sets, in the generative model, a command statement for outputting, as a product to be recommended to the user, a product whose weight and size are within a certain range and which is determined to have a high advertising effect on the user based on the tendency of the user's purchase history. In addition, the advertisement distribution device 100 can automatically generate the above-mentioned command statement and set it in the generative model.

[0038] To explain this using a specific example, the distribution unit 124 sets a command statement in the generation model such as, "You are an expert in creating advertisements. The given purchased product names are the purchase history of a specific user. Analyze the trends in these purchase histories and list appropriate products from the sold product names that are in the range of weight less than XX kg and size less than △△ cm and that you would recommend to the user for purchase." and inputs the user's purchase history and information on the sold product to obtain the output product name.

[0039] The preset weight and size may be, for example, any value set by the user, or may be a value set in consideration of the weight and size that the user can carry to their destination without any problems after shopping. Specifically, the weight and size may be set to 5 kg or 50 cm, and advertisements for products up to the set values ​​are delivered to the user. Furthermore, the delivery unit 124 may deliver advertisements suggesting the purchase of products over the weight or size limit via online shopping.

[0040] The distribution unit 124 also inputs information about family structure and information about meal history into the generative model, and distributes to the user a recipe recommended for the user output by the generative model and an advertisement for a product for sale related to the recipe. For example, the distribution unit 124 inputs information about the user's family structure, information about meal history, and basic information about a product for sale into the generative model, and distributes the output recipe and an advertisement for the ingredients listed in the recipe to the user terminal 200.

[0041] In this case, the distribution unit 124 sets, for example, a command statement to output recipes for meals that do not overlap with the user's meal history for a certain period and that are nutritionally balanced for the number of people in a family, in the generation model. Furthermore, the advertisement distribution device 100 can automatically generate the above-mentioned command statement and set it in the generation model.

[0042] To give a specific example, the distribution unit 124 sets an instruction statement in the generation model such as, "You are a registered dietitian. The images of the dishes you are given are the dietary history of a specific user. Analyze the trends in these dietary histories and list recipes for meals that are nutritionally balanced and serve x servings and that you recommend to the user, without overlapping with the dietary history within the past week." and inputs information about the user's family composition and information about the user's dietary history to obtain the recipe for the dish that is output.

[0043] Furthermore, the distribution unit 124 uses information related to the location information of the user's terminal to distribute an advertisement when the user is staying within a predetermined range from a predetermined store. For example, the distribution unit 124 estimates the location information of the user terminal 200 acquired from the user terminal 200 as the user's location information, and distributes a product advertisement to the user terminal 200 when the estimated location information is detected near the store that is the advertiser.

[0044] Here, the predetermined range within which the advertisement is distributed can be, for example, any value set by the user. If a distance of a 5 km radius from the store is set, the distribution unit 124 distributes the advertisement when the user's location information is detected within a 5 km radius from the store.

[0045] Furthermore, the distribution unit 124 can distribute advertisements in accordance with the timing of the user's shopping, for example. Specifically, if it is estimated from the purchase history that the user goes shopping at 5 PM every day, the distribution unit 124 can distribute advertisements at 4 PM before the shopping. Note that the distribution unit 124 can also distribute advertisements during a time period preset by the user.

[0046] The distribution unit 124 also distributes advertisements to users in accordance with the content input by the user into a predetermined application. For example, the distribution unit 124 inputs chat history information, such as "I want to eat pizza" or "I'm running out of detergent," input by the user into a chat tool related to a dedicated application, and basic information about a product for sale into a generative model, and distributes the output advertisement for the product to the user terminal 200.

[0047] In this case, the distribution unit 124 sets, for example, a command statement for outputting a product that is estimated to be desired by the user from the chat history input by the user, in the generative model. In addition, the advertisement distribution device 100 can automatically generate the above-mentioned command statement and set it in the generative model.

[0048] To give a specific example, the distribution unit 124 sets a command statement such as "You are an advertising creation expert. The given sentences are chat histories entered by a specific user. Analyze the input contents of these chat histories and list appropriate products from the names of products on sale that you would recommend to the user for purchase" in the generation model, inputs the user's chat history and information about the products on sale, and obtains the product names that are output.

[0049] [Specific example] Next, a cooking recipe distribution process by the advertisement distribution device 100 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram showing a specific example of a cooking recipe distribution process to a user according to the embodiment. The example shown in Fig. 4 illustrates a process in which, when information on the user's family structure, information on products sold by an advertising store, and information on a meal history are input to a generation model, a cooking recipe output by the generation model is distributed to the user terminal 200.

[0050] First, the behavioral content acquisition unit 121 acquires photographed images of the user's dinner from yesterday to one week ago as the user's meal history. Furthermore, the product information acquisition unit 122 acquires information on products sold by the advertiser's store in a list format as shown in Fig. 3. Furthermore, the user information acquisition unit 123 acquires the family structure information "self, husband, son" entered by the user.

[0051] Next, the distribution unit 124 inputs each of the acquired information into the generative model along with the setting of the command sentence, and acquires an output of a recommended dinner recipe to be recommended to the user and an advertisement for the ingredients from the store that advertised the recipe. The distribution unit 124 then distributes the recipe and the advertisement for the ingredients to the user terminal 200 as "Recommended dinner recipe (serves 3)..." and "Ingredients required (serves 3)...".

[0052] Next, a process of delivering a product advertisement according to chat input content by the advertisement delivery device 100 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a diagram showing a specific example of an advertisement delivery process according to chat input content by a user according to the embodiment. The example shown in Fig. 5 illustrates a process of delivering a product advertisement output by a generative model to the user terminal 200 when chat history information entered by a user, product sales information of a store that is an advertising source, and location information of the user terminal 200 are input to the generative model.

[0053] First, the behavioral content acquisition unit 121 acquires chat history information such as "I'm hungry. I want to eat pizza. I want to eat pizza." in an XX chat related to an application downloaded to the user terminal 200. Furthermore, the product information acquisition unit 122 acquires information on products sold by each of multiple stores that are advertisers. In the example of FIG. 5, the product information acquisition unit 122 particularly acquires information on products sold by the stores "XX Pizza" and "△△ Pizza." Furthermore, the advertisement distribution device 100 acquires location information of the user terminal 200, such as "Shinbashi, Minato-ku, Tokyo."

[0054] Next, the distribution unit 124 inputs each piece of acquired information into the generative model along with the setting of the command sentence, and acquires the output of an advertisement for a store that provides the product (pizza) desired by the user, taking the location information into consideration. Then, the distribution unit 124 distributes "XX Pizza, 3 minutes' walk from Shimbashi Station, delivery available" to the user terminal 200 as an advertisement for a store that provides pizza.

[0055] 〔flowchart〕 Next, an example of processing by the advertisement distribution device 100 according to the present embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of a processing procedure of the advertisement distribution device according to the embodiment. Note that the steps in the flowchart shown in Fig. 6 may be executed in a different order, and some processing may be added or omitted.

[0056] First, the behavioral content acquisition unit 121 acquires information about the user's purchase history (S101). Next, the product information acquisition unit 122 acquires information about products for sale at a predetermined store (S102). Subsequently, the distribution unit 124 inputs the user's purchase history and the information about the products for sale at the predetermined store into a generative model and sets a command statement (S103). Thereafter, the distribution unit 124 distributes the advertisements for the products for sale output by the generative model to the user terminal 200 (S104), and the advertisement distribution device 100 ends the process.

[0057] 〔effect〕 The advertisement distribution device 100 according to this embodiment includes a behavioral content acquisition unit 121, a product information acquisition unit 122, and a distribution unit 124. The behavioral content acquisition unit 121 acquires information related to predetermined behavioral content of a user. The product information acquisition unit 122 acquires information related to products for sale at a predetermined store. The distribution unit 124 inputs the information related to the behavioral content and the information related to the products for sale into a generative model, and distributes advertisements for the products for sale output by the generative model to users.

[0058] As a result, the advertisement distribution device 100 distributes advertisements for products that are considered to be in high demand by users, such as products that the user purchases regularly, products required for dishes recommended from the user's meal history, and discounted products with a high purchase history, based on information on user behavior such as the user's purchase history and meal history, and information on products on sale such as special offers at stores, and can therefore distribute advertisements with more effective content to consumers.

[0059] In addition, when the behavioral content acquisition unit 121 acquires information regarding the user's product purchase history and the product information acquisition unit 122 acquires information regarding either or both of the weight and size of the product for sale, the distribution unit 124 distributes advertisements for products recommended to the user according to the user's purchase history, and for which either or both of the weight and size of the product for sale are within a predetermined range.

[0060] As a result, the advertisement distribution device 100 can distribute to the user advertisements for products that take into consideration the amount that the user can comfortably carry when shopping, based on information on the user's purchase history and information on the weight and size of the products on sale.

[0061] The advertisement distribution device 100 also includes a user information acquisition unit 123. The user information acquisition unit 123 acquires information about the user's family structure. In this case, the behavioral content acquisition unit 121 acquires information about the user's meal history, and the distribution unit 124 inputs the information about the family structure and the information about the meal history into a generative model and distributes to the user recipes recommended to the user and advertisements for products related to the recipes, which are output by the generative model.

[0062] As a result, the advertisement distribution device 100 distributes a recipe of a dish recommended to the user, which is output taking into consideration the user's family structure and dietary history, and an advertisement for ingredients for the number of people listed in the recipe, and can therefore distribute advertisements for specific dish contents that are in high demand among users.

[0063] Furthermore, the distribution unit 124 distributes advertisements when the user is staying within a predetermined range from a predetermined store, using information related to the location information of the user's terminal. This allows the advertisement distribution device 100 to distribute advertisements when the location information of the user terminal 200 indicates that the user is approaching a store that is the advertiser, thereby enabling advertisements for products for sale to be distributed to the user at appropriate times.

[0064] Furthermore, when the behavioral content acquisition unit 121 acquires information regarding the content input by the user to a predetermined application, the distribution unit 124 distributes advertisements to the user according to the content input by the user to the predetermined application. This allows the advertisement distribution device 100 to appropriately distribute advertisements for products desired by the user based on everyday conversations input by the user to a chat tool related to a dedicated application.

[0065] [System configuration, etc.] Of the processes described in the above embodiments, some of the processes described as being performed automatically can also be performed manually. Alternatively, all or some of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0066] Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads and usage conditions. Furthermore, all or any part of the processing functions performed by each device can be realized by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0067] 2 may be stored in a storage server or the like, instead of being stored in the advertisement distribution device 100. In this case, the advertisement distribution device 100 accesses the storage server to acquire various pieces of information.

[0068] [Hardware configuration] 7 is a diagram illustrating an example of a hardware configuration. The advertisement distribution device 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG.

[0069] The computer 1000 includes, for example, a memory 1010 and a CPU 1020. The computer 1000 also includes a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0070] The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores, for example, a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1090. The disk drive interface 1040 is connected to a disk drive 1041. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to, for example, a mouse 1110 and a keyboard 1120. The video adapter 1060 is connected to, for example, a display 1130.

[0071] The hard disk drive 1090 stores, for example, an OS (Operating System) 1091, an application program 1092, a program module 1093, and program data 1094. That is, a program that defines each process of the advertisement distribution device 100 is implemented as a program module 1093 in which code executable by the computer 1000 is written. The program module 1093 is stored, for example, in the hard disk drive 1090. For example, a program module 1093 for executing processes similar to those of the functional configuration of the advertisement distribution device 100 is stored in the hard disk drive 1090. Note that the hard disk drive 1090 may be replaced with an SSD (Solid State Drive).

[0072] Furthermore, setting data used in the processing of the above-described embodiment is stored as program data 1094, for example, in memory 1010 or hard disk drive 1090. Then, CPU 1020 reads program module 1093 and program data 1094 stored in memory 1010 or hard disk drive 1090 into RAM 1012 as necessary and executes them.

[0073] The program module 1093 and program data 1094 are not limited to being stored in the hard disk drive 1090, but may also be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1041. Alternatively, the program module 1093 and program data 1094 may be stored in another computer connected via a network (LAN, WAN, etc.). The program module 1093 and program data 1094 may then be read by the CPU 1020 from the other computer via the network interface 1070. [Explanation of symbols]

[0074] 100 Advertisement distribution device 110 Communications Department 120 control section 121 Action content acquisition unit 122 Product Information Acquisition Department 123 User Information Acquisition Unit 124 Distribution Department 130 Storage section 200 user terminals 300 store servers

Claims

1. an activity content acquisition unit that acquires information about predetermined activity content of a user; a product information acquisition unit that acquires information about products sold at a predetermined store; a distribution unit that inputs information about the behavioral content and information about the product for sale into a generative model and distributes an advertisement for the product for sale output by the generative model to users; An advertisement distribution device comprising:

2. the behavior content acquisition unit acquires information about the user's product purchase history; the product information acquisition unit acquires information regarding one or both of the weight and size of the product for sale, the distribution unit distributes advertisements for products recommended to the user in accordance with the user's purchase history, the products being for sale with either or both of weight and size within a predetermined range; 2. The advertisement distribution device according to claim 1.

3. a user information acquisition unit that acquires information about the user's family structure; the behavioral content acquisition unit acquires information about the user's meal history, the distribution unit inputs the information related to the family structure and the information related to the meal history into the generative model, and distributes to the user the recipes of dishes recommended to the user output by the generative model and advertisements of the products for sale related to the recipes of dishes; 2. The advertisement distribution device according to claim 1.

4. the distribution unit uses information related to location information of the user's terminal to distribute an advertisement when the user is staying within a predetermined range from the predetermined store; 2. The advertisement distribution device according to claim 1.

5. the behavior content acquisition unit acquires information about content input by the user into a predetermined application; the distribution unit distributes an advertisement to the user in accordance with content input by the user into a predetermined application.

2. The advertisement distribution device according to claim 1.

6. An advertisement distribution method executed by an advertisement distribution device, an activity content acquisition step of acquiring information about predetermined activity content of the user; a product information acquisition step of acquiring information about products sold at a predetermined store; a distribution step of inputting information about the behavioral content and information about the product for sale into a generative model and distributing an advertisement for the product for sale output by the generative model to users; An advertisement distribution method comprising:

7. An action content acquisition step for acquiring information about predetermined action content of the user; a product information acquisition step for acquiring information about products sold at a predetermined store; a distribution step of inputting information about the behavioral content and information about the product for sale into a generative model and distributing an advertisement for the product for sale output by the generative model to a user; An advertisement distribution program that causes a computer to execute the above.

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