System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving input of advertising requirements; means for generating advertising creatives based on the advertising requirements; means for testing the generated advertising creatives; means for delivering the tested advertising creatives to an ad network; and means for collecting advertising placement results and generating a report.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditionally, creating creative ads required a great deal of time and effort, as well as specialized knowledge, making it difficult for small and medium-sized businesses to easily create and place ads. Furthermore, there were no efficient methods for delivering ads to different ad networks, supporting multiple languages, or measuring and reporting on ad performance, so there was a need to streamline these processes and reduce the burden on advertisers. [Means for solving the problem]

[0005] The present invention provides a system including a means for accepting input of advertising requirements, a generating means for generating advertising creatives based on the advertising requirements, a means for inspecting the generated advertising creatives, a means for distributing advertising creatives that pass inspection to an ad network, and a means for collecting advertising performance results and generating reports. This allows users, even without specialized knowledge, to easily create, distribute, and measure the effectiveness of advertisements, thereby efficiently implementing advertising strategies. Furthermore, by automatically generating and filtering advertising creatives using a machine learning model, high-quality advertising materials can be quickly provided.

[0006] "Advertising requirements" are information necessary to generate advertising materials, including titles, descriptions, images, target audiences, budgets, and periods.

[0007] The "generation means" has a function of automatically generating advertising creatives based on input advertising requirements.

[0008] The "inspection means" has a function of checking whether the generated advertising creative contains inappropriate expressions or content.

[0009] The "distribution means" has the function of distributing advertising creatives that have passed inspection to a designated ad network.

[0010] "Report generation means" means a means that has the function of collecting and analyzing the results of advertisements and creating reports on the performance of advertisements.

[0011] The "input form display means" has a function of providing an interface for the user to input advertisement requirements.

[0012] The "transmission means" has a function of transmitting the advertisement requirements input by the user to the server.

[0013] The "display means" has a function of displaying the generated advertising creative and a report on the results of advertising to the user.

[0014] "Machine Learning Model" means the algorithms and data models used to generate and filter advertising creative.

[0015] The "filtering means" has the function of inspecting the appropriateness of advertising creatives generated by the machine learning model.

[0016] The "schedule setting means" has a function of setting the advertisement distribution schedule (start date, end date, target demographic, budget allocation, etc.).

[0017] The "settings management means" has a function of managing various settings for advertisement distribution.

[0018] The "strategy proposal means" has the function of automatically proposing the next advertising strategy based on the results of advertising.

[0019] The "automatic advertising requirement updating means" has a function of automatically updating advertising requirements based on a proposed advertising strategy. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The present invention is a system for efficiently carrying out a series of advertising management processes, from inputting advertising requirements to distribution and report generation. A specific embodiment of this system will be described.

[0042] 1. Enter your advertising requirements

[0043] User Action:

[0044] Users begin creating ads on a dedicated management screen. Clicking the "Create Ad" button displays an input form. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. After entering the required information in the form and clicking the submit button, this data is sent to the server via the device.

[0045] Terminal processing:

[0046] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[0047] 2. Generating ad creatives

[0048] Server side:

[0049] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[0050] Generative AI processing:

[0051] Generative AI uses machine learning models to automatically generate ad creatives based on input factors, including optimal design and wording to maximize ad effectiveness.

[0052] 3. Inspection of advertising materials

[0053] Server side:

[0054] The generated ad creatives are subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If non-compliant content is found, it is automatically corrected or instructed to be regenerated.

[0055] 4. Review and Approval of Advertising Materials

[0056] Terminal processing:

[0057] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[0058] User Action:

[0059] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[0060] 5. Preparing for ad delivery

[0061] Server side:

[0062] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[0063] 6. Delivery of advertisements

[0064] Server side:

[0065] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[0066] 7. Collecting and reporting on advertising performance results

[0067] Server side:

[0068] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[0069] 8. Check advertising reports and plan your next strategy

[0070] Terminal processing:

[0071] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[0072] User Action:

[0073] Users can use the reports to consider their next advertising strategy, and by using the system's built-in strategy proposal function, they can receive specific suggestions for improvement.

[0074] Specific examples

[0075] Consider the case where a small business advertiser wants to advertise an in-store sale.

[0076] 1. User starts creating an ad:

[0077] Users select "Create Ad" on the admin screen, enter the title "Winter Sale," the description "20% off all items," upload a photo of their store as the image, and enter their budget and target audience.

[0078] 2. Ad creative generation:

[0079] The server inputs this information into the AI ​​generator, which then generates the appropriate design and copy. For example, a catchy slogan such as "Click here for limited-time coupons" is automatically generated.

[0080] 3. Inspect the generated ad:

[0081] Inspect server-generated content to ensure it does not contain inappropriate content.

[0082] 4. Ad Review and Approval:

[0083] The generated advertisement is displayed to the user, who then reviews and approves the content.

[0084] 5. Preparation and implementation of advertising distribution:

[0085] The server sets the delivery schedule and settings, and delivers advertisements to domestic and international ad networks based on the settings.

[0086] 6. Performance collection and reporting:

[0087] It collects advertising performance data and generates effectiveness reports based on this data.

[0088] 7. Review the report and consider your next strategy:

[0089] The user reviews the report and plans their next advertising strategy based on the obtained data.

[0090] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[0091] The processing flow will be explained below.

[0092] Step 1:

[0093] User begins creating ad

[0094] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[0095] Step 2:

[0096] The device displays the input form

[0097] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, duration, etc.

[0098] Step 3:

[0099] User enters advertising requirements

[0100] The user enters the advertising requirements into the displayed input form, and once all the required information has been entered, the user clicks the submit button.

[0101] Step 4:

[0102] The device sends the input data to the server

[0103] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[0104] Step 5:

[0105] The server passes the data to the generated AI.

[0106] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creatives. At this point, the generative AI generates optimal designs and copy.

[0107] Step 6:

[0108] Generative AI generates ad creatives

[0109] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[0110] Step 7:

[0111] Server inspects generated creative

[0112] The server filters the generated ad creative to ensure it does not contain violent, adult or inappropriate content.

[0113] Step 8:

[0114] The server sends the ad creative to the device

[0115] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[0116] Step 9:

[0117] User reviews ad creative

[0118] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[0119] Step 10:

[0120] Prepare to deliver ads

[0121] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[0122] Step 11:

[0123] Ads delivered to ad networks

[0124] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[0125] Step 12:

[0126] Collect ad performance data

[0127] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[0128] Step 13:

[0129] The server generates the report

[0130] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[0131] Step 14:

[0132] The server sends the report to the device.

[0133] The generated report is sent from the server to the terminal and displayed to the user.

[0134] Step 15:

[0135] User checks the report

[0136] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[0137] Step 16:

[0138] Users consider their next advertising strategy

[0139] Users can plan their next advertising strategy based on the report results, and can receive specific suggestions for improvement by using the system's built-in strategy suggestion function.

[0140] Example 1

[0141] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0142] With conventional ad management systems, the process from entering advertising requirements to distribution and report generation was complex and time-consuming, making it difficult to operate efficiently. Furthermore, the creation and testing of ad creatives required a lot of manual work, making it difficult to maximize advertising effectiveness. This made it difficult to run simple and effective ad campaigns, especially for advertisers with limited resources, such as small and medium-sized businesses.

[0143] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0144] In this invention, the server includes means for accepting input of advertising requirements, means for structuring the advertising requirements and transmitting them to the server, and means for generating advertising creatives using a generative AI model based on the advertising requirements. This enables efficient automatic generation and inspection of advertising creatives, preparation for distribution, distribution, collection of results, and report generation as a single process.

[0145] "Advertising requirements" refers to the information required to create and distribute an advertisement, including details such as the title, description, image, target audience, budget, and distribution period.

[0146] A "generative AI model" is an algorithm or system that uses machine learning technology to automatically generate advertising creatives (e.g., text, images, layout, etc.).

[0147] "Server" refers to the part of the computer system that receives, processes, and stores data sent by users, generates advertising creatives using generative AI models, inspects the results of such generation, and ultimately delivers and generates reports.

[0148] "Advertising creative" refers to all materials used in advertising, such as text, images, and layout, and is content designed to maximize advertising effectiveness.

[0149] "User" refers to an advertiser who uses the system to create, manage, and distribute advertisements.

[0150] "Input Form" means a web form used by a User to enter advertising requirements, where specific fields may be entered to provide further information about the advertisement.

[0151] "Inspection" refers to the process of checking the content of the generated advertising creative to ensure that it does not contain inappropriate content (e.g., violent or adult content).

[0152] An "ad network" is a network that delivers advertisements to multiple websites, and examples include Google Ads and Facebook Ads.

[0153] "Report" means a document containing detailed analytical information about the performance of an Ad, including data such as impressions, click-through rates, engagement rates, and conversions.

[0154] "Next advertising strategy" refers to the specific policies and methods for planning and executing the next advertising activity based on the results of past advertising campaigns.

[0155] The present invention is a system that automates and streamlines a series of advertising management processes, from inputting advertising requirements to generating, inspecting, and distributing advertising creatives, collecting results, and generating reports. A specific embodiment of this system will be described.

[0156] First, the user accesses the management screen using a dedicated web browser. When the "Create Ad" button on this management screen is clicked, an input form for entering the ad requirements is displayed. This input form contains fields for entering information such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the "Submit" button.

[0157] The input data is structured on the device via a JavaScript API and converted to JSON format. This data is then sent to the server using HTTPS. Once the data transfer is complete, the server receives the data and passes it to a generative AI model. This generative AI model uses OpenAI's GPT series, which uses machine learning technology, for example.

[0158] The server generates a prompt based on the advertising requirements and sends it to the AI ​​model. An example of a prompt might be, "Generate advertising creative based on the following information: Title: Winter Sale, Description: 20% off all items, Image: Store photo, Target audience: Housewives, Budget: 10,000 yen, Distribution period: 1 week."

[0159] The generative AI model receives a prompt and automatically generates ad creatives based on it. The generated creatives are sent back to the server, where content inspection is performed. This inspection method uses NLP and image analysis technologies to check whether the generated creatives contain violent or adult content. If inappropriate content is detected, it is automatically filtered or corrected.

[0160] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user checks the generated ad to ensure there are no omissions or errors. If there are no problems, the user clicks the "Approve" button for final confirmation.

[0161] After receiving the user's final approval, the server sets the schedule and distribution settings for ad distribution. Specifically, the distribution start date, end date, target audience characteristics, budget allocation, etc. are set. Once the settings are complete, the ads are distributed in a format optimized for each ad network. Examples of ad networks include Google Ads and Facebook Ads.

[0162] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. The server analyzes this data and automatically generates a report, which is sent to the device and displayed to the user.

[0163] Finally, users review the report and consider their next advertising strategy. The system's built-in strategy suggestion function allows users to make specific suggestions for improvement or formulate new strategies.

[0164] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[0165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0166] Step 1:

[0167] User processing

[0168] Users access the management screen using a dedicated web browser. When they click the "Create Ad" button, an input form for entering their ad requirements appears. The input form includes fields for the ad title, description, image, target audience, budget, distribution period, etc. The user enters information in these fields and clicks the "Submit" button.

[0169] Input: Ad title, description, image, target audience, budget, delivery period and other details.

[0170] Output: Structured ad requirements data.

[0171] Step 2:

[0172] Terminal side processing

[0173] The device structures the advertising requirements data entered by the user via a JavaScript API and converts it into JSON format, which is then sent to the server via HTTPS. The device also checks whether the data has been transferred correctly.

[0174] Input: Structured ad requirements data.

[0175] Output: Ad requirements JSON data sent to the server.

[0176] Step 3:

[0177] Server-side processing

[0178] The server passes the received ad requirements JSON data to a generative AI model. The generative AI model can be, for example, OpenAI's GPT series, which uses machine learning technology. The server generates a prompt based on the ad requirements and sends it to the generative AI model.

[0179] Input: Ad requirements JSON data.

[0180] Output: The prompt sentence that is passed to the generative AI model.

[0181] Step 4:

[0182] Processing by generative AI models

[0183] The generative AI model receives the prompt text and automatically generates ad creatives based on it. The generated creatives are sent back to the server via API. The generated ad creatives include text, image placement, layout, etc.

[0184] Input: Prompt statement.

[0185] Output: The generated ad creative.

[0186] Step 5:

[0187] Server-side processing

[0188] The server inputs the received ad creative into the content inspection module. This module uses NLP and image analysis technologies to check whether the generated creative contains violent or adult content. If inappropriate content is detected, it automatically corrects it or sends a regeneration instruction to the generation AI model.

[0189] Input: The generated ad creative.

[0190] Output: Inspected ad creative.

[0191] Step 6:

[0192] Terminal side processing

[0193] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user reviews the ad and checks for any omissions or errors. If there are no problems, they click the "Approve" button. If necessary, they can enter correction requests and resubmit.

[0194] Input: Inspected ad creative.

[0195] Output: User approval or correction request.

[0196] Step 7:

[0197] Server-side processing

[0198] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery. Specifically, it sets the delivery start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the ad is delivered in an optimized format for each ad network.

[0199] Input: User approval.

[0200] Output: Ad delivery schedule and configuration information.

[0201] Step 8:

[0202] Server-side processing

[0203] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. This data is analyzed and automatically generated into a report, which is then sent to the device and displayed to the user.

[0204] Input: Ad performance data.

[0205] Output: The generated ad effectiveness report.

[0206] Step 9:

[0207] User processing

[0208] Users can review the reports and consider their next advertising strategy. By using the system's built-in strategy suggestion function, they can propose specific improvements or formulate new strategies.

[0209] Input: The generated ad effectiveness report.

[0210] Output: Next advertising strategy and improvement suggestions.

[0211] (Application example 1)

[0212] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0213] Conventional ad generation systems make it difficult for users to efficiently create and distribute ad creatives. Furthermore, the effectiveness of generated ads cannot be predicted in advance, leading to uncertainty about ad performance. Furthermore, the inability to check generated ads in real time and make immediate corrections can lead to a decline in user satisfaction.

[0214] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0215] In this invention, the server includes means for accepting input of advertising requirements, means for generating advertising creatives based on the advertising requirements, means for inspecting the generated advertising creatives, means for distributing advertising creatives that pass inspection to an ad network, means for collecting advertising performance results and generating reports, means for providing real-time previews of the advertising creatives, and means for predicting the effectiveness of the generated advertising creatives. This allows users to efficiently manage the entire process from creating advertising creatives to distributing them, and enables them to predict the effectiveness of advertising in advance. Furthermore, the real-time preview function allows users to instantly check and modify advertising content, thereby improving user satisfaction.

[0216] The "means for inputting advertisement requirements" is a means for providing an interface for a user to input details such as the title, description, image, target audience, budget, and distribution period of an advertisement.

[0217] "Generation means" refers to a device or program that automatically generates advertising creatives (images, text, layout, etc.) using generation AI based on advertising requirements entered by the user.

[0218] The "inspection means" is a device or program that checks whether the generated advertising creative contains inappropriate content and performs filtering.

[0219] A "distribution means" is a device or program that transmits advertising creatives that have passed inspection to an ad network and distributes advertisements based on a set schedule.

[0220] A "report generation means" is a device or program that collects the performance results of delivered advertisements (number of impressions, click rate, engagement rate, number of conversions, etc.), analyzes them, and automatically generates a report showing the effectiveness of the advertisements.

[0221] The "real-time preview means" is a means for providing an interface that allows a user to check the results of creation in real time during the process of creating an advertising creative and make any necessary corrections immediately.

[0222] The "effectiveness prediction means" is a device or program that uses past advertising data and a machine learning model to predict the advertising effectiveness of the generated advertising creative in advance and present it to the user.

[0223] A "machine learning model" is an algorithm or model that learns from past data and is used to generate advertising creatives and predict their effectiveness.

[0224] This invention relates to an advertising management system that performs an integrated process from inputting advertising requirements to generating, inspecting, distributing, measuring effectiveness, and generating reports. The mechanism for implementing this system is described below.

[0225] Enter your advertising requirements

[0226] Users begin creating ads using the dedicated smartphone application "SmartAd Creator." When users click the "Create Ad" button on the application's management screen, an input form for ad requirements is displayed. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. The input data is sent to the server by the smartphone application.

[0227] Ad creative generation

[0228] The server receives the ad requirements sent by the user and passes them to a generative AI engine (e.g., GPT-3 or Stable Diffusion). The generative AI engine automatically generates ad creatives (images, text, layout, etc.) based on these requirements. The generated ad creatives are sent back to the server.

[0229] Real-time preview and effectiveness prediction of advertising materials

[0230] The server provides a function to preview the generated ad creative in real time. Users can check this preview through a smartphone application. The server also uses past advertising data and machine learning models to predict the effectiveness of the generated ad creative in advance and presents the results to users.

[0231] Ad creative inspection

[0232] The generated ad creatives are then subject to content inspection by server-based inspection means, which filters the ads for inappropriate content (e.g., violent, adult, or discriminatory language).

[0233] Ad serving

[0234] After the user approves the ad creative, the server sets a distribution schedule and distributes the ad to the ad network. The distribution is carried out based on the set schedule, and the server also manages the target audience characteristics and budget allocation.

[0235] Measurement and reporting

[0236] The server automatically collects and analyzes the performance of the advertisements (number of impressions, click-through rate, engagement rate, number of conversions, etc.) and generates an effectiveness report, which is displayed to the user via a smartphone application.

[0237] Hardware and software used

[0238] Smartphone: "SmartAd Creator" application

[0239] Server: Receives advertising requirements, connects with AI engine, generates advertising creatives, provides real-time previews, predicts effectiveness, inspects content, delivers ads, measures effectiveness, generates reports

[0240] Generative AI engine: GPT-3, Stable Diffusion

[0241] Machine learning model: Advertising effectiveness prediction

[0242] Specific examples

[0243] For example, consider a small business advertiser announcing a "Winter Sale." The user uses the "SmartAd Creator" application and enters the following prompt text:

[0244] Prompt statement:

[0245] I would like to create an ad to announce this month's members-only sale. The sale runs until the end of the month, with a total budget of 500,000 yen, and the main target audience is women in their 20s and 30s. The ad title should be "Members-only sale," and the description should be "All products are eligible. Don't miss out on this special discount!" I would like to use a photo from inside the store.

[0246] Based on this prompt, the generative AI engine generates ad creatives, and the server provides real-time previews and effectiveness predictions. After the user confirms, modifies, and approves the ad, it is automatically distributed to the ad network. After the ad is distributed, the server measures its effectiveness and generates a report that is provided to the user to support their next advertising strategy.

[0247] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0248] Step 1:

[0249] The user starts the "SmartAd Creator" application on their smartphone and starts creating an ad. When the user clicks the "Create Ad" button on the management screen, an input form for the ad requirements is displayed. The form has fields for entering details such as the ad title, description, image, target audience, budget, and distribution period. When the user enters data into these fields and clicks the "Submit" button, the input data is sent from the device to the server.

[0250] Input: Ad title, description, image, target audience, budget, delivery period

[0251] Output: Ad requirements data sent to the server

[0252] Specific actions: The user uses the smartphone's touchscreen to enter information into each field and tap the send button.

[0253] Step 2:

[0254] The server receives the ad requirement data sent from the device. The server then passes this data to a generative AI engine (e.g., GPT-3, Stable Diffusion) and requests it to generate ad creatives. The generative AI engine generates optimal ad creatives (images, text, layout, etc.) based on the input information and returns the results to the server.

[0255] Input: Advertising requirements data

[0256] Output: Generated ad creative (images, text, layout)

[0257] Specific operation: The server calls the API of the generation AI engine and passes the advertising requirements as input data. The server receives the generated creative data.

[0258] Step 3:

[0259] The server sends the generated ad creative to the device as a real-time preview. The user can view this real-time preview through a smartphone application. The server also predicts the effectiveness of the generated ad based on past ad data and provides the results to the user. This effectiveness prediction includes, for example, estimates of click-through rate and conversion rate.

[0260] Input: Generated ad creative

[0261] Output: Real-time preview and effect prediction data

[0262] Specific operation: The server delivers the generated advertising creative and the results of the effectiveness prediction to the device, which the user can check on their smartphone.

[0263] Step 4:

[0264] The user checks the real-time preview and requests corrections as necessary. If corrections are necessary, the user sends a specific change request to the server via their device. The server then asks the AI ​​engine to regenerate the ad and generate a new creative. If no corrections are required, the user "approves" the generated ad creative.

[0265] Input: User's correction request (or approval)

[0266] Output: Revised ad creative (or approved ad creative)

[0267] Specific operation: The user operates the smartphone interface and taps the correction request or approval button. The server receives the input and performs the necessary processing.

[0268] Step 5:

[0269] After receiving final approval from the user, the server schedules and configures the ad delivery, including the ad delivery start date, end date, target audience characteristics, budget allocation, etc. Based on this, the server delivers the ad to the ad network.

[0270] Input: Final approved ad creative and delivery schedule

[0271] Output: Ad delivery to ad network

[0272] Specific operation: The server calls the ad network's API and sends the ad creative and delivery schedule data.

[0273] Step 6:

[0274] The server automatically collects the performance of the delivered ads (number of impressions, click-through rate, engagement rate, number of conversions, etc.), analyzes the collected data, and generates a report showing the effectiveness of the ads. This report is sent to the user via their device.

[0275] Input: Ad delivery result data

[0276] Output: Effectiveness report

[0277] Specific operation: The server collects delivery result data from each ad network, generates a report using a data analysis tool, and delivers it to the user's device.

[0278] Step 7:

[0279] Users can check the effectiveness report displayed on their device, which details the ad's performance and areas for improvement. Based on this, users can consider their next advertising strategy.

[0280] Input: Effectiveness report

[0281] Output: Feedback on your next advertising strategy

[0282] Specific operation: The user views the report on the smartphone screen and obtains information to plan their next advertising strategy.

[0283] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0284] The present invention combines a system that efficiently performs a series of advertisement management processes, from inputting advertisement requirements to distribution and report generation, with an emotion engine that recognizes user emotions. A specific embodiment of this system will be described.

[0285] Enter your advertising requirements

[0286] User Action:

[0287] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form allows the user to enter details such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the submit button.

[0288] Terminal processing:

[0289] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[0290] Ad creative generation

[0291] Server side:

[0292] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[0293] Generative AI processing:

[0294] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including content optimized for the target audience.

[0295] Emotion recognition by emotion engine

[0296] Terminal processing:

[0297] While the user is operating the input form, the device uses an emotion engine to recognize the user's emotions in real time. This emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[0298] Server side:

[0299] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[0300] Advertising material inspection

[0301] Server side:

[0302] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[0303] Creative review and approval

[0304] Terminal processing:

[0305] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[0306] User Action:

[0307] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[0308] Preparing for ad delivery

[0309] Server side:

[0310] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[0311] Ad serving

[0312] Server side:

[0313] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[0314] Ad performance collection and reporting

[0315] Server side:

[0316] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[0317] Utilizing Emotional Data

[0318] Server side:

[0319] The collected emotional data is included in ad performance reports, which deepens the emotional understanding of advertising campaigns. Furthermore, the emotional data is used to propose next advertising strategies. For example, past emotional data can be analyzed to suggest what type of creative will be more effective for the next campaign.

[0320] Checking advertising reports and next strategies

[0321] Terminal processing:

[0322] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[0323] User Action:

[0324] Users can use the reports to consider their next advertising strategy. Using the system's built-in strategy suggestion function, they can receive specific suggestions for improvement. For example, they can analyze past emotional data and advertising performance to determine which creatives were effective and incorporate that information into their next strategy.

[0325] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[0326] The processing flow will be explained below.

[0327] Step 1:

[0328] User begins creating ad

[0329] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[0330] Step 2:

[0331] The device displays the input form

[0332] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, and delivery period.

[0333] Step 3:

[0334] User enters advertising requirements

[0335] The user enters the advertising requirements in the displayed input form, and once all the required information has been entered, the user clicks the submit button to confirm the input data.

[0336] Step 4:

[0337] The device sends the input data to the server

[0338] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[0339] Step 5:

[0340] The server passes the data to the generated AI.

[0341] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creative. The generative AI generates optimal designs and copy based on the input information.

[0342] Step 6:

[0343] Generative AI generates ad creatives

[0344] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[0345] Step 7:

[0346] The device activates the emotion engine

[0347] While the user is operating the input form, the device activates an emotion engine and acquires emotion data in real time from the user's facial expressions, voice, etc.

[0348] Step 8:

[0349] Emotion engine analyzes emotional data

[0350] The emotion engine analyzes the acquired data and recognizes the user's emotional state, which is then transmitted to the server.

[0351] Step 9:

[0352] Server inspects generated creative

[0353] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[0354] Step 10:

[0355] The server sends the ad creative to the device

[0356] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[0357] Step 11:

[0358] User reviews ad creative

[0359] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[0360] Step 12:

[0361] Prepare to deliver ads

[0362] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[0363] Step 13:

[0364] Ads delivered to ad networks

[0365] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[0366] Step 14:

[0367] Collect ad performance data

[0368] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[0369] Step 15:

[0370] The server generates the report

[0371] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[0372] Step 16:

[0373] The server sends the report to the device.

[0374] The generated report is sent from the server to the terminal and displayed to the user.

[0375] Step 17:

[0376] User checks the report

[0377] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[0378] Step 18:

[0379] Users consider their next advertising strategy

[0380] Users can use the reports to plan their next advertising strategy. The system's built-in strategy suggestion function allows users to receive specific suggestions for improvement. For example, users can analyze past emotional data and ad performance to determine which creatives were effective and incorporate these into their next strategy.

[0381] Example 2

[0382] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0383] Current advertising management systems have a complicated process from entering advertising requirements to delivering ads and measuring their effectiveness, making it difficult to manage efficiently. Another issue is that they are unable to generate advertising creatives that take user emotions into account in order to improve advertising effectiveness. Furthermore, there is no established method for utilizing emotional data in measuring advertising effectiveness.

[0384] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generating means for generating advertising creatives based on the advertising requirements, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to a distribution network, a means for collecting advertising performance results and generating reports, and a means for recognizing emotion data in real time and utilizing it in generating and adjusting advertising creatives. This makes it possible to streamline the advertising management process and generate advertising creatives that take user emotions into consideration. Furthermore, utilizing emotion data can be expected to propose more effective advertising strategies and improve advertising effectiveness.

[0385] "Advertising requirements" refers to all information required to create and distribute an advertisement, including, but not limited to, the title, description, images, target audience, budget, and distribution period.

[0386] "Generation means" refers to technologies and algorithms for automatically generating advertising creatives based on input advertising requirements, and includes artificial intelligence technologies such as machine learning models.

[0387] "Inspection methods" refers to technologies and algorithms used to filter the content of generated advertising creatives and remove inappropriate elements.

[0388] "Delivery Network" means the online and offline outlets and platforms through which advertising is delivered to a target audience, including, specifically, major online advertising networks and partnerships.

[0389] "Advertising performance results" refers to data on the effect that delivered advertisements had on users, including the number of impressions, click-through rate, engagement rate, and number of conversions.

[0390] "Report generation" refers to the process of evaluating and analyzing advertising campaigns based on collected advertising performance results and compiling the results into a document.

[0391] "Emotion data" refers to an emotional state recognized based on data such as a user's facial expression, voice, and operation log.

[0392] "Advertising creative" refers to advertising materials generated based on advertising requirements, and specifically includes images, text, layout, etc.

[0393] "Generative AI engine" refers to a platform or algorithm that uses artificial intelligence technology to automatically generate advertising creatives based on input data.

[0394] The present invention is a system for efficiently performing a series of advertising management processes, from inputting advertising requirements to distribution and report generation, and is combined with an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[0395] Enter your advertising requirements

[0396] User Action:

[0397] Users start the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form contains fields for entering details such as the ad title, description, image, target audience, budget, and delivery period. For example, users enter the following information:

[0398] Title: "Experience the next generation smartphone now"

[0399] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[0400] Image: New product photos

[0401] Target audience: Technology-interested men and women aged 25-45

[0402] Budget: 500,000 yen

[0403] Distribution period: November 1st to December 31st, 2023

[0404] Terminal processing:

[0405] The terminal provides an interface for sending information entered by the user to the server, converting the input data into a structured format such as JSON and sending it to the server.

[0406] Ad creative generation

[0407] Server side:

[0408] The server passes the advertising requirements received from the device to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are then sent back to the server.

[0409] Examples of prompts include:

[0410] Please use the information below to generate advertising creative for next-generation smartphones.

[0411] Title: Experience the next generation smartphone now

[0412] Description: A next-generation smartphone with innovative features and design. Learn more here.

[0413] Image: [URL of new product photo]

[0414] Target audience: Technology-interested men and women aged 25-45

[0415] Emotion recognition by emotion engine

[0416] Terminal processing:

[0417] The device uses an emotion engine to recognize the user's emotions in real time while the user is operating the input form. Emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[0418] Server side:

[0419] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[0420] Inspection and distribution of advertising materials

[0421] Server side:

[0422] The generated ad creatives are inspected by the server's inspection means to check whether the ad contains violent or inappropriate content, and if any inappropriate content is found, it is automatically corrected or instructed to be regenerated. Ad creatives that pass inspection are delivered in a format optimized for each delivery network.

[0423] Ad performance collection and reporting

[0424] Server side:

[0425] After an ad is delivered, ad performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions are collected. The collected data is analyzed and a detailed report is automatically generated. This report details the effectiveness of the ad and areas for improvement.

[0426] Utilizing emotion data and next-generation strategies

[0427] Server side:

[0428] The collected emotional data is also included in ad performance reports. A detailed understanding of emotional responses can be used to suggest future advertising strategies. For example, analyzing past emotional data can suggest which creative elements were most effective in the next campaign.

[0429] Terminal side processing and user side processing:

[0430] The generated report is sent to the terminal and displayed to the user. The user can use the report to consider their next advertising strategy and receive specific suggestions for improvement using the system's strategy suggestion function.

[0431] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[0432] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0433] Step 1:

[0434] User Action:

[0435] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. Specifically, the user enters the following information into the form:

[0436] title

[0437] Description

[0438] image

[0439] Target Audience

[0440] budget

[0441] Distribution period

[0442] Input: Ad details (title, description, image, target audience, budget, delivery period)

[0443] Output: Data entered in the input form

[0444] Step 2:

[0445] Terminal processing:

[0446] The terminal converts the contents of the input form into a structured data format (for example, JSON format) and sends it to the server. Specifically, the data is structured as follows:

[0447] Ad title: "Experience the next generation smartphone now"

[0448] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[0449] Image URL: "example.com / image.png"

[0450] Target audience: "Men and women aged 25-45 who are interested in technology"

[0451] Budget: 500,000 yen

[0452] Distribution period: November 1st to December 31st, 2023

[0453] Input: Data entered into an input form

[0454] Output: Structured data to send to the server

[0455] Step 3:

[0456] Server side:

[0457] The server stores the received advertising requirements in a database and requests the AI ​​engine to generate advertising creatives. Specifically, the server sends the following prompt to the AI ​​engine:

[0458] Please use the information below to generate advertising creative for next-generation smartphones.

[0459] Title: Experience the next generation smartphone now

[0460] Description: A next-generation smartphone with innovative features and design. Learn more here.

[0461] Image: example.com / image.png

[0462] Target audience: Technology-interested men and women aged 25-45

[0463] Input: Structured ad requirements data

[0464] Output: Prompt sent to the generative AI engine

[0465] Step 4:

[0466] Processing by the generative AI engine:

[0467] The generative AI engine automatically generates ad creatives based on prompt text. Specifically, it generates the following data:

[0468] Advertising banner image

[0469] Ad text

[0470] Layout Information

[0471] Input: Prompt received from the server

[0472] Output: Generated ad creative data (images, text, layout)

[0473] Step 5:

[0474] Server side:

[0475] The ad creative returned by the generation AI engine is received and passed to the inspection means. Specifically, the ad creative content is checked to see if there is any inappropriate content.

[0476] Input: Generated ad creative data

[0477] Output: Ad creative data that passes inspection

[0478] Step 6:

[0479] Server side:

[0480] After the ad creative passes inspection, it is provided to the distribution network in an optimized format, for example, by adapting the creative to the format of each distribution network.

[0481] Input: Ad creative data that has passed inspection

[0482] Output: Ad creative data optimized for each distribution network

[0483] Step 7:

[0484] Terminal processing:

[0485] The generated ad creative is sent to the terminal and displayed for user confirmation, specifically displaying a screen that allows the user to preview the ad creative.

[0486] Input: Ad creative data optimized for each distribution network

[0487] Output: Ad creative displayed on device

[0488] Step 8:

[0489] User Action:

[0490] The user can review the ad and click the "Approve" button for final confirmation. If necessary, they can request corrections.

[0491] Input: Previewed ad creative

[0492] Output: Approval or correction request

[0493] Step 9:

[0494] Server side:

[0495] Once final approval is received, the schedule and delivery settings for ad delivery are set, including the delivery start date, end date, target audience characteristics, and budget allocation.

[0496] Input: User authorization data

[0497] Output: Ad delivery schedule and delivery setting data

[0498] Step 10:

[0499] Server side:

[0500] The advertisements are distributed to each distribution network according to a set schedule. Specifically, the advertisement material is transmitted to the distribution network.

[0501] Input: Distribution setting data

[0502] Output: Ad creative sent to the delivery network

[0503] Step 11:

[0504] Server side:

[0505] It collects ad performance results and generates reports. Specifically, it collects and analyzes the following data:

[0506] Impressions

[0507] Click-through rate

[0508] Engagement Rate

[0509] Conversions

[0510] Input: Performance data of delivered ads

[0511] Output: Ad performance report

[0512] Step 12:

[0513] Server side:

[0514] The system analyzes emotional data included in advertising campaign reports and uses it to propose next-generation strategies. Specifically, it compares past emotional data with advertising performance and proposes optimal creatives.

[0515] Input: Ad performance reports and sentiment data

[0516] Output: Proposal data for next advertising strategy

[0517] Step 13:

[0518] Terminal processing:

[0519] The generated report is sent to the terminal and displayed to the user.

[0520] Input: Ad Performance Report

[0521] Output: Report displayed on terminal

[0522] These processing steps allow advertisers to efficiently generate, distribute, measure the effectiveness of their ads, and develop next-generation strategies. Furthermore, by utilizing emotion data, they can create ad creatives that are more relevant to their target audience.

[0523] (Application example 2)

[0524] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0525] Traditional ad management systems generate ad creatives without considering user emotions, making it difficult to resonate with the target audience. Furthermore, the ad creative generation process is complex and time-consuming, and there is insufficient measurement of ad effectiveness after delivery. This makes it difficult for advertisers to optimize their ad campaigns, potentially resulting in wasted budgets.

[0526] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generation means for generating advertising creatives based on the advertising requirements, an emotion recognition means for recognizing user emotions in real time, a means for using emotion data to generate and adjust advertising creatives, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to an ad network, and a means for collecting advertising performance results and generating reports. This enables the generation of advertising creatives that take user emotions into consideration, thereby increasing empathy with the target audience. It also streamlines the process from ad generation to delivery and effectiveness measurement, making it easier to optimize advertising campaigns.

[0527] "Advertising requirements" refers to a collection of information required to run an advertising campaign, including details such as the ad title, description, images, target audience, budget, and distribution period.

[0528] "Generative method" refers to the process of using machine learning models or generative AI to automatically generate advertising creative based on input advertising requirements.

[0529] An "emotion recognition means" is a combination of a device and software for analyzing a user's facial expressions and voice in real time and acquiring emotional data.

[0530] "Emotion data" is information about the user's emotional state obtained by the emotion recognition means, and is used to generate and adjust advertising creatives.

[0531] "Inspection method" refers to the process used to filter generated ad creatives to ensure they do not contain inappropriate content.

[0532] "Delivery method" refers to the process by which the inspected ad creative is sent to the ad network, which then displays the ad to the target audience.

[0533] "Advertising performance" refers to performance indicators after an advertisement is delivered, and specifically includes the number of impressions, click-through rate, engagement rate, number of conversions, etc.

[0534] "Collection means" refers to the process for collecting performance data after advertisement delivery, which is used to measure the effectiveness of the advertisement.

[0535] "Report generation means" refers to a process for analyzing collected advertising performance results and automatically generating reports.

[0536] "Camera and microphone" are input devices that capture the user's facial expressions and voice to provide data for emotion recognition.

[0537] An "emotion recognition engine" is software that analyzes data acquired by a camera and microphone and estimates the user's emotional state.

[0538] A "machine learning model" is a collection of algorithms that learn patterns from input data and automatically generate advertising creatives.

[0539] "Filtering measures" are processes used to inspect the advertising creative generated by the machine learning model to ensure it does not contain inappropriate content.

[0540] This invention provides a system that automates a series of processes from inputting advertising requirements to generating advertising creatives, recognizing emotions, delivering advertisements, and measuring their effectiveness. Specific embodiments of this system are described below.

[0541] System Program

[0542] Hardware and Software:

[0543] The system utilizes advertisers' smartphones, servers, and emotion recognition engines (e.g., Affectiva SDK), and uses generative AI models (e.g., OpenAI GPT-3) to generate ad creatives. The main components and their functions are listed below.

[0544] Enter your advertising requirements:

[0545] On the device, the user uses a dedicated management screen to input advertising requirements such as ad title, description, image, target audience, budget, distribution period, etc. This information is structured and sent to the server.

[0546] Emotion recognition:

[0547] The device is equipped with a camera and microphone, which capture the user's facial expressions and voice in real time. An emotion recognition engine analyzes this data to obtain the user's emotional data.

[0548] Ad creative generation:

[0549] The server requests the generative AI model to generate ad creatives based on the received ad requirements and emotional data. The generative AI model automatically generates ad creatives that take the emotional data into account.

[0550] Ad creative inspection:

[0551] The generated ad creative is inspected by the server using filtering measures to ensure it does not contain inappropriate content.

[0552] Ad serving:

[0553] Ad creatives that pass inspection are distributed through ad networks.

[0554] Ad performance collection and reporting:

[0555] After the ad is delivered, the server collects performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions. The collected data is analyzed to generate a report on the effectiveness of the ad. This report also includes sentiment data, which can be used to plan future advertising strategies.

[0556] Specific examples of processing

[0557] For example, consider an advertiser creating an ad titled "New Product Announcement" to introduce the latest gadget packed with technological innovation. The user inputs the following ad requirements:

[0558] Title: New Product Announcement

[0559] Description: Introducing the latest gadgets packed with technological innovation.

[0560] Image: new_gadget.png

[0561] Target Audience: Technology Enthusiasts

[0562] Budget: 100,000 yen

[0563] Distribution period: 7 days

[0564] After sending this information to the server, an emotion recognition engine analyzes the user's facial expressions and voice to obtain emotional data such as "75% delight," "20% surprise," and "15% neutral." Based on this emotional data and the advertising requirements, a generative AI model generates advertising creative, creating an ad with a "New Product Launch" banner and the tagline "Amazing Innovation, Buy Now!"

[0565] In this way, this system makes it possible to generate advertising creatives that take user emotions into account, thereby increasing empathy with the target audience. It also streamlines the process from ad creation to distribution and effectiveness measurement.

[0566] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0567] Step 1:

[0568] The user opens a dedicated management screen and inputs the ad requirements, specifically, information such as the ad title, description, image file path, target audience, budget, and distribution period into a form. This input data is structured and sent from the device to the server.

[0569] Step 2:

[0570] The device uses a camera and microphone to capture the user's facial expressions and voice data in real time. This data is sent to an emotion recognition engine, which generates emotion data. For example, the emotion (happiness, surprise, etc.) that the user is feeling during the creation of an advertisement is analyzed and that data is acquired.

[0571] Step 3:

[0572] The server sends the input advertising requirements and the acquired emotional data to the generative AI model. The generative AI model generates advertising creatives based on this data. In doing so, it reflects content based on the emotional data and creates advertising materials optimized for the target audience. For example, for a title such as "New Product Launch," an advertisement is generated that includes the catchphrase "Amazing Technological Innovation, Check It Out Now!"

[0573] Step 4:

[0574] The server sends the generated ad creative to an inspection tool to filter it for inappropriate content. The filtering checks for violent or adult content, and if there are any problems, they are corrected. For example, automatic checks can be done using language filtering or image recognition.

[0575] Step 5:

[0576] Ad creatives that pass inspection are sent from the server to the device and displayed to the user. The user can review the displayed ad and request corrections if necessary. If the user wants to make corrections, their feedback is sent back to the server and the ad is regenerated by the generative AI model.

[0577] Step 6:

[0578] Once the user gives final approval, the server sets up ad distribution settings, including distribution start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the server distributes the ads to each ad network.

[0579] Step 7:

[0580] Once the ad distribution begins, the server collects the ad performance results (number of impressions, click-through rate, engagement rate, number of conversions, etc.) in real time. The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad during the distribution period and areas for improvement.

[0581] Step 8:

[0582] The collected emotional data is also included in the report and used to propose the next advertising strategy. The server analyzes past emotional data and suggests what kind of advertising creative will be more effective for the next campaign, with the aim of maximizing advertising effectiveness.

[0583] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0584] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0585] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0586] [Second embodiment]

[0587] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0588] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0589] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0590] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0591] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0592] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0593] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0594] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0595] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0596] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0597] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0598] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0599] The present invention is a system for efficiently carrying out a series of advertising management processes, from inputting advertising requirements to distribution and report generation. A specific embodiment of this system will be described.

[0600] 1. Enter your advertising requirements

[0601] User Action:

[0602] Users begin creating ads on a dedicated management screen. Clicking the "Create Ad" button displays an input form. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. After entering the required information in the form and clicking the submit button, this data is sent to the server via the device.

[0603] Terminal processing:

[0604] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[0605] 2. Generating ad creatives

[0606] Server side:

[0607] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[0608] Generative AI processing:

[0609] Generative AI uses machine learning models to automatically generate ad creatives based on input factors, including optimal design and wording to maximize ad effectiveness.

[0610] 3. Inspection of advertising materials

[0611] Server side:

[0612] The generated ad creatives are subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If non-compliant content is found, it is automatically corrected or instructed to be regenerated.

[0613] 4. Review and Approval of Advertising Materials

[0614] Terminal processing:

[0615] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[0616] User Action:

[0617] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[0618] 5. Preparing for ad delivery

[0619] Server side:

[0620] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[0621] 6. Delivery of advertisements

[0622] Server side:

[0623] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[0624] 7. Collecting and reporting on advertising performance results

[0625] Server side:

[0626] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[0627] 8. Check advertising reports and plan your next strategy

[0628] Terminal processing:

[0629] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[0630] User Action:

[0631] Users can use the reports to consider their next advertising strategy, and by using the system's built-in strategy proposal function, they can receive specific suggestions for improvement.

[0632] Specific examples

[0633] Consider the case where a small business advertiser wants to advertise an in-store sale.

[0634] 1. User starts creating an ad:

[0635] Users select "Create Ad" on the admin screen, enter the title "Winter Sale," the description "20% off all items," upload a photo of their store as the image, and enter their budget and target audience.

[0636] 2. Ad creative generation:

[0637] The server inputs this information into the AI ​​generator, which then generates the appropriate design and copy. For example, a catchy slogan such as "Click here for limited-time coupons" is automatically generated.

[0638] 3. Inspect the generated ad:

[0639] Inspect server-generated content to ensure it does not contain inappropriate content.

[0640] 4. Ad Review and Approval:

[0641] The generated advertisement is displayed to the user, who then reviews and approves the content.

[0642] 5. Preparation and implementation of advertising distribution:

[0643] The server sets the delivery schedule and settings, and delivers advertisements to domestic and international ad networks based on the settings.

[0644] 6. Performance collection and reporting:

[0645] It collects advertising performance data and generates effectiveness reports based on this data.

[0646] 7. Review the report and consider your next strategy:

[0647] The user reviews the report and plans their next advertising strategy based on the obtained data.

[0648] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[0649] The processing flow will be explained below.

[0650] Step 1:

[0651] User begins creating ad

[0652] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[0653] Step 2:

[0654] The device displays the input form

[0655] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, duration, etc.

[0656] Step 3:

[0657] User enters advertising requirements

[0658] The user enters the advertising requirements into the displayed input form, and once all the required information has been entered, the user clicks the submit button.

[0659] Step 4:

[0660] The device sends the input data to the server

[0661] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[0662] Step 5:

[0663] The server passes the data to the generated AI.

[0664] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creatives. At this point, the generative AI generates optimal designs and copy.

[0665] Step 6:

[0666] Generative AI generates ad creatives

[0667] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[0668] Step 7:

[0669] Server inspects generated creative

[0670] The server filters the generated ad creative to ensure it does not contain violent, adult or inappropriate content.

[0671] Step 8:

[0672] The server sends the ad creative to the device

[0673] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[0674] Step 9:

[0675] User reviews ad creative

[0676] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[0677] Step 10:

[0678] Prepare to deliver ads

[0679] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[0680] Step 11:

[0681] Ads delivered to ad networks

[0682] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[0683] Step 12:

[0684] Collect ad performance data

[0685] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[0686] Step 13:

[0687] The server generates the report

[0688] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[0689] Step 14:

[0690] The server sends the report to the device.

[0691] The generated report is sent from the server to the terminal and displayed to the user.

[0692] Step 15:

[0693] User checks the report

[0694] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[0695] Step 16:

[0696] Users consider their next advertising strategy

[0697] Users can plan their next advertising strategy based on the report results, and can receive specific suggestions for improvement by using the system's built-in strategy suggestion function.

[0698] Example 1

[0699] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0700] With conventional ad management systems, the process from entering advertising requirements to distribution and report generation was complex and time-consuming, making it difficult to operate efficiently. Furthermore, the creation and testing of ad creatives required a lot of manual work, making it difficult to maximize advertising effectiveness. This made it difficult to run simple and effective ad campaigns, especially for advertisers with limited resources, such as small and medium-sized businesses.

[0701] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0702] In this invention, the server includes means for accepting input of advertising requirements, means for structuring the advertising requirements and transmitting them to the server, and means for generating advertising creatives using a generative AI model based on the advertising requirements. This enables efficient automatic generation and inspection of advertising creatives, preparation for distribution, distribution, collection of results, and report generation as a single process.

[0703] "Advertising requirements" refers to the information required to create and distribute an advertisement, including details such as the title, description, image, target audience, budget, and distribution period.

[0704] A "generative AI model" is an algorithm or system that uses machine learning technology to automatically generate advertising creatives (e.g., text, images, layout, etc.).

[0705] "Server" refers to the part of the computer system that receives, processes, and stores data sent by users, generates advertising creatives using generative AI models, inspects the results of such generation, and ultimately delivers and generates reports.

[0706] "Advertising creative" refers to all materials used in advertising, such as text, images, and layout, and is content designed to maximize advertising effectiveness.

[0707] "User" refers to an advertiser who uses the system to create, manage, and distribute advertisements.

[0708] "Input Form" means a web form used by a User to enter advertising requirements, where specific fields may be entered to provide further information about the advertisement.

[0709] "Inspection" refers to the process of checking the content of the generated advertising creative to ensure that it does not contain inappropriate content (e.g., violent or adult content).

[0710] An "ad network" is a network that delivers advertisements to multiple websites, and examples include Google Ads and Facebook Ads.

[0711] "Report" means a document containing detailed analytical information about the performance of an Ad, including data such as impressions, click-through rates, engagement rates, and conversions.

[0712] "Next advertising strategy" refers to the specific policies and methods for planning and executing the next advertising activity based on the results of past advertising campaigns.

[0713] The present invention is a system that automates and streamlines a series of advertising management processes, from inputting advertising requirements to generating, inspecting, and distributing advertising creatives, collecting results, and generating reports. A specific embodiment of this system will be described.

[0714] First, the user accesses the management screen using a dedicated web browser. When the "Create Ad" button on this management screen is clicked, an input form for entering the ad requirements is displayed. This input form contains fields for entering information such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the "Submit" button.

[0715] The input data is structured on the device via a JavaScript API and converted to JSON format. This data is then sent to the server using HTTPS. Once the data transfer is complete, the server receives the data and passes it to a generative AI model. This generative AI model uses OpenAI's GPT series, which uses machine learning technology, for example.

[0716] The server generates a prompt based on the advertising requirements and sends it to the AI ​​model. An example of a prompt might be, "Generate advertising creative based on the following information: Title: Winter Sale, Description: 20% off all items, Image: Store photo, Target audience: Housewives, Budget: 10,000 yen, Distribution period: 1 week."

[0717] The generative AI model receives a prompt and automatically generates ad creatives based on it. The generated creatives are sent back to the server, where content inspection is performed. This inspection method uses NLP and image analysis technologies to check whether the generated creatives contain violent or adult content. If inappropriate content is detected, it is automatically filtered or corrected.

[0718] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user checks the generated ad to ensure there are no omissions or errors. If there are no problems, the user clicks the "Approve" button for final confirmation.

[0719] After receiving the user's final approval, the server sets the schedule and distribution settings for ad distribution. Specifically, the distribution start date, end date, target audience characteristics, budget allocation, etc. are set. Once the settings are complete, the ads are distributed in a format optimized for each ad network. Examples of ad networks include Google Ads and Facebook Ads.

[0720] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. The server analyzes this data and automatically generates a report, which is sent to the device and displayed to the user.

[0721] Finally, users review the report and consider their next advertising strategy. The system's built-in strategy suggestion function allows users to make specific suggestions for improvement or formulate new strategies.

[0722] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[0723] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0724] Step 1:

[0725] User processing

[0726] Users access the management screen using a dedicated web browser. When they click the "Create Ad" button, an input form for entering their ad requirements appears. The input form includes fields for the ad title, description, image, target audience, budget, distribution period, etc. The user enters information in these fields and clicks the "Submit" button.

[0727] Input: Ad title, description, image, target audience, budget, delivery period and other details.

[0728] Output: Structured ad requirements data.

[0729] Step 2:

[0730] Terminal side processing

[0731] The device structures the advertising requirements data entered by the user via a JavaScript API and converts it into JSON format, which is then sent to the server via HTTPS. The device also checks whether the data has been transferred correctly.

[0732] Input: Structured ad requirements data.

[0733] Output: Ad requirements JSON data sent to the server.

[0734] Step 3:

[0735] Server-side processing

[0736] The server passes the received ad requirements JSON data to a generative AI model. The generative AI model can be, for example, OpenAI's GPT series, which uses machine learning technology. The server generates a prompt based on the ad requirements and sends it to the generative AI model.

[0737] Input: Ad requirements JSON data.

[0738] Output: The prompt sentence that is passed to the generative AI model.

[0739] Step 4:

[0740] Processing by generative AI models

[0741] The generative AI model receives the prompt text and automatically generates ad creatives based on it. The generated creatives are sent back to the server via API. The generated ad creatives include text, image placement, layout, etc.

[0742] Input: Prompt statement.

[0743] Output: The generated ad creative.

[0744] Step 5:

[0745] Server-side processing

[0746] The server inputs the received ad creative into the content inspection module. This module uses NLP and image analysis technologies to check whether the generated creative contains violent or adult content. If inappropriate content is detected, it automatically corrects it or sends a regeneration instruction to the generation AI model.

[0747] Input: The generated ad creative.

[0748] Output: Inspected ad creative.

[0749] Step 6:

[0750] Terminal side processing

[0751] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user reviews the ad and checks for any omissions or errors. If there are no problems, they click the "Approve" button. If necessary, they can enter correction requests and resubmit.

[0752] Input: Inspected ad creative.

[0753] Output: User approval or correction request.

[0754] Step 7:

[0755] Server-side processing

[0756] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery. Specifically, it sets the delivery start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the ad is delivered in an optimized format for each ad network.

[0757] Input: User approval.

[0758] Output: Ad delivery schedule and configuration information.

[0759] Step 8:

[0760] Server-side processing

[0761] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. This data is analyzed and automatically generated into a report, which is then sent to the device and displayed to the user.

[0762] Input: Ad performance data.

[0763] Output: The generated ad effectiveness report.

[0764] Step 9:

[0765] User processing

[0766] Users can review the reports and consider their next advertising strategy. By using the system's built-in strategy suggestion function, they can propose specific improvements or formulate new strategies.

[0767] Input: The generated ad effectiveness report.

[0768] Output: Next advertising strategy and improvement suggestions.

[0769] (Application example 1)

[0770] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0771] Conventional ad generation systems make it difficult for users to efficiently create and distribute ad creatives. Furthermore, the effectiveness of generated ads cannot be predicted in advance, leading to uncertainty about ad performance. Furthermore, the inability to check generated ads in real time and make immediate corrections can lead to a decline in user satisfaction.

[0772] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0773] In this invention, the server includes means for accepting input of advertising requirements, means for generating advertising creatives based on the advertising requirements, means for inspecting the generated advertising creatives, means for distributing advertising creatives that pass inspection to an ad network, means for collecting advertising performance results and generating reports, means for providing real-time previews of the advertising creatives, and means for predicting the effectiveness of the generated advertising creatives. This allows users to efficiently manage the entire process from creating advertising creatives to distributing them, and enables them to predict the effectiveness of advertising in advance. Furthermore, the real-time preview function allows users to instantly check and modify advertising content, thereby improving user satisfaction.

[0774] The "means for inputting advertisement requirements" is a means for providing an interface for a user to input details such as the title, description, image, target audience, budget, and distribution period of an advertisement.

[0775] "Generation means" refers to a device or program that automatically generates advertising creatives (images, text, layout, etc.) using generation AI based on advertising requirements entered by the user.

[0776] The "inspection means" is a device or program that checks whether the generated advertising creative contains inappropriate content and performs filtering.

[0777] A "distribution means" is a device or program that transmits advertising creatives that have passed inspection to an ad network and distributes advertisements based on a set schedule.

[0778] A "report generation means" is a device or program that collects the performance results of delivered advertisements (number of impressions, click rate, engagement rate, number of conversions, etc.), analyzes them, and automatically generates a report showing the effectiveness of the advertisements.

[0779] The "real-time preview means" is a means for providing an interface that allows a user to check the results of creation in real time during the process of creating an advertising creative and make any necessary corrections immediately.

[0780] The "effectiveness prediction means" is a device or program that uses past advertising data and a machine learning model to predict the advertising effectiveness of the generated advertising creative in advance and present it to the user.

[0781] A "machine learning model" is an algorithm or model that learns from past data and is used to generate advertising creatives and predict their effectiveness.

[0782] This invention relates to an advertising management system that performs an integrated process from inputting advertising requirements to generating, inspecting, distributing, measuring effectiveness, and generating reports. The mechanism for implementing this system is described below.

[0783] Enter your advertising requirements

[0784] Users begin creating ads using the dedicated smartphone application "SmartAd Creator." When users click the "Create Ad" button on the application's management screen, an input form for ad requirements is displayed. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. The input data is sent to the server by the smartphone application.

[0785] Ad creative generation

[0786] The server receives the ad requirements sent by the user and passes them to a generative AI engine (e.g., GPT-3 or Stable Diffusion). The generative AI engine automatically generates ad creatives (images, text, layout, etc.) based on these requirements. The generated ad creatives are sent back to the server.

[0787] Real-time preview and effectiveness prediction of advertising materials

[0788] The server provides a function to preview the generated ad creative in real time. Users can check this preview through a smartphone application. The server also uses past advertising data and machine learning models to predict the effectiveness of the generated ad creative in advance and presents the results to users.

[0789] Ad creative inspection

[0790] The generated ad creatives are then subject to content inspection by server-based inspection means, which filters the ads for inappropriate content (e.g., violent, adult, or discriminatory language).

[0791] Ad serving

[0792] After the user approves the ad creative, the server sets a distribution schedule and distributes the ad to the ad network. The distribution is carried out based on the set schedule, and the server also manages the target audience characteristics and budget allocation.

[0793] Measurement and reporting

[0794] The server automatically collects and analyzes the performance of the advertisements (number of impressions, click-through rate, engagement rate, number of conversions, etc.) and generates an effectiveness report, which is displayed to the user via a smartphone application.

[0795] Hardware and software used

[0796] Smartphone: "SmartAd Creator" application

[0797] Server: Receives advertising requirements, connects with AI engine, generates advertising creatives, provides real-time previews, predicts effectiveness, inspects content, delivers ads, measures effectiveness, generates reports

[0798] Generative AI engine: GPT-3, Stable Diffusion

[0799] Machine learning model: Advertising effectiveness prediction

[0800] Specific examples

[0801] For example, consider a small business advertiser announcing a "Winter Sale." The user uses the "SmartAd Creator" application and enters the following prompt text:

[0802] Prompt statement:

[0803] I would like to create an ad to announce this month's members-only sale. The sale runs until the end of the month, with a total budget of 500,000 yen, and the main target audience is women in their 20s and 30s. The ad title should be "Members-only sale," and the description should be "All products are eligible. Don't miss out on this special discount!" I would like to use a photo from inside the store.

[0804] Based on this prompt, the generative AI engine generates ad creatives, and the server provides real-time previews and effectiveness predictions. After the user confirms, modifies, and approves the ad, it is automatically distributed to the ad network. After the ad is distributed, the server measures its effectiveness and generates a report that is provided to the user to support their next advertising strategy.

[0805] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0806] Step 1:

[0807] The user starts the "SmartAd Creator" application on their smartphone and starts creating an ad. When the user clicks the "Create Ad" button on the management screen, an input form for the ad requirements is displayed. The form has fields for entering details such as the ad title, description, image, target audience, budget, and distribution period. When the user enters data into these fields and clicks the "Submit" button, the input data is sent from the device to the server.

[0808] Input: Ad title, description, image, target audience, budget, delivery period

[0809] Output: Ad requirements data sent to the server

[0810] Specific actions: The user uses the smartphone's touchscreen to enter information into each field and tap the send button.

[0811] Step 2:

[0812] The server receives the ad requirement data sent from the device. The server then passes this data to a generative AI engine (e.g., GPT-3, Stable Diffusion) and requests it to generate ad creatives. The generative AI engine generates optimal ad creatives (images, text, layout, etc.) based on the input information and returns the results to the server.

[0813] Input: Advertising requirements data

[0814] Output: Generated ad creative (images, text, layout)

[0815] Specific operation: The server calls the API of the generation AI engine and passes the advertising requirements as input data. The server receives the generated creative data.

[0816] Step 3:

[0817] The server sends the generated ad creative to the device as a real-time preview. The user can view this real-time preview through a smartphone application. The server also predicts the effectiveness of the generated ad based on past ad data and provides the results to the user. This effectiveness prediction includes, for example, estimates of click-through rate and conversion rate.

[0818] Input: Generated ad creative

[0819] Output: Real-time preview and effect prediction data

[0820] Specific operation: The server delivers the generated advertising creative and the results of the effectiveness prediction to the device, which the user can check on their smartphone.

[0821] Step 4:

[0822] The user checks the real-time preview and requests corrections as necessary. If corrections are necessary, the user sends a specific change request to the server via their device. The server then asks the AI ​​engine to regenerate the ad and generate a new creative. If no corrections are required, the user "approves" the generated ad creative.

[0823] Input: User's correction request (or approval)

[0824] Output: Revised ad creative (or approved ad creative)

[0825] Specific operation: The user operates the smartphone interface and taps the correction request or approval button. The server receives the input and performs the necessary processing.

[0826] Step 5:

[0827] After receiving final approval from the user, the server schedules and configures the ad delivery, including the ad delivery start date, end date, target audience characteristics, budget allocation, etc. Based on this, the server delivers the ad to the ad network.

[0828] Input: Final approved ad creative and delivery schedule

[0829] Output: Ad delivery to ad network

[0830] Specific operation: The server calls the ad network's API and sends the ad creative and delivery schedule data.

[0831] Step 6:

[0832] The server automatically collects the performance of the delivered ads (number of impressions, click-through rate, engagement rate, number of conversions, etc.), analyzes the collected data, and generates a report showing the effectiveness of the ads. This report is sent to the user via their device.

[0833] Input: Ad delivery result data

[0834] Output: Effectiveness report

[0835] Specific operation: The server collects delivery result data from each ad network, generates a report using a data analysis tool, and delivers it to the user's device.

[0836] Step 7:

[0837] Users can check the effectiveness report displayed on their device, which details the ad's performance and areas for improvement. Based on this, users can consider their next advertising strategy.

[0838] Input: Effectiveness report

[0839] Output: Feedback on your next advertising strategy

[0840] Specific operation: The user views the report on the smartphone screen and obtains information to plan their next advertising strategy.

[0841] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0842] The present invention combines a system that efficiently performs a series of advertisement management processes, from inputting advertisement requirements to distribution and report generation, with an emotion engine that recognizes user emotions. A specific embodiment of this system will be described.

[0843] Enter your advertising requirements

[0844] User Action:

[0845] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form allows the user to enter details such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the submit button.

[0846] Terminal processing:

[0847] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[0848] Ad creative generation

[0849] Server side:

[0850] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[0851] Generative AI processing:

[0852] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including content optimized for the target audience.

[0853] Emotion recognition by emotion engine

[0854] Terminal processing:

[0855] While the user is operating the input form, the device uses an emotion engine to recognize the user's emotions in real time. This emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[0856] Server side:

[0857] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[0858] Advertising material inspection

[0859] Server side:

[0860] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[0861] Creative review and approval

[0862] Terminal processing:

[0863] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[0864] User Action:

[0865] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[0866] Preparing for ad delivery

[0867] Server side:

[0868] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[0869] Ad serving

[0870] Server side:

[0871] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[0872] Ad performance collection and reporting

[0873] Server side:

[0874] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[0875] Utilizing Emotional Data

[0876] Server side:

[0877] The collected emotional data is included in ad performance reports, which deepens the emotional understanding of advertising campaigns. Furthermore, the emotional data is used to propose next advertising strategies. For example, past emotional data can be analyzed to suggest what type of creative will be more effective for the next campaign.

[0878] Checking advertising reports and next strategies

[0879] Terminal processing:

[0880] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[0881] User Action:

[0882] Users can use the reports to consider their next advertising strategy. Using the system's built-in strategy suggestion function, they can receive specific suggestions for improvement. For example, they can analyze past emotional data and advertising performance to determine which creatives were effective and incorporate that information into their next strategy.

[0883] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[0884] The processing flow will be explained below.

[0885] Step 1:

[0886] User begins creating ad

[0887] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[0888] Step 2:

[0889] The device displays the input form

[0890] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, and delivery period.

[0891] Step 3:

[0892] User enters advertising requirements

[0893] The user enters the advertising requirements in the displayed input form, and once all the required information has been entered, the user clicks the submit button to confirm the input data.

[0894] Step 4:

[0895] The device sends the input data to the server

[0896] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[0897] Step 5:

[0898] The server passes the data to the generated AI.

[0899] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creative. The generative AI generates optimal designs and copy based on the input information.

[0900] Step 6:

[0901] Generative AI generates ad creatives

[0902] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[0903] Step 7:

[0904] The device activates the emotion engine

[0905] While the user is operating the input form, the device activates an emotion engine and acquires emotion data in real time from the user's facial expressions, voice, etc.

[0906] Step 8:

[0907] Emotion engine analyzes emotional data

[0908] The emotion engine analyzes the acquired data and recognizes the user's emotional state, which is then transmitted to the server.

[0909] Step 9:

[0910] Server inspects generated creative

[0911] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[0912] Step 10:

[0913] The server sends the ad creative to the device

[0914] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[0915] Step 11:

[0916] User reviews ad creative

[0917] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[0918] Step 12:

[0919] Prepare to deliver ads

[0920] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[0921] Step 13:

[0922] Ads delivered to ad networks

[0923] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[0924] Step 14:

[0925] Collect ad performance data

[0926] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[0927] Step 15:

[0928] The server generates the report

[0929] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[0930] Step 16:

[0931] The server sends the report to the device.

[0932] The generated report is sent from the server to the terminal and displayed to the user.

[0933] Step 17:

[0934] User checks the report

[0935] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[0936] Step 18:

[0937] Users consider their next advertising strategy

[0938] Users can use the reports to plan their next advertising strategy. The system's built-in strategy suggestion function allows users to receive specific suggestions for improvement. For example, users can analyze past emotional data and ad performance to determine which creatives were effective and incorporate these into their next strategy.

[0939] Example 2

[0940] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0941] Current advertising management systems have a complicated process from entering advertising requirements to delivering ads and measuring their effectiveness, making it difficult to manage efficiently. Another issue is that they are unable to generate advertising creatives that take user emotions into account in order to improve advertising effectiveness. Furthermore, there is no established method for utilizing emotional data in measuring advertising effectiveness.

[0942] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generating means for generating advertising creatives based on the advertising requirements, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to a distribution network, a means for collecting advertising performance results and generating reports, and a means for recognizing emotion data in real time and utilizing it in generating and adjusting advertising creatives. This makes it possible to streamline the advertising management process and generate advertising creatives that take user emotions into consideration. Furthermore, utilizing emotion data can be expected to propose more effective advertising strategies and improve advertising effectiveness.

[0943] "Advertising requirements" refers to all information required to create and distribute an advertisement, including, but not limited to, the title, description, images, target audience, budget, and distribution period.

[0944] "Generation means" refers to technologies and algorithms for automatically generating advertising creatives based on input advertising requirements, and includes artificial intelligence technologies such as machine learning models.

[0945] "Inspection methods" refers to technologies and algorithms used to filter the content of generated advertising creatives and remove inappropriate elements.

[0946] "Delivery Network" means the online and offline outlets and platforms through which advertising is delivered to a target audience, including, specifically, major online advertising networks and partnerships.

[0947] "Advertising performance results" refers to data on the effect that delivered advertisements had on users, including the number of impressions, click-through rate, engagement rate, and number of conversions.

[0948] "Report generation" refers to the process of evaluating and analyzing advertising campaigns based on collected advertising performance results and compiling the results into a document.

[0949] "Emotion data" refers to an emotional state recognized based on data such as a user's facial expression, voice, and operation log.

[0950] "Advertising creative" refers to advertising materials generated based on advertising requirements, and specifically includes images, text, layout, etc.

[0951] "Generative AI engine" refers to a platform or algorithm that uses artificial intelligence technology to automatically generate advertising creatives based on input data.

[0952] The present invention is a system for efficiently performing a series of advertising management processes, from inputting advertising requirements to distribution and report generation, and is combined with an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[0953] Enter your advertising requirements

[0954] User Action:

[0955] Users start the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form contains fields for entering details such as the ad title, description, image, target audience, budget, and delivery period. For example, users enter the following information:

[0956] Title: "Experience the next generation smartphone now"

[0957] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[0958] Image: New product photos

[0959] Target audience: Technology-interested men and women aged 25-45

[0960] Budget: 500,000 yen

[0961] Distribution period: November 1st to December 31st, 2023

[0962] Terminal processing:

[0963] The terminal provides an interface for sending information entered by the user to the server, converting the input data into a structured format such as JSON and sending it to the server.

[0964] Ad creative generation

[0965] Server side:

[0966] The server passes the advertising requirements received from the device to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are then sent back to the server.

[0967] Examples of prompts include:

[0968] Please use the information below to generate advertising creative for next-generation smartphones.

[0969] Title: Experience the next generation smartphone now

[0970] Description: A next-generation smartphone with innovative features and design. Learn more here.

[0971] Image: [URL of new product photo]

[0972] Target audience: Technology-interested men and women aged 25-45

[0973] Emotion recognition by emotion engine

[0974] Terminal processing:

[0975] The device uses an emotion engine to recognize the user's emotions in real time while the user is operating the input form. Emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[0976] Server side:

[0977] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[0978] Inspection and distribution of advertising materials

[0979] Server side:

[0980] The generated ad creatives are inspected by the server's inspection means to check whether the ad contains violent or inappropriate content, and if any inappropriate content is found, it is automatically corrected or instructed to be regenerated. Ad creatives that pass inspection are delivered in a format optimized for each delivery network.

[0981] Ad performance collection and reporting

[0982] Server side:

[0983] After an ad is delivered, ad performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions are collected. The collected data is analyzed and a detailed report is automatically generated. This report details the effectiveness of the ad and areas for improvement.

[0984] Utilizing emotion data and next-generation strategies

[0985] Server side:

[0986] The collected emotional data is also included in ad performance reports. A detailed understanding of emotional responses can be used to suggest future advertising strategies. For example, analyzing past emotional data can suggest which creative elements were most effective in the next campaign.

[0987] Terminal side processing and user side processing:

[0988] The generated report is sent to the terminal and displayed to the user. The user can use the report to consider their next advertising strategy and receive specific suggestions for improvement using the system's strategy suggestion function.

[0989] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[0990] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0991] Step 1:

[0992] User Action:

[0993] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. Specifically, the user enters the following information into the form:

[0994] title

[0995] Description

[0996] image

[0997] Target Audience

[0998] budget

[0999] Distribution period

[1000] Input: Ad details (title, description, image, target audience, budget, delivery period)

[1001] Output: Data entered in the input form

[1002] Step 2:

[1003] Terminal processing:

[1004] The terminal converts the contents of the input form into a structured data format (for example, JSON format) and sends it to the server. Specifically, the data is structured as follows:

[1005] Ad title: "Experience the next generation smartphone now"

[1006] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[1007] Image URL: "example.com / image.png"

[1008] Target audience: "Men and women aged 25-45 who are interested in technology"

[1009] Budget: 500,000 yen

[1010] Distribution period: November 1st to December 31st, 2023

[1011] Input: Data entered into an input form

[1012] Output: Structured data to send to the server

[1013] Step 3:

[1014] Server side:

[1015] The server stores the received advertising requirements in a database and requests the AI ​​engine to generate advertising creatives. Specifically, the server sends the following prompt to the AI ​​engine:

[1016] Please use the information below to generate advertising creative for next-generation smartphones.

[1017] Title: Experience the next generation smartphone now

[1018] Description: A next-generation smartphone with innovative features and design. Learn more here.

[1019] Image: example.com / image.png

[1020] Target audience: Technology-interested men and women aged 25-45

[1021] Input: Structured ad requirements data

[1022] Output: Prompt sent to the generative AI engine

[1023] Step 4:

[1024] Processing by the generative AI engine:

[1025] The generative AI engine automatically generates ad creatives based on prompt text. Specifically, it generates the following data:

[1026] Advertising banner image

[1027] Ad text

[1028] Layout Information

[1029] Input: Prompt received from the server

[1030] Output: Generated ad creative data (images, text, layout)

[1031] Step 5:

[1032] Server side:

[1033] The ad creative returned by the generation AI engine is received and passed to the inspection means. Specifically, the ad creative content is checked to see if there is any inappropriate content.

[1034] Input: Generated ad creative data

[1035] Output: Ad creative data that passes inspection

[1036] Step 6:

[1037] Server side:

[1038] After the ad creative passes inspection, it is provided to the distribution network in an optimized format, for example, by adapting the creative to the format of each distribution network.

[1039] Input: Ad creative data that has passed inspection

[1040] Output: Ad creative data optimized for each distribution network

[1041] Step 7:

[1042] Terminal processing:

[1043] The generated ad creative is sent to the terminal and displayed for user confirmation, specifically displaying a screen that allows the user to preview the ad creative.

[1044] Input: Ad creative data optimized for each distribution network

[1045] Output: Ad creative displayed on device

[1046] Step 8:

[1047] User Action:

[1048] The user can review the ad and click the "Approve" button for final confirmation. If necessary, they can request corrections.

[1049] Input: Previewed ad creative

[1050] Output: Approval or correction request

[1051] Step 9:

[1052] Server side:

[1053] Once final approval is received, the schedule and delivery settings for ad delivery are set, including the delivery start date, end date, target audience characteristics, and budget allocation.

[1054] Input: User authorization data

[1055] Output: Ad delivery schedule and delivery setting data

[1056] Step 10:

[1057] Server side:

[1058] The advertisements are distributed to each distribution network according to a set schedule. Specifically, the advertisement material is transmitted to the distribution network.

[1059] Input: Distribution setting data

[1060] Output: Ad creative sent to the delivery network

[1061] Step 11:

[1062] Server side:

[1063] It collects ad performance results and generates reports. Specifically, it collects and analyzes the following data:

[1064] Impressions

[1065] Click-through rate

[1066] Engagement Rate

[1067] Conversions

[1068] Input: Performance data of delivered ads

[1069] Output: Ad performance report

[1070] Step 12:

[1071] Server side:

[1072] The system analyzes emotional data included in advertising campaign reports and uses it to propose next-generation strategies. Specifically, it compares past emotional data with advertising performance and proposes optimal creatives.

[1073] Input: Ad performance reports and sentiment data

[1074] Output: Proposal data for next advertising strategy

[1075] Step 13:

[1076] Terminal processing:

[1077] The generated report is sent to the terminal and displayed to the user.

[1078] Input: Ad Performance Report

[1079] Output: Report displayed on terminal

[1080] These processing steps allow advertisers to efficiently generate, distribute, measure the effectiveness of their ads, and develop next-generation strategies. Furthermore, by utilizing emotion data, they can create ad creatives that are more relevant to their target audience.

[1081] (Application example 2)

[1082] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1083] Traditional ad management systems generate ad creatives without considering user emotions, making it difficult to resonate with the target audience. Furthermore, the ad creative generation process is complex and time-consuming, and there is insufficient measurement of ad effectiveness after delivery. This makes it difficult for advertisers to optimize their ad campaigns, potentially resulting in wasted budgets.

[1084] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generation means for generating advertising creatives based on the advertising requirements, an emotion recognition means for recognizing user emotions in real time, a means for using emotion data to generate and adjust advertising creatives, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to an ad network, and a means for collecting advertising performance results and generating reports. This enables the generation of advertising creatives that take user emotions into consideration, thereby increasing empathy with the target audience. It also streamlines the process from ad generation to delivery and effectiveness measurement, making it easier to optimize advertising campaigns.

[1085] "Advertising requirements" refers to a collection of information required to run an advertising campaign, including details such as the ad title, description, images, target audience, budget, and distribution period.

[1086] "Generative method" refers to the process of using machine learning models or generative AI to automatically generate advertising creative based on input advertising requirements.

[1087] An "emotion recognition means" is a combination of a device and software for analyzing a user's facial expressions and voice in real time and acquiring emotional data.

[1088] "Emotion data" is information about the user's emotional state obtained by the emotion recognition means, and is used to generate and adjust advertising creatives.

[1089] "Inspection method" refers to the process used to filter generated ad creatives to ensure they do not contain inappropriate content.

[1090] "Delivery method" refers to the process by which the inspected ad creative is sent to the ad network, which then displays the ad to the target audience.

[1091] "Advertising performance" refers to performance indicators after an advertisement is delivered, and specifically includes the number of impressions, click-through rate, engagement rate, number of conversions, etc.

[1092] "Collection means" refers to the process for collecting performance data after advertisement delivery, which is used to measure the effectiveness of the advertisement.

[1093] "Report generation means" refers to a process for analyzing collected advertising performance results and automatically generating reports.

[1094] "Camera and microphone" are input devices that capture the user's facial expressions and voice to provide data for emotion recognition.

[1095] An "emotion recognition engine" is software that analyzes data acquired by a camera and microphone and estimates the user's emotional state.

[1096] A "machine learning model" is a collection of algorithms that learn patterns from input data and automatically generate advertising creatives.

[1097] "Filtering measures" are processes used to inspect the advertising creative generated by the machine learning model to ensure it does not contain inappropriate content.

[1098] This invention provides a system that automates a series of processes from inputting advertising requirements to generating advertising creatives, recognizing emotions, delivering advertisements, and measuring their effectiveness. Specific embodiments of this system are described below.

[1099] System Program

[1100] Hardware and Software:

[1101] The system utilizes advertisers' smartphones, servers, and emotion recognition engines (e.g., Affectiva SDK), and uses generative AI models (e.g., OpenAI GPT-3) to generate ad creatives. The main components and their functions are listed below.

[1102] Enter your advertising requirements:

[1103] On the device, the user uses a dedicated management screen to input advertising requirements such as ad title, description, image, target audience, budget, distribution period, etc. This information is structured and sent to the server.

[1104] Emotion recognition:

[1105] The device is equipped with a camera and microphone, which capture the user's facial expressions and voice in real time. An emotion recognition engine analyzes this data to obtain the user's emotional data.

[1106] Ad creative generation:

[1107] The server requests the generative AI model to generate ad creatives based on the received ad requirements and emotional data. The generative AI model automatically generates ad creatives that take the emotional data into account.

[1108] Ad creative inspection:

[1109] The generated ad creative is inspected by the server using filtering measures to ensure it does not contain inappropriate content.

[1110] Ad serving:

[1111] Ad creatives that pass inspection are distributed through ad networks.

[1112] Ad performance collection and reporting:

[1113] After the ad is delivered, the server collects performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions. The collected data is analyzed to generate a report on the effectiveness of the ad. This report also includes sentiment data, which can be used to plan future advertising strategies.

[1114] Specific examples of processing

[1115] For example, consider an advertiser creating an ad titled "New Product Announcement" to introduce the latest gadget packed with technological innovation. The user inputs the following ad requirements:

[1116] Title: New Product Announcement

[1117] Description: Introducing the latest gadgets packed with technological innovation.

[1118] Image: new_gadget.png

[1119] Target Audience: Technology Enthusiasts

[1120] Budget: 100,000 yen

[1121] Distribution period: 7 days

[1122] After sending this information to the server, an emotion recognition engine analyzes the user's facial expressions and voice to obtain emotional data such as "75% delight," "20% surprise," and "15% neutral." Based on this emotional data and the advertising requirements, a generative AI model generates advertising creative, creating an ad with a "New Product Launch" banner and the tagline "Amazing Innovation, Buy Now!"

[1123] In this way, this system makes it possible to generate advertising creatives that take user emotions into account, thereby increasing empathy with the target audience. It also streamlines the process from ad creation to distribution and effectiveness measurement.

[1124] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1125] Step 1:

[1126] The user opens a dedicated management screen and inputs the ad requirements, specifically, information such as the ad title, description, image file path, target audience, budget, and distribution period into a form. This input data is structured and sent from the device to the server.

[1127] Step 2:

[1128] The device uses a camera and microphone to capture the user's facial expressions and voice data in real time. This data is sent to an emotion recognition engine, which generates emotion data. For example, the emotion (happiness, surprise, etc.) that the user is feeling during the creation of an advertisement is analyzed and that data is acquired.

[1129] Step 3:

[1130] The server sends the input advertising requirements and the acquired emotional data to the generative AI model. The generative AI model generates advertising creatives based on this data. In doing so, it reflects content based on the emotional data and creates advertising materials optimized for the target audience. For example, for a title such as "New Product Launch," an advertisement is generated that includes the catchphrase "Amazing Technological Innovation, Check It Out Now!"

[1131] Step 4:

[1132] The server sends the generated ad creative to an inspection tool to filter it for inappropriate content. The filtering checks for violent or adult content, and if there are any problems, they are corrected. For example, automatic checks can be done using language filtering or image recognition.

[1133] Step 5:

[1134] Ad creatives that pass inspection are sent from the server to the device and displayed to the user. The user can review the displayed ad and request corrections if necessary. If the user wants to make corrections, their feedback is sent back to the server and the ad is regenerated by the generative AI model.

[1135] Step 6:

[1136] Once the user gives final approval, the server sets up ad distribution settings, including distribution start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the server distributes the ads to each ad network.

[1137] Step 7:

[1138] Once the ad distribution begins, the server collects the ad performance results (number of impressions, click-through rate, engagement rate, number of conversions, etc.) in real time. The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad during the distribution period and areas for improvement.

[1139] Step 8:

[1140] The collected emotional data is also included in the report and used to propose the next advertising strategy. The server analyzes past emotional data and suggests what kind of advertising creative will be more effective for the next campaign, with the aim of maximizing advertising effectiveness.

[1141] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1142] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1143] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1144] [Third embodiment]

[1145] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1146] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1147] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1148] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1149] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1150] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1151] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1152] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1153] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1154] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1155] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1156] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1157] The present invention is a system for efficiently carrying out a series of advertising management processes, from inputting advertising requirements to distribution and report generation. A specific embodiment of this system will be described.

[1158] 1. Enter your advertising requirements

[1159] User Action:

[1160] Users begin creating ads on a dedicated management screen. Clicking the "Create Ad" button displays an input form. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. After entering the required information in the form and clicking the submit button, this data is sent to the server via the device.

[1161] Terminal processing:

[1162] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[1163] 2. Generating ad creatives

[1164] Server side:

[1165] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[1166] Generative AI processing:

[1167] Generative AI uses machine learning models to automatically generate ad creatives based on input factors, including optimal design and wording to maximize ad effectiveness.

[1168] 3. Inspection of advertising materials

[1169] Server side:

[1170] The generated ad creatives are subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If non-compliant content is found, it is automatically corrected or instructed to be regenerated.

[1171] 4. Review and Approval of Advertising Materials

[1172] Terminal processing:

[1173] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[1174] User Action:

[1175] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[1176] 5. Preparing for ad delivery

[1177] Server side:

[1178] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[1179] 6. Delivery of advertisements

[1180] Server side:

[1181] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[1182] 7. Collecting and reporting on advertising performance results

[1183] Server side:

[1184] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[1185] 8. Check advertising reports and plan your next strategy

[1186] Terminal processing:

[1187] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[1188] User Action:

[1189] Users can use the reports to consider their next advertising strategy, and by using the system's built-in strategy proposal function, they can receive specific suggestions for improvement.

[1190] Specific examples

[1191] Consider the case where a small business advertiser wants to advertise an in-store sale.

[1192] 1. User starts creating an ad:

[1193] Users select "Create Ad" on the admin screen, enter the title "Winter Sale," the description "20% off all items," upload a photo of their store as the image, and enter their budget and target audience.

[1194] 2. Ad creative generation:

[1195] The server inputs this information into the AI ​​generator, which then generates the appropriate design and copy. For example, a catchy slogan such as "Click here for limited-time coupons" is automatically generated.

[1196] 3. Inspect the generated ad:

[1197] Inspect server-generated content to ensure it does not contain inappropriate content.

[1198] 4. Ad Review and Approval:

[1199] The generated advertisement is displayed to the user, who then reviews and approves the content.

[1200] 5. Preparation and implementation of advertising distribution:

[1201] The server sets the delivery schedule and settings, and delivers advertisements to domestic and international ad networks based on the settings.

[1202] 6. Performance collection and reporting:

[1203] It collects advertising performance data and generates effectiveness reports based on this data.

[1204] 7. Review the report and consider your next strategy:

[1205] The user reviews the report and plans their next advertising strategy based on the obtained data.

[1206] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] User begins creating ad

[1210] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[1211] Step 2:

[1212] The device displays the input form

[1213] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, duration, etc.

[1214] Step 3:

[1215] User enters advertising requirements

[1216] The user enters the advertising requirements into the displayed input form, and once all the required information has been entered, the user clicks the submit button.

[1217] Step 4:

[1218] The device sends the input data to the server

[1219] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[1220] Step 5:

[1221] The server passes the data to the generated AI.

[1222] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creatives. At this point, the generative AI generates optimal designs and copy.

[1223] Step 6:

[1224] Generative AI generates ad creatives

[1225] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[1226] Step 7:

[1227] Server inspects generated creative

[1228] The server filters the generated ad creative to ensure it does not contain violent, adult or inappropriate content.

[1229] Step 8:

[1230] The server sends the ad creative to the device

[1231] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[1232] Step 9:

[1233] User reviews ad creative

[1234] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[1235] Step 10:

[1236] Prepare to deliver ads

[1237] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[1238] Step 11:

[1239] Ads delivered to ad networks

[1240] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[1241] Step 12:

[1242] Collect ad performance data

[1243] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[1244] Step 13:

[1245] The server generates the report

[1246] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[1247] Step 14:

[1248] The server sends the report to the device.

[1249] The generated report is sent from the server to the terminal and displayed to the user.

[1250] Step 15:

[1251] User checks the report

[1252] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[1253] Step 16:

[1254] Users consider their next advertising strategy

[1255] Users can plan their next advertising strategy based on the report results, and can receive specific suggestions for improvement by using the system's built-in strategy suggestion function.

[1256] Example 1

[1257] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1258] With conventional ad management systems, the process from entering advertising requirements to distribution and report generation was complex and time-consuming, making it difficult to operate efficiently. Furthermore, the creation and testing of ad creatives required a lot of manual work, making it difficult to maximize advertising effectiveness. This made it difficult to run simple and effective ad campaigns, especially for advertisers with limited resources, such as small and medium-sized businesses.

[1259] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1260] In this invention, the server includes means for accepting input of advertising requirements, means for structuring the advertising requirements and transmitting them to the server, and means for generating advertising creatives using a generative AI model based on the advertising requirements. This enables efficient automatic generation and inspection of advertising creatives, preparation for distribution, distribution, collection of results, and report generation as a single process.

[1261] "Advertising requirements" refers to the information required to create and distribute an advertisement, including details such as the title, description, image, target audience, budget, and distribution period.

[1262] A "generative AI model" is an algorithm or system that uses machine learning technology to automatically generate advertising creatives (e.g., text, images, layout, etc.).

[1263] "Server" refers to the part of the computer system that receives, processes, and stores data sent by users, generates advertising creatives using generative AI models, inspects the results of such generation, and ultimately delivers and generates reports.

[1264] "Advertising creative" refers to all materials used in advertising, such as text, images, and layout, and is content designed to maximize advertising effectiveness.

[1265] "User" refers to an advertiser who uses the system to create, manage, and distribute advertisements.

[1266] "Input Form" means a web form used by a User to enter advertising requirements, where specific fields may be entered to provide further information about the advertisement.

[1267] "Inspection" refers to the process of checking the content of the generated advertising creative to ensure that it does not contain inappropriate content (e.g., violent or adult content).

[1268] An "ad network" is a network that delivers advertisements to multiple websites, and examples include Google Ads and Facebook Ads.

[1269] "Report" means a document containing detailed analytical information about the performance of an Ad, including data such as impressions, click-through rates, engagement rates, and conversions.

[1270] "Next advertising strategy" refers to the specific policies and methods for planning and executing the next advertising activity based on the results of past advertising campaigns.

[1271] The present invention is a system that automates and streamlines a series of advertising management processes, from inputting advertising requirements to generating, inspecting, and distributing advertising creatives, collecting results, and generating reports. A specific embodiment of this system will be described.

[1272] First, the user accesses the management screen using a dedicated web browser. When the "Create Ad" button on this management screen is clicked, an input form for entering the ad requirements is displayed. This input form contains fields for entering information such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the "Submit" button.

[1273] The input data is structured on the device via a JavaScript API and converted to JSON format. This data is then sent to the server using HTTPS. Once the data transfer is complete, the server receives the data and passes it to a generative AI model. This generative AI model uses OpenAI's GPT series, which uses machine learning technology, for example.

[1274] The server generates a prompt based on the advertising requirements and sends it to the AI ​​model. An example of a prompt might be, "Generate advertising creative based on the following information: Title: Winter Sale, Description: 20% off all items, Image: Store photo, Target audience: Housewives, Budget: 10,000 yen, Distribution period: 1 week."

[1275] The generative AI model receives a prompt and automatically generates ad creatives based on it. The generated creatives are sent back to the server, where content inspection is performed. This inspection method uses NLP and image analysis technologies to check whether the generated creatives contain violent or adult content. If inappropriate content is detected, it is automatically filtered or corrected.

[1276] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user checks the generated ad to ensure there are no omissions or errors. If there are no problems, the user clicks the "Approve" button for final confirmation.

[1277] After receiving the user's final approval, the server sets the schedule and distribution settings for ad distribution. Specifically, the distribution start date, end date, target audience characteristics, budget allocation, etc. are set. Once the settings are complete, the ads are distributed in a format optimized for each ad network. Examples of ad networks include Google Ads and Facebook Ads.

[1278] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. The server analyzes this data and automatically generates a report, which is sent to the device and displayed to the user.

[1279] Finally, users review the report and consider their next advertising strategy. The system's built-in strategy suggestion function allows users to make specific suggestions for improvement or formulate new strategies.

[1280] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[1281] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1282] Step 1:

[1283] User processing

[1284] Users access the management screen using a dedicated web browser. When they click the "Create Ad" button, an input form for entering their ad requirements appears. The input form includes fields for the ad title, description, image, target audience, budget, distribution period, etc. The user enters information in these fields and clicks the "Submit" button.

[1285] Input: Ad title, description, image, target audience, budget, delivery period and other details.

[1286] Output: Structured ad requirements data.

[1287] Step 2:

[1288] Terminal side processing

[1289] The device structures the advertising requirements data entered by the user via a JavaScript API and converts it into JSON format, which is then sent to the server via HTTPS. The device also checks whether the data has been transferred correctly.

[1290] Input: Structured ad requirements data.

[1291] Output: Ad requirements JSON data sent to the server.

[1292] Step 3:

[1293] Server-side processing

[1294] The server passes the received ad requirements JSON data to a generative AI model. The generative AI model can be, for example, OpenAI's GPT series, which uses machine learning technology. The server generates a prompt based on the ad requirements and sends it to the generative AI model.

[1295] Input: Ad requirements JSON data.

[1296] Output: The prompt sentence that is passed to the generative AI model.

[1297] Step 4:

[1298] Processing by generative AI models

[1299] The generative AI model receives the prompt text and automatically generates ad creatives based on it. The generated creatives are sent back to the server via API. The generated ad creatives include text, image placement, layout, etc.

[1300] Input: Prompt statement.

[1301] Output: The generated ad creative.

[1302] Step 5:

[1303] Server-side processing

[1304] The server inputs the received ad creative into the content inspection module. This module uses NLP and image analysis technologies to check whether the generated creative contains violent or adult content. If inappropriate content is detected, it automatically corrects it or sends a regeneration instruction to the generation AI model.

[1305] Input: The generated ad creative.

[1306] Output: Inspected ad creative.

[1307] Step 6:

[1308] Terminal side processing

[1309] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user reviews the ad and checks for any omissions or errors. If there are no problems, they click the "Approve" button. If necessary, they can enter correction requests and resubmit.

[1310] Input: Inspected ad creative.

[1311] Output: User approval or correction request.

[1312] Step 7:

[1313] Server-side processing

[1314] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery. Specifically, it sets the delivery start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the ad is delivered in an optimized format for each ad network.

[1315] Input: User approval.

[1316] Output: Ad delivery schedule and configuration information.

[1317] Step 8:

[1318] Server-side processing

[1319] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. This data is analyzed and automatically generated into a report, which is then sent to the device and displayed to the user.

[1320] Input: Ad performance data.

[1321] Output: The generated ad effectiveness report.

[1322] Step 9:

[1323] User processing

[1324] Users can review the reports and consider their next advertising strategy. By using the system's built-in strategy suggestion function, they can propose specific improvements or formulate new strategies.

[1325] Input: The generated ad effectiveness report.

[1326] Output: Next advertising strategy and improvement suggestions.

[1327] (Application example 1)

[1328] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1329] Conventional ad generation systems make it difficult for users to efficiently create and distribute ad creatives. Furthermore, the effectiveness of generated ads cannot be predicted in advance, leading to uncertainty about ad performance. Furthermore, the inability to check generated ads in real time and make immediate corrections can lead to a decline in user satisfaction.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1331] In this invention, the server includes means for accepting input of advertising requirements, means for generating advertising creatives based on the advertising requirements, means for inspecting the generated advertising creatives, means for distributing advertising creatives that pass inspection to an ad network, means for collecting advertising performance results and generating reports, means for providing real-time previews of the advertising creatives, and means for predicting the effectiveness of the generated advertising creatives. This allows users to efficiently manage the entire process from creating advertising creatives to distributing them, and enables them to predict the effectiveness of advertising in advance. Furthermore, the real-time preview function allows users to instantly check and modify advertising content, thereby improving user satisfaction.

[1332] The "means for inputting advertisement requirements" is a means for providing an interface for a user to input details such as the title, description, image, target audience, budget, and distribution period of an advertisement.

[1333] "Generation means" refers to a device or program that automatically generates advertising creatives (images, text, layout, etc.) using generation AI based on advertising requirements entered by the user.

[1334] The "inspection means" is a device or program that checks whether the generated advertising creative contains inappropriate content and performs filtering.

[1335] A "distribution means" is a device or program that transmits advertising creatives that have passed inspection to an ad network and distributes advertisements based on a set schedule.

[1336] A "report generation means" is a device or program that collects the performance results of delivered advertisements (number of impressions, click rate, engagement rate, number of conversions, etc.), analyzes them, and automatically generates a report showing the effectiveness of the advertisements.

[1337] The "real-time preview means" is a means for providing an interface that allows a user to check the results of creation in real time during the process of creating an advertising creative and make any necessary corrections immediately.

[1338] The "effectiveness prediction means" is a device or program that uses past advertising data and a machine learning model to predict the advertising effectiveness of the generated advertising creative in advance and present it to the user.

[1339] A "machine learning model" is an algorithm or model that learns from past data and is used to generate advertising creatives and predict their effectiveness.

[1340] This invention relates to an advertising management system that performs an integrated process from inputting advertising requirements to generating, inspecting, distributing, measuring effectiveness, and generating reports. The mechanism for implementing this system is described below.

[1341] Enter your advertising requirements

[1342] Users begin creating ads using the dedicated smartphone application "SmartAd Creator." When users click the "Create Ad" button on the application's management screen, an input form for ad requirements is displayed. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. The input data is sent to the server by the smartphone application.

[1343] Ad creative generation

[1344] The server receives the ad requirements sent by the user and passes them to a generative AI engine (e.g., GPT-3 or Stable Diffusion). The generative AI engine automatically generates ad creatives (images, text, layout, etc.) based on these requirements. The generated ad creatives are sent back to the server.

[1345] Real-time preview and effectiveness prediction of advertising materials

[1346] The server provides a function to preview the generated ad creative in real time. Users can check this preview through a smartphone application. The server also uses past advertising data and machine learning models to predict the effectiveness of the generated ad creative in advance and presents the results to users.

[1347] Ad creative inspection

[1348] The generated ad creatives are then subject to content inspection by server-based inspection means, which filters the ads for inappropriate content (e.g., violent, adult, or discriminatory language).

[1349] Ad serving

[1350] After the user approves the ad creative, the server sets a distribution schedule and distributes the ad to the ad network. The distribution is carried out based on the set schedule, and the server also manages the target audience characteristics and budget allocation.

[1351] Measurement and reporting

[1352] The server automatically collects and analyzes the performance of the advertisements (number of impressions, click-through rate, engagement rate, number of conversions, etc.) and generates an effectiveness report, which is displayed to the user via a smartphone application.

[1353] Hardware and software used

[1354] Smartphone: "SmartAd Creator" application

[1355] Server: Receives advertising requirements, connects with AI engine, generates advertising creatives, provides real-time previews, predicts effectiveness, inspects content, delivers ads, measures effectiveness, generates reports

[1356] Generative AI engine: GPT-3, Stable Diffusion

[1357] Machine learning model: Advertising effectiveness prediction

[1358] Specific examples

[1359] For example, consider a small business advertiser announcing a "Winter Sale." The user uses the "SmartAd Creator" application and enters the following prompt text:

[1360] Prompt statement:

[1361] I would like to create an ad to announce this month's members-only sale. The sale runs until the end of the month, with a total budget of 500,000 yen, and the main target audience is women in their 20s and 30s. The ad title should be "Members-only sale," and the description should be "All products are eligible. Don't miss out on this special discount!" I would like to use a photo from inside the store.

[1362] Based on this prompt, the generative AI engine generates ad creatives, and the server provides real-time previews and effectiveness predictions. After the user confirms, modifies, and approves the ad, it is automatically distributed to the ad network. After the ad is distributed, the server measures its effectiveness and generates a report that is provided to the user to support their next advertising strategy.

[1363] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1364] Step 1:

[1365] The user starts the "SmartAd Creator" application on their smartphone and starts creating an ad. When the user clicks the "Create Ad" button on the management screen, an input form for the ad requirements is displayed. The form has fields for entering details such as the ad title, description, image, target audience, budget, and distribution period. When the user enters data into these fields and clicks the "Submit" button, the input data is sent from the device to the server.

[1366] Input: Ad title, description, image, target audience, budget, delivery period

[1367] Output: Ad requirements data sent to the server

[1368] Specific actions: The user uses the smartphone's touchscreen to enter information into each field and tap the send button.

[1369] Step 2:

[1370] The server receives the ad requirement data sent from the device. The server then passes this data to a generative AI engine (e.g., GPT-3, Stable Diffusion) and requests it to generate ad creatives. The generative AI engine generates optimal ad creatives (images, text, layout, etc.) based on the input information and returns the results to the server.

[1371] Input: Advertising requirements data

[1372] Output: Generated ad creative (images, text, layout)

[1373] Specific operation: The server calls the API of the generation AI engine and passes the advertising requirements as input data. The server receives the generated creative data.

[1374] Step 3:

[1375] The server sends the generated ad creative to the device as a real-time preview. The user can view this real-time preview through a smartphone application. The server also predicts the effectiveness of the generated ad based on past ad data and provides the results to the user. This effectiveness prediction includes, for example, estimates of click-through rate and conversion rate.

[1376] Input: Generated ad creative

[1377] Output: Real-time preview and effect prediction data

[1378] Specific operation: The server delivers the generated advertising creative and the results of the effectiveness prediction to the device, which the user can check on their smartphone.

[1379] Step 4:

[1380] The user checks the real-time preview and requests corrections as necessary. If corrections are necessary, the user sends a specific change request to the server via their device. The server then asks the AI ​​engine to regenerate the ad and generate a new creative. If no corrections are required, the user "approves" the generated ad creative.

[1381] Input: User's correction request (or approval)

[1382] Output: Revised ad creative (or approved ad creative)

[1383] Specific operation: The user operates the smartphone interface and taps the correction request or approval button. The server receives the input and performs the necessary processing.

[1384] Step 5:

[1385] After receiving final approval from the user, the server schedules and configures the ad delivery, including the ad delivery start date, end date, target audience characteristics, budget allocation, etc. Based on this, the server delivers the ad to the ad network.

[1386] Input: Final approved ad creative and delivery schedule

[1387] Output: Ad delivery to ad network

[1388] Specific operation: The server calls the ad network's API and sends the ad creative and delivery schedule data.

[1389] Step 6:

[1390] The server automatically collects the performance of the delivered ads (number of impressions, click-through rate, engagement rate, number of conversions, etc.), analyzes the collected data, and generates a report showing the effectiveness of the ads. This report is sent to the user via their device.

[1391] Input: Ad delivery result data

[1392] Output: Effectiveness report

[1393] Specific operation: The server collects delivery result data from each ad network, generates a report using a data analysis tool, and delivers it to the user's device.

[1394] Step 7:

[1395] Users can check the effectiveness report displayed on their device, which details the ad's performance and areas for improvement. Based on this, users can consider their next advertising strategy.

[1396] Input: Effectiveness report

[1397] Output: Feedback on your next advertising strategy

[1398] Specific operation: The user views the report on the smartphone screen and obtains information to plan their next advertising strategy.

[1399] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1400] The present invention combines a system that efficiently performs a series of advertisement management processes, from inputting advertisement requirements to distribution and report generation, with an emotion engine that recognizes user emotions. A specific embodiment of this system will be described.

[1401] Enter your advertising requirements

[1402] User Action:

[1403] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form allows the user to enter details such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the submit button.

[1404] Terminal processing:

[1405] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[1406] Ad creative generation

[1407] Server side:

[1408] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[1409] Generative AI processing:

[1410] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including content optimized for the target audience.

[1411] Emotion recognition by emotion engine

[1412] Terminal processing:

[1413] While the user is operating the input form, the device uses an emotion engine to recognize the user's emotions in real time. This emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[1414] Server side:

[1415] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[1416] Advertising material inspection

[1417] Server side:

[1418] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[1419] Creative review and approval

[1420] Terminal processing:

[1421] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[1422] User Action:

[1423] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[1424] Preparing for ad delivery

[1425] Server side:

[1426] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[1427] Ad serving

[1428] Server side:

[1429] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[1430] Ad performance collection and reporting

[1431] Server side:

[1432] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[1433] Utilizing Emotional Data

[1434] Server side:

[1435] The collected emotional data is included in ad performance reports, which deepens the emotional understanding of advertising campaigns. Furthermore, the emotional data is used to propose next advertising strategies. For example, past emotional data can be analyzed to suggest what type of creative will be more effective for the next campaign.

[1436] Checking advertising reports and next strategies

[1437] Terminal processing:

[1438] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[1439] User Action:

[1440] Users can use the reports to consider their next advertising strategy. Using the system's built-in strategy suggestion function, they can receive specific suggestions for improvement. For example, they can analyze past emotional data and advertising performance to determine which creatives were effective and incorporate that information into their next strategy.

[1441] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[1442] The processing flow will be explained below.

[1443] Step 1:

[1444] User begins creating ad

[1445] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[1446] Step 2:

[1447] The device displays the input form

[1448] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, and delivery period.

[1449] Step 3:

[1450] User enters advertising requirements

[1451] The user enters the advertising requirements in the displayed input form, and once all the required information has been entered, the user clicks the submit button to confirm the input data.

[1452] Step 4:

[1453] The device sends the input data to the server

[1454] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[1455] Step 5:

[1456] The server passes the data to the generated AI.

[1457] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creative. The generative AI generates optimal designs and copy based on the input information.

[1458] Step 6:

[1459] Generative AI generates ad creatives

[1460] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[1461] Step 7:

[1462] The device activates the emotion engine

[1463] While the user is operating the input form, the device activates an emotion engine and acquires emotion data in real time from the user's facial expressions, voice, etc.

[1464] Step 8:

[1465] Emotion engine analyzes emotional data

[1466] The emotion engine analyzes the acquired data and recognizes the user's emotional state, which is then transmitted to the server.

[1467] Step 9:

[1468] Server inspects generated creative

[1469] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[1470] Step 10:

[1471] The server sends the ad creative to the device

[1472] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[1473] Step 11:

[1474] User reviews ad creative

[1475] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[1476] Step 12:

[1477] Prepare to deliver ads

[1478] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[1479] Step 13:

[1480] Ads delivered to ad networks

[1481] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[1482] Step 14:

[1483] Collect ad performance data

[1484] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[1485] Step 15:

[1486] The server generates the report

[1487] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[1488] Step 16:

[1489] The server sends the report to the device.

[1490] The generated report is sent from the server to the terminal and displayed to the user.

[1491] Step 17:

[1492] User checks the report

[1493] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[1494] Step 18:

[1495] Users consider their next advertising strategy

[1496] Users can use the reports to plan their next advertising strategy. The system's built-in strategy suggestion function allows users to receive specific suggestions for improvement. For example, users can analyze past emotional data and ad performance to determine which creatives were effective and incorporate these into their next strategy.

[1497] Example 2

[1498] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1499] Current advertising management systems have a complicated process from entering advertising requirements to delivering ads and measuring their effectiveness, making it difficult to manage efficiently. Another issue is that they are unable to generate advertising creatives that take user emotions into account in order to improve advertising effectiveness. Furthermore, there is no established method for utilizing emotional data in measuring advertising effectiveness.

[1500] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generating means for generating advertising creatives based on the advertising requirements, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to a distribution network, a means for collecting advertising performance results and generating reports, and a means for recognizing emotion data in real time and utilizing it in generating and adjusting advertising creatives. This makes it possible to streamline the advertising management process and generate advertising creatives that take user emotions into consideration. Furthermore, utilizing emotion data can be expected to propose more effective advertising strategies and improve advertising effectiveness.

[1501] "Advertising requirements" refers to all information required to create and distribute an advertisement, including, but not limited to, the title, description, images, target audience, budget, and distribution period.

[1502] "Generation means" refers to technologies and algorithms for automatically generating advertising creatives based on input advertising requirements, and includes artificial intelligence technologies such as machine learning models.

[1503] "Inspection methods" refers to technologies and algorithms used to filter the content of generated advertising creatives and remove inappropriate elements.

[1504] "Delivery Network" means the online and offline outlets and platforms through which advertising is delivered to a target audience, including, specifically, major online advertising networks and partnerships.

[1505] "Advertising performance results" refers to data on the effect that delivered advertisements had on users, including the number of impressions, click-through rate, engagement rate, and number of conversions.

[1506] "Report generation" refers to the process of evaluating and analyzing advertising campaigns based on collected advertising performance results and compiling the results into a document.

[1507] "Emotion data" refers to an emotional state recognized based on data such as a user's facial expression, voice, and operation log.

[1508] "Advertising creative" refers to advertising materials generated based on advertising requirements, and specifically includes images, text, layout, etc.

[1509] "Generative AI engine" refers to a platform or algorithm that uses artificial intelligence technology to automatically generate advertising creatives based on input data.

[1510] The present invention is a system for efficiently performing a series of advertising management processes, from inputting advertising requirements to distribution and report generation, and is combined with an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[1511] Enter your advertising requirements

[1512] User Action:

[1513] Users start the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form contains fields for entering details such as the ad title, description, image, target audience, budget, and delivery period. For example, users enter the following information:

[1514] Title: "Experience the next generation smartphone now"

[1515] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[1516] Image: New product photos

[1517] Target audience: Technology-interested men and women aged 25-45

[1518] Budget: 500,000 yen

[1519] Distribution period: November 1st to December 31st, 2023

[1520] Terminal processing:

[1521] The terminal provides an interface for sending information entered by the user to the server, converting the input data into a structured format such as JSON and sending it to the server.

[1522] Ad creative generation

[1523] Server side:

[1524] The server passes the advertising requirements received from the device to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are then sent back to the server.

[1525] Examples of prompts include:

[1526] Please use the information below to generate advertising creative for next-generation smartphones.

[1527] Title: Experience the next generation smartphone now

[1528] Description: A next-generation smartphone with innovative features and design. Learn more here.

[1529] Image: [URL of new product photo]

[1530] Target audience: Technology-interested men and women aged 25-45

[1531] Emotion recognition by emotion engine

[1532] Terminal processing:

[1533] The device uses an emotion engine to recognize the user's emotions in real time while the user is operating the input form. Emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[1534] Server side:

[1535] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[1536] Inspection and distribution of advertising materials

[1537] Server side:

[1538] The generated ad creatives are inspected by the server's inspection means to check whether the ad contains violent or inappropriate content, and if any inappropriate content is found, it is automatically corrected or instructed to be regenerated. Ad creatives that pass inspection are delivered in a format optimized for each delivery network.

[1539] Ad performance collection and reporting

[1540] Server side:

[1541] After an ad is delivered, ad performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions are collected. The collected data is analyzed and a detailed report is automatically generated. This report details the effectiveness of the ad and areas for improvement.

[1542] Utilizing emotion data and next-generation strategies

[1543] Server side:

[1544] The collected emotional data is also included in ad performance reports. A detailed understanding of emotional responses can be used to suggest future advertising strategies. For example, analyzing past emotional data can suggest which creative elements were most effective in the next campaign.

[1545] Terminal side processing and user side processing:

[1546] The generated report is sent to the terminal and displayed to the user. The user can use the report to consider their next advertising strategy and receive specific suggestions for improvement using the system's strategy suggestion function.

[1547] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[1548] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1549] Step 1:

[1550] User Action:

[1551] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. Specifically, the user enters the following information into the form:

[1552] title

[1553] Description

[1554] image

[1555] Target Audience

[1556] budget

[1557] Distribution period

[1558] Input: Ad details (title, description, image, target audience, budget, delivery period)

[1559] Output: Data entered in the input form

[1560] Step 2:

[1561] Terminal processing:

[1562] The terminal converts the contents of the input form into a structured data format (for example, JSON format) and sends it to the server. Specifically, the data is structured as follows:

[1563] Ad title: "Experience the next generation smartphone now"

[1564] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[1565] Image URL: "example.com / image.png"

[1566] Target audience: "Men and women aged 25-45 who are interested in technology"

[1567] Budget: 500,000 yen

[1568] Distribution period: November 1st to December 31st, 2023

[1569] Input: Data entered into an input form

[1570] Output: Structured data to send to the server

[1571] Step 3:

[1572] Server side:

[1573] The server stores the received advertising requirements in a database and requests the AI ​​engine to generate advertising creatives. Specifically, the server sends the following prompt to the AI ​​engine:

[1574] Please use the information below to generate advertising creative for next-generation smartphones.

[1575] Title: Experience the next generation smartphone now

[1576] Description: A next-generation smartphone with innovative features and design. Learn more here.

[1577] Image: example.com / image.png

[1578] Target audience: Technology-interested men and women aged 25-45

[1579] Input: Structured ad requirements data

[1580] Output: Prompt sent to the generative AI engine

[1581] Step 4:

[1582] Processing by the generative AI engine:

[1583] The generative AI engine automatically generates ad creatives based on prompt text. Specifically, it generates the following data:

[1584] Advertising banner image

[1585] Ad text

[1586] Layout Information

[1587] Input: Prompt received from the server

[1588] Output: Generated ad creative data (images, text, layout)

[1589] Step 5:

[1590] Server side:

[1591] The ad creative returned by the generation AI engine is received and passed to the inspection means. Specifically, the ad creative content is checked to see if there is any inappropriate content.

[1592] Input: Generated ad creative data

[1593] Output: Ad creative data that passes inspection

[1594] Step 6:

[1595] Server side:

[1596] After the ad creative passes inspection, it is provided to the distribution network in an optimized format, for example, by adapting the creative to the format of each distribution network.

[1597] Input: Ad creative data that has passed inspection

[1598] Output: Ad creative data optimized for each distribution network

[1599] Step 7:

[1600] Terminal processing:

[1601] The generated ad creative is sent to the terminal and displayed for user confirmation, specifically displaying a screen that allows the user to preview the ad creative.

[1602] Input: Ad creative data optimized for each distribution network

[1603] Output: Ad creative displayed on device

[1604] Step 8:

[1605] User Action:

[1606] The user can review the ad and click the "Approve" button for final confirmation. If necessary, they can request corrections.

[1607] Input: Previewed ad creative

[1608] Output: Approval or correction request

[1609] Step 9:

[1610] Server side:

[1611] Once final approval is received, the schedule and delivery settings for ad delivery are set, including the delivery start date, end date, target audience characteristics, and budget allocation.

[1612] Input: User authorization data

[1613] Output: Ad delivery schedule and delivery setting data

[1614] Step 10:

[1615] Server side:

[1616] The advertisements are distributed to each distribution network according to a set schedule. Specifically, the advertisement material is transmitted to the distribution network.

[1617] Input: Distribution setting data

[1618] Output: Ad creative sent to the delivery network

[1619] Step 11:

[1620] Server side:

[1621] It collects ad performance results and generates reports. Specifically, it collects and analyzes the following data:

[1622] Impressions

[1623] Click-through rate

[1624] Engagement Rate

[1625] Conversions

[1626] Input: Performance data of delivered ads

[1627] Output: Ad performance report

[1628] Step 12:

[1629] Server side:

[1630] The system analyzes emotional data included in advertising campaign reports and uses it to propose next-generation strategies. Specifically, it compares past emotional data with advertising performance and proposes optimal creatives.

[1631] Input: Ad performance reports and sentiment data

[1632] Output: Proposal data for next advertising strategy

[1633] Step 13:

[1634] Terminal processing:

[1635] The generated report is sent to the terminal and displayed to the user.

[1636] Input: Ad Performance Report

[1637] Output: Report displayed on terminal

[1638] These processing steps allow advertisers to efficiently generate, distribute, measure the effectiveness of their ads, and develop next-generation strategies. Furthermore, by utilizing emotion data, they can create ad creatives that are more relevant to their target audience.

[1639] (Application example 2)

[1640] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1641] Traditional ad management systems generate ad creatives without considering user emotions, making it difficult to resonate with the target audience. Furthermore, the ad creative generation process is complex and time-consuming, and there is insufficient measurement of ad effectiveness after delivery. This makes it difficult for advertisers to optimize their ad campaigns, potentially resulting in wasted budgets.

[1642] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generation means for generating advertising creatives based on the advertising requirements, an emotion recognition means for recognizing user emotions in real time, a means for using emotion data to generate and adjust advertising creatives, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to an ad network, and a means for collecting advertising performance results and generating reports. This enables the generation of advertising creatives that take user emotions into consideration, thereby increasing empathy with the target audience. It also streamlines the process from ad generation to delivery and effectiveness measurement, making it easier to optimize advertising campaigns.

[1643] "Advertising requirements" refers to a collection of information required to run an advertising campaign, including details such as the ad title, description, images, target audience, budget, and distribution period.

[1644] "Generative method" refers to the process of using machine learning models or generative AI to automatically generate advertising creative based on input advertising requirements.

[1645] An "emotion recognition means" is a combination of a device and software for analyzing a user's facial expressions and voice in real time and acquiring emotional data.

[1646] "Emotion data" is information about the user's emotional state obtained by the emotion recognition means, and is used to generate and adjust advertising creatives.

[1647] "Inspection method" refers to the process used to filter generated ad creatives to ensure they do not contain inappropriate content.

[1648] "Delivery method" refers to the process by which the inspected ad creative is sent to the ad network, which then displays the ad to the target audience.

[1649] "Advertising performance" refers to performance indicators after an advertisement is delivered, and specifically includes the number of impressions, click-through rate, engagement rate, number of conversions, etc.

[1650] "Collection means" refers to the process for collecting performance data after advertisement delivery, which is used to measure the effectiveness of the advertisement.

[1651] "Report generation means" refers to a process for analyzing collected advertising performance results and automatically generating reports.

[1652] "Camera and microphone" are input devices that capture the user's facial expressions and voice to provide data for emotion recognition.

[1653] An "emotion recognition engine" is software that analyzes data acquired by a camera and microphone and estimates the user's emotional state.

[1654] A "machine learning model" is a collection of algorithms that learn patterns from input data and automatically generate advertising creatives.

[1655] "Filtering measures" are processes used to inspect the advertising creative generated by the machine learning model to ensure it does not contain inappropriate content.

[1656] This invention provides a system that automates a series of processes from inputting advertising requirements to generating advertising creatives, recognizing emotions, delivering advertisements, and measuring their effectiveness. Specific embodiments of this system are described below.

[1657] System Program

[1658] Hardware and Software:

[1659] The system utilizes advertisers' smartphones, servers, and emotion recognition engines (e.g., Affectiva SDK), and uses generative AI models (e.g., OpenAI GPT-3) to generate ad creatives. The main components and their functions are listed below.

[1660] Enter your advertising requirements:

[1661] On the device, the user uses a dedicated management screen to input advertising requirements such as ad title, description, image, target audience, budget, distribution period, etc. This information is structured and sent to the server.

[1662] Emotion recognition:

[1663] The device is equipped with a camera and microphone, which capture the user's facial expressions and voice in real time. An emotion recognition engine analyzes this data to obtain the user's emotional data.

[1664] Ad creative generation:

[1665] The server requests the generative AI model to generate ad creatives based on the received ad requirements and emotional data. The generative AI model automatically generates ad creatives that take the emotional data into account.

[1666] Ad creative inspection:

[1667] The generated ad creative is inspected by the server using filtering measures to ensure it does not contain inappropriate content.

[1668] Ad serving:

[1669] Ad creatives that pass inspection are distributed through ad networks.

[1670] Ad performance collection and reporting:

[1671] After the ad is delivered, the server collects performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions. The collected data is analyzed to generate a report on the effectiveness of the ad. This report also includes sentiment data, which can be used to plan future advertising strategies.

[1672] Specific examples of processing

[1673] For example, consider an advertiser creating an ad titled "New Product Announcement" to introduce the latest gadget packed with technological innovation. The user inputs the following ad requirements:

[1674] Title: New Product Announcement

[1675] Description: Introducing the latest gadgets packed with technological innovation.

[1676] Image: new_gadget.png

[1677] Target Audience: Technology Enthusiasts

[1678] Budget: 100,000 yen

[1679] Distribution period: 7 days

[1680] After sending this information to the server, an emotion recognition engine analyzes the user's facial expressions and voice to obtain emotional data such as "75% delight," "20% surprise," and "15% neutral." Based on this emotional data and the advertising requirements, a generative AI model generates advertising creative, creating an ad with a "New Product Launch" banner and the tagline "Amazing Innovation, Buy Now!"

[1681] In this way, this system makes it possible to generate advertising creatives that take user emotions into account, thereby increasing empathy with the target audience. It also streamlines the process from ad creation to distribution and effectiveness measurement.

[1682] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1683] Step 1:

[1684] The user opens a dedicated management screen and inputs the ad requirements, specifically, information such as the ad title, description, image file path, target audience, budget, and distribution period into a form. This input data is structured and sent from the device to the server.

[1685] Step 2:

[1686] The device uses a camera and microphone to capture the user's facial expressions and voice data in real time. This data is sent to an emotion recognition engine, which generates emotion data. For example, the emotion (happiness, surprise, etc.) that the user is feeling during the creation of an advertisement is analyzed and that data is acquired.

[1687] Step 3:

[1688] The server sends the input advertising requirements and the acquired emotional data to the generative AI model. The generative AI model generates advertising creatives based on this data. In doing so, it reflects content based on the emotional data and creates advertising materials optimized for the target audience. For example, for a title such as "New Product Launch," an advertisement is generated that includes the catchphrase "Amazing Technological Innovation, Check It Out Now!"

[1689] Step 4:

[1690] The server sends the generated ad creative to an inspection tool to filter it for inappropriate content. The filtering checks for violent or adult content, and if there are any problems, they are corrected. For example, automatic checks can be done using language filtering or image recognition.

[1691] Step 5:

[1692] Ad creatives that pass inspection are sent from the server to the device and displayed to the user. The user can review the displayed ad and request corrections if necessary. If the user wants to make corrections, their feedback is sent back to the server and the ad is regenerated by the generative AI model.

[1693] Step 6:

[1694] Once the user gives final approval, the server sets up ad distribution settings, including distribution start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the server distributes the ads to each ad network.

[1695] Step 7:

[1696] Once the ad distribution begins, the server collects the ad performance results (number of impressions, click-through rate, engagement rate, number of conversions, etc.) in real time. The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad during the distribution period and areas for improvement.

[1697] Step 8:

[1698] The collected emotional data is also included in the report and used to propose the next advertising strategy. The server analyzes past emotional data and suggests what kind of advertising creative will be more effective for the next campaign, with the aim of maximizing advertising effectiveness.

[1699] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1700] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1701] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1702] [Fourth embodiment]

[1703] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1704] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1705] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1706] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1707] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1708] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1709] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1710] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1711] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1712] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1713] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1714] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1715] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1716] The present invention is a system for efficiently carrying out a series of advertising management processes, from inputting advertising requirements to distribution and report generation. A specific embodiment of this system will be described.

[1717] 1. Enter your advertising requirements

[1718] User Action:

[1719] Users begin creating ads on a dedicated management screen. Clicking the "Create Ad" button displays an input form. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. After entering the required information in the form and clicking the submit button, this data is sent to the server via the device.

[1720] Terminal processing:

[1721] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[1722] 2. Generating ad creatives

[1723] Server side:

[1724] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[1725] Generative AI processing:

[1726] Generative AI uses machine learning models to automatically generate ad creatives based on input factors, including optimal design and wording to maximize ad effectiveness.

[1727] 3. Inspection of advertising materials

[1728] Server side:

[1729] The generated ad creatives are subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If non-compliant content is found, it is automatically corrected or instructed to be regenerated.

[1730] 4. Review and Approval of Advertising Materials

[1731] Terminal processing:

[1732] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[1733] User Action:

[1734] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[1735] 5. Preparing for ad delivery

[1736] Server side:

[1737] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[1738] 6. Delivery of advertisements

[1739] Server side:

[1740] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[1741] 7. Collecting and reporting on advertising performance results

[1742] Server side:

[1743] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[1744] 8. Check advertising reports and plan your next strategy

[1745] Terminal processing:

[1746] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[1747] User Action:

[1748] Users can use the reports to consider their next advertising strategy, and by using the system's built-in strategy proposal function, they can receive specific suggestions for improvement.

[1749] Specific examples

[1750] Consider the case where a small business advertiser wants to advertise an in-store sale.

[1751] 1. User starts creating an ad:

[1752] Users select "Create Ad" on the admin screen, enter the title "Winter Sale," the description "20% off all items," upload a photo of their store as the image, and enter their budget and target audience.

[1753] 2. Ad creative generation:

[1754] The server inputs this information into the AI ​​generator, which then generates the appropriate design and copy. For example, a catchy slogan such as "Click here for limited-time coupons" is automatically generated.

[1755] 3. Inspect the generated ad:

[1756] Inspect server-generated content to ensure it does not contain inappropriate content.

[1757] 4. Ad Review and Approval:

[1758] The generated advertisement is displayed to the user, who then reviews and approves the content.

[1759] 5. Preparation and implementation of advertising distribution:

[1760] The server sets the delivery schedule and settings, and delivers advertisements to domestic and international ad networks based on the settings.

[1761] 6. Performance collection and reporting:

[1762] It collects advertising performance data and generates effectiveness reports based on this data.

[1763] 7. Review the report and consider your next strategy:

[1764] The user reviews the report and plans their next advertising strategy based on the obtained data.

[1765] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[1766] The processing flow will be explained below.

[1767] Step 1:

[1768] User begins creating ad

[1769] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[1770] Step 2:

[1771] The device displays the input form

[1772] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, duration, etc.

[1773] Step 3:

[1774] User enters advertising requirements

[1775] The user enters the advertising requirements into the displayed input form, and once all the required information has been entered, the user clicks the submit button.

[1776] Step 4:

[1777] The device sends the input data to the server

[1778] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[1779] Step 5:

[1780] The server passes the data to the generated AI.

[1781] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creatives. At this point, the generative AI generates optimal designs and copy.

[1782] Step 6:

[1783] Generative AI generates ad creatives

[1784] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[1785] Step 7:

[1786] Server inspects generated creative

[1787] The server filters the generated ad creative to ensure it does not contain violent, adult or inappropriate content.

[1788] Step 8:

[1789] The server sends the ad creative to the device

[1790] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[1791] Step 9:

[1792] User reviews ad creative

[1793] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[1794] Step 10:

[1795] Prepare to deliver ads

[1796] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[1797] Step 11:

[1798] Ads delivered to ad networks

[1799] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[1800] Step 12:

[1801] Collect ad performance data

[1802] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[1803] Step 13:

[1804] The server generates the report

[1805] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[1806] Step 14:

[1807] The server sends the report to the device.

[1808] The generated report is sent from the server to the terminal and displayed to the user.

[1809] Step 15:

[1810] User checks the report

[1811] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[1812] Step 16:

[1813] Users consider their next advertising strategy

[1814] Users can plan their next advertising strategy based on the report results, and can receive specific suggestions for improvement by using the system's built-in strategy suggestion function.

[1815] Example 1

[1816] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1817] With conventional ad management systems, the process from entering advertising requirements to distribution and report generation was complex and time-consuming, making it difficult to operate efficiently. Furthermore, the creation and testing of ad creatives required a lot of manual work, making it difficult to maximize advertising effectiveness. This made it difficult to run simple and effective ad campaigns, especially for advertisers with limited resources, such as small and medium-sized businesses.

[1818] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1819] In this invention, the server includes means for accepting input of advertising requirements, means for structuring the advertising requirements and transmitting them to the server, and means for generating advertising creatives using a generative AI model based on the advertising requirements. This enables efficient automatic generation and inspection of advertising creatives, preparation for distribution, distribution, collection of results, and report generation as a single process.

[1820] "Advertising requirements" refers to the information required to create and distribute an advertisement, including details such as the title, description, image, target audience, budget, and distribution period.

[1821] A "generative AI model" is an algorithm or system that uses machine learning technology to automatically generate advertising creatives (e.g., text, images, layout, etc.).

[1822] "Server" refers to the part of the computer system that receives, processes, and stores data sent by users, generates advertising creatives using generative AI models, inspects the results of such generation, and ultimately delivers and generates reports.

[1823] "Advertising creative" refers to all materials used in advertising, such as text, images, and layout, and is content designed to maximize advertising effectiveness.

[1824] "User" refers to an advertiser who uses the system to create, manage, and distribute advertisements.

[1825] "Input Form" means a web form used by a User to enter advertising requirements, where specific fields may be entered to provide further information about the advertisement.

[1826] "Inspection" refers to the process of checking the content of the generated advertising creative to ensure that it does not contain inappropriate content (e.g., violent or adult content).

[1827] An "ad network" is a network that delivers advertisements to multiple websites, and examples include Google Ads and Facebook Ads.

[1828] "Report" means a document containing detailed analytical information about the performance of an Ad, including data such as impressions, click-through rates, engagement rates, and conversions.

[1829] "Next advertising strategy" refers to the specific policies and methods for planning and executing the next advertising activity based on the results of past advertising campaigns.

[1830] The present invention is a system that automates and streamlines a series of advertising management processes, from inputting advertising requirements to generating, inspecting, and distributing advertising creatives, collecting results, and generating reports. A specific embodiment of this system will be described.

[1831] First, the user accesses the management screen using a dedicated web browser. When the "Create Ad" button on this management screen is clicked, an input form for entering the ad requirements is displayed. This input form contains fields for entering information such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the "Submit" button.

[1832] The input data is structured on the device via a JavaScript API and converted to JSON format. This data is then sent to the server using HTTPS. Once the data transfer is complete, the server receives the data and passes it to a generative AI model. This generative AI model uses OpenAI's GPT series, which uses machine learning technology, for example.

[1833] The server generates a prompt based on the advertising requirements and sends it to the AI ​​model. An example of a prompt might be, "Generate advertising creative based on the following information: Title: Winter Sale, Description: 20% off all items, Image: Store photo, Target audience: Housewives, Budget: 10,000 yen, Distribution period: 1 week."

[1834] The generative AI model receives a prompt and automatically generates ad creatives based on it. The generated creatives are sent back to the server, where content inspection is performed. This inspection method uses NLP and image analysis technologies to check whether the generated creatives contain violent or adult content. If inappropriate content is detected, it is automatically filtered or corrected.

[1835] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user checks the generated ad to ensure there are no omissions or errors. If there are no problems, the user clicks the "Approve" button for final confirmation.

[1836] After receiving the user's final approval, the server sets the schedule and distribution settings for ad distribution. Specifically, the distribution start date, end date, target audience characteristics, budget allocation, etc. are set. Once the settings are complete, the ads are distributed in a format optimized for each ad network. Examples of ad networks include Google Ads and Facebook Ads.

[1837] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. The server analyzes this data and automatically generates a report, which is sent to the device and displayed to the user.

[1838] Finally, users review the report and consider their next advertising strategy. The system's built-in strategy suggestion function allows users to make specific suggestions for improvement or formulate new strategies.

[1839] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them and measuring their effectiveness.

[1840] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1841] Step 1:

[1842] User processing

[1843] Users access the management screen using a dedicated web browser. When they click the "Create Ad" button, an input form for entering their ad requirements appears. The input form includes fields for the ad title, description, image, target audience, budget, distribution period, etc. The user enters information in these fields and clicks the "Submit" button.

[1844] Input: Ad title, description, image, target audience, budget, delivery period and other details.

[1845] Output: Structured ad requirements data.

[1846] Step 2:

[1847] Terminal side processing

[1848] The device structures the advertising requirements data entered by the user via a JavaScript API and converts it into JSON format, which is then sent to the server via HTTPS. The device also checks whether the data has been transferred correctly.

[1849] Input: Structured ad requirements data.

[1850] Output: Ad requirements JSON data sent to the server.

[1851] Step 3:

[1852] Server-side processing

[1853] The server passes the received ad requirements JSON data to a generative AI model. The generative AI model can be, for example, OpenAI's GPT series, which uses machine learning technology. The server generates a prompt based on the ad requirements and sends it to the generative AI model.

[1854] Input: Ad requirements JSON data.

[1855] Output: The prompt sentence that is passed to the generative AI model.

[1856] Step 4:

[1857] Processing by generative AI models

[1858] The generative AI model receives the prompt text and automatically generates ad creatives based on it. The generated creatives are sent back to the server via API. The generated ad creatives include text, image placement, layout, etc.

[1859] Input: Prompt statement.

[1860] Output: The generated ad creative.

[1861] Step 5:

[1862] Server-side processing

[1863] The server inputs the received ad creative into the content inspection module. This module uses NLP and image analysis technologies to check whether the generated creative contains violent or adult content. If inappropriate content is detected, it automatically corrects it or sends a regeneration instruction to the generation AI model.

[1864] Input: The generated ad creative.

[1865] Output: Inspected ad creative.

[1866] Step 6:

[1867] Terminal side processing

[1868] Ad creatives that pass inspection are sent to the device and displayed in the user's browser. The user reviews the ad and checks for any omissions or errors. If there are no problems, they click the "Approve" button. If necessary, they can enter correction requests and resubmit.

[1869] Input: Inspected ad creative.

[1870] Output: User approval or correction request.

[1871] Step 7:

[1872] Server-side processing

[1873] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery. Specifically, it sets the delivery start date, end date, target audience characteristics, budget allocation, etc. Once the settings are complete, the ad is delivered in an optimized format for each ad network.

[1874] Input: User approval.

[1875] Output: Ad delivery schedule and configuration information.

[1876] Step 8:

[1877] Server-side processing

[1878] After delivering the ads, the server collects performance data from each ad network, such as the number of impressions, click-through rate, engagement rate, and number of conversions. This data is analyzed and automatically generated into a report, which is then sent to the device and displayed to the user.

[1879] Input: Ad performance data.

[1880] Output: The generated ad effectiveness report.

[1881] Step 9:

[1882] User processing

[1883] Users can review the reports and consider their next advertising strategy. By using the system's built-in strategy suggestion function, they can propose specific improvements or formulate new strategies.

[1884] Input: The generated ad effectiveness report.

[1885] Output: Next advertising strategy and improvement suggestions.

[1886] (Application example 1)

[1887] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1888] Conventional ad generation systems make it difficult for users to efficiently create and distribute ad creatives. Furthermore, the effectiveness of generated ads cannot be predicted in advance, leading to uncertainty about ad performance. Furthermore, the inability to check generated ads in real time and make immediate corrections can lead to a decline in user satisfaction.

[1889] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1890] In this invention, the server includes means for accepting input of advertising requirements, means for generating advertising creatives based on the advertising requirements, means for inspecting the generated advertising creatives, means for distributing advertising creatives that pass inspection to an ad network, means for collecting advertising performance results and generating reports, means for providing real-time previews of the advertising creatives, and means for predicting the effectiveness of the generated advertising creatives. This allows users to efficiently manage the entire process from creating advertising creatives to distributing them, and enables them to predict the effectiveness of advertising in advance. Furthermore, the real-time preview function allows users to instantly check and modify advertising content, thereby improving user satisfaction.

[1891] The "means for inputting advertisement requirements" is a means for providing an interface for a user to input details such as the title, description, image, target audience, budget, and distribution period of an advertisement.

[1892] "Generation means" refers to a device or program that automatically generates advertising creatives (images, text, layout, etc.) using generation AI based on advertising requirements entered by the user.

[1893] The "inspection means" is a device or program that checks whether the generated advertising creative contains inappropriate content and performs filtering.

[1894] A "distribution means" is a device or program that transmits advertising creatives that have passed inspection to an ad network and distributes advertisements based on a set schedule.

[1895] A "report generation means" is a device or program that collects the performance results of delivered advertisements (number of impressions, click rate, engagement rate, number of conversions, etc.), analyzes them, and automatically generates a report showing the effectiveness of the advertisements.

[1896] The "real-time preview means" is a means for providing an interface that allows a user to check the results of creation in real time during the process of creating an advertising creative and make any necessary corrections immediately.

[1897] The "effectiveness prediction means" is a device or program that uses past advertising data and a machine learning model to predict the advertising effectiveness of the generated advertising creative in advance and present it to the user.

[1898] A "machine learning model" is an algorithm or model that learns from past data and is used to generate advertising creatives and predict their effectiveness.

[1899] This invention relates to an advertising management system that performs an integrated process from inputting advertising requirements to generating, inspecting, distributing, measuring effectiveness, and generating reports. The mechanism for implementing this system is described below.

[1900] Enter your advertising requirements

[1901] Users begin creating ads using the dedicated smartphone application "SmartAd Creator." When users click the "Create Ad" button on the application's management screen, an input form for ad requirements is displayed. In this form, users can enter details such as the ad title, description, image, target audience, budget, and distribution period. The input data is sent to the server by the smartphone application.

[1902] Ad creative generation

[1903] The server receives the ad requirements sent by the user and passes them to a generative AI engine (e.g., GPT-3 or Stable Diffusion). The generative AI engine automatically generates ad creatives (images, text, layout, etc.) based on these requirements. The generated ad creatives are sent back to the server.

[1904] Real-time preview and effectiveness prediction of advertising materials

[1905] The server provides a function to preview the generated ad creative in real time. Users can check this preview through a smartphone application. The server also uses past advertising data and machine learning models to predict the effectiveness of the generated ad creative in advance and presents the results to users.

[1906] Ad creative inspection

[1907] The generated ad creatives are then subject to content inspection by server-based inspection means, which filters the ads for inappropriate content (e.g., violent, adult, or discriminatory language).

[1908] Ad serving

[1909] After the user approves the ad creative, the server sets a distribution schedule and distributes the ad to the ad network. The distribution is carried out based on the set schedule, and the server also manages the target audience characteristics and budget allocation.

[1910] Measurement and reporting

[1911] The server automatically collects and analyzes the performance of the advertisements (number of impressions, click-through rate, engagement rate, number of conversions, etc.) and generates an effectiveness report, which is displayed to the user via a smartphone application.

[1912] Hardware and software used

[1913] Smartphone: "SmartAd Creator" application

[1914] Server: Receives advertising requirements, connects with AI engine, generates advertising creatives, provides real-time previews, predicts effectiveness, inspects content, delivers ads, measures effectiveness, generates reports

[1915] Generative AI engine: GPT-3, Stable Diffusion

[1916] Machine learning model: Advertising effectiveness prediction

[1917] Specific examples

[1918] For example, consider a small business advertiser announcing a "Winter Sale." The user uses the "SmartAd Creator" application and enters the following prompt text:

[1919] Prompt statement:

[1920] I would like to create an ad to announce this month's members-only sale. The sale runs until the end of the month, with a total budget of 500,000 yen, and the main target audience is women in their 20s and 30s. The ad title should be "Members-only sale," and the description should be "All products are eligible. Don't miss out on this special discount!" I would like to use a photo from inside the store.

[1921] Based on this prompt, the generative AI engine generates ad creatives, and the server provides real-time previews and effectiveness predictions. After the user confirms, modifies, and approves the ad, it is automatically distributed to the ad network. After the ad is distributed, the server measures its effectiveness and generates a report that is provided to the user to support their next advertising strategy.

[1922] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1923] Step 1:

[1924] The user starts the "SmartAd Creator" application on their smartphone and starts creating an ad. When the user clicks the "Create Ad" button on the management screen, an input form for the ad requirements is displayed. The form has fields for entering details such as the ad title, description, image, target audience, budget, and distribution period. When the user enters data into these fields and clicks the "Submit" button, the input data is sent from the device to the server.

[1925] Input: Ad title, description, image, target audience, budget, delivery period

[1926] Output: Ad requirements data sent to the server

[1927] Specific actions: The user uses the smartphone's touchscreen to enter information into each field and tap the send button.

[1928] Step 2:

[1929] The server receives the ad requirement data sent from the device. The server then passes this data to a generative AI engine (e.g., GPT-3, Stable Diffusion) and requests it to generate ad creatives. The generative AI engine generates optimal ad creatives (images, text, layout, etc.) based on the input information and returns the results to the server.

[1930] Input: Advertising requirements data

[1931] Output: Generated ad creative (images, text, layout)

[1932] Specific operation: The server calls the API of the generation AI engine and passes the advertising requirements as input data. The server receives the generated creative data.

[1933] Step 3:

[1934] The server sends the generated ad creative to the device as a real-time preview. The user can view this real-time preview through a smartphone application. The server also predicts the effectiveness of the generated ad based on past ad data and provides the results to the user. This effectiveness prediction includes, for example, estimates of click-through rate and conversion rate.

[1935] Input: Generated ad creative

[1936] Output: Real-time preview and effect prediction data

[1937] Specific operation: The server delivers the generated advertising creative and the results of the effectiveness prediction to the device, which the user can check on their smartphone.

[1938] Step 4:

[1939] The user checks the real-time preview and requests corrections as necessary. If corrections are necessary, the user sends a specific change request to the server via their device. The server then asks the AI ​​engine to regenerate the ad and generate a new creative. If no corrections are required, the user "approves" the generated ad creative.

[1940] Input: User's correction request (or approval)

[1941] Output: Revised ad creative (or approved ad creative)

[1942] Specific operation: The user operates the smartphone interface and taps the correction request or approval button. The server receives the input and performs the necessary processing.

[1943] Step 5:

[1944] After receiving final approval from the user, the server schedules and configures the ad delivery, including the ad delivery start date, end date, target audience characteristics, budget allocation, etc. Based on this, the server delivers the ad to the ad network.

[1945] Input: Final approved ad creative and delivery schedule

[1946] Output: Ad delivery to ad network

[1947] Specific operation: The server calls the ad network's API and sends the ad creative and delivery schedule data.

[1948] Step 6:

[1949] The server automatically collects the performance of the delivered ads (number of impressions, click-through rate, engagement rate, number of conversions, etc.), analyzes the collected data, and generates a report showing the effectiveness of the ads. This report is sent to the user via their device.

[1950] Input: Ad delivery result data

[1951] Output: Effectiveness report

[1952] Specific operation: The server collects delivery result data from each ad network, generates a report using a data analysis tool, and delivers it to the user's device.

[1953] Step 7:

[1954] Users can check the effectiveness report displayed on their device, which details the ad's performance and areas for improvement. Based on this, users can consider their next advertising strategy.

[1955] Input: Effectiveness report

[1956] Output: Feedback on your next advertising strategy

[1957] Specific operation: The user views the report on the smartphone screen and obtains information to plan their next advertising strategy.

[1958] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1959] The present invention combines a system that efficiently performs a series of advertisement management processes, from inputting advertisement requirements to distribution and report generation, with an emotion engine that recognizes user emotions. A specific embodiment of this system will be described.

[1960] Enter your advertising requirements

[1961] User Action:

[1962] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form allows the user to enter details such as the ad title, description, image, target audience, budget, and distribution period. The user enters this information and clicks the submit button.

[1963] Terminal processing:

[1964] The terminal provides an interface for transmitting information entered by the user to the server, and structures the input data and transmits it to the server.

[1965] Ad creative generation

[1966] Server side:

[1967] The server passes the received advertising requirements to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are sent back to the server.

[1968] Generative AI processing:

[1969] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including content optimized for the target audience.

[1970] Emotion recognition by emotion engine

[1971] Terminal processing:

[1972] While the user is operating the input form, the device uses an emotion engine to recognize the user's emotions in real time. This emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[1973] Server side:

[1974] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[1975] Advertising material inspection

[1976] Server side:

[1977] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[1978] Creative review and approval

[1979] Terminal processing:

[1980] Ad creatives that pass inspection are sent to the device and displayed to the user, who can then review the generated ad and request corrections if necessary.

[1981] User Action:

[1982] The user checks the displayed ad creative, and if satisfied, clicks the "Approve" button to make a final confirmation of ad delivery.

[1983] Preparing for ad delivery

[1984] Server side:

[1985] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including delivery start and end dates, target audience characteristics, budget allocation, etc.

[1986] Ad serving

[1987] Server side:

[1988] The server distributes advertisements to each ad network (for example, major domestic ad networks and overseas partner networks) based on a set schedule, providing advertising materials in a format optimized for each ad distribution destination.

[1989] Ad performance collection and reporting

[1990] Server side:

[1991] After an ad is delivered, the server collects its performance (number of impressions, click-through rate, engagement rate, number of conversions, etc.). The collected data is analyzed and a report is automatically generated. The report details the effectiveness of the ad and areas for improvement.

[1992] Utilizing Emotional Data

[1993] Server side:

[1994] The collected emotional data is included in ad performance reports, which deepens the emotional understanding of advertising campaigns. Furthermore, the emotional data is used to propose next advertising strategies. For example, past emotional data can be analyzed to suggest what type of creative will be more effective for the next campaign.

[1995] Checking advertising reports and next strategies

[1996] Terminal processing:

[1997] The generated report is sent to the terminal and displayed to the user, who can then review the report and evaluate the effectiveness of the advertisement.

[1998] User Action:

[1999] Users can use the reports to consider their next advertising strategy. Using the system's built-in strategy suggestion function, they can receive specific suggestions for improvement. For example, they can analyze past emotional data and advertising performance to determine which creatives were effective and incorporate that information into their next strategy.

[2000] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[2001] The processing flow will be explained below.

[2002] Step 1:

[2003] User begins creating ad

[2004] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen, which displays an input form for creating an ad.

[2005] Step 2:

[2006] The device displays the input form

[2007] The device displays a form for creating an ad to the user, including fields for the ad title, description, image, target audience, budget, and delivery period.

[2008] Step 3:

[2009] User enters advertising requirements

[2010] The user enters the advertising requirements in the displayed input form, and once all the required information has been entered, the user clicks the submit button to confirm the input data.

[2011] Step 4:

[2012] The device sends the input data to the server

[2013] The terminal structures the advertising requirements entered by the user and sends them to the server, which then obtains the conditions for generating advertising creatives.

[2014] Step 5:

[2015] The server passes the data to the generated AI.

[2016] The server inputs the received advertising requirements into a generative AI engine and requests it to generate advertising creative. The generative AI generates optimal designs and copy based on the input information.

[2017] Step 6:

[2018] Generative AI generates ad creatives

[2019] Generative AI uses machine learning models to automatically generate ad creative based on input factors, including optimizing for the target audience.

[2020] Step 7:

[2021] The device activates the emotion engine

[2022] While the user is operating the input form, the device activates an emotion engine and acquires emotion data in real time from the user's facial expressions, voice, etc.

[2023] Step 8:

[2024] Emotion engine analyzes emotional data

[2025] The emotion engine analyzes the acquired data and recognizes the user's emotional state, which is then transmitted to the server.

[2026] Step 9:

[2027] Server inspects generated creative

[2028] The generated ad creatives are then subject to content inspection by the server's inspection means. This is a filtering process to ensure that the ad does not contain violent or adult content. If any inappropriate content is found, it is automatically corrected or instructed to be regenerated.

[2029] Step 10:

[2030] The server sends the ad creative to the device

[2031] Ad creatives that pass inspection are sent from the server to the device, which then displays them to the user.

[2032] Step 11:

[2033] User reviews ad creative

[2034] The user can review the ad creative displayed on their device, request corrections if necessary, and click the approve button if they are satisfied.

[2035] Step 12:

[2036] Prepare to deliver ads

[2037] After receiving final approval from the user, the server sets the schedule and delivery settings for ad delivery, including the delivery start date, end date, target audience characteristics, budget allocation, etc.

[2038] Step 13:

[2039] Ads delivered to ad networks

[2040] The server distributes ads to each ad network based on a set schedule, and the distributed ads are converted into a format suitable for each network.

[2041] Step 14:

[2042] Collect ad performance data

[2043] The server collects performance data such as ad impressions, click-through rates, engagement rates, and conversions.

[2044] Step 15:

[2045] The server generates the report

[2046] The server generates a report based on the collected ad performance data, which details the effectiveness of the ad and areas for improvement.

[2047] Step 16:

[2048] The server sends the report to the device.

[2049] The generated report is sent from the server to the terminal and displayed to the user.

[2050] Step 17:

[2051] User checks the report

[2052] The user checks the report displayed on the terminal and evaluates the effectiveness of the advertisement.

[2053] Step 18:

[2054] Users consider their next advertising strategy

[2055] Users can use the reports to plan their next advertising strategy. The system's built-in strategy suggestion function allows users to receive specific suggestions for improvement. For example, users can analyze past emotional data and ad performance to determine which creatives were effective and incorporate these into their next strategy.

[2056] Example 2

[2057] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2058] Current advertising management systems have a complicated process from entering advertising requirements to delivering ads and measuring their effectiveness, making it difficult to manage efficiently. Another issue is that they are unable to generate advertising creatives that take user emotions into account in order to improve advertising effectiveness. Furthermore, there is no established method for utilizing emotional data in measuring advertising effectiveness.

[2059] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generating means for generating advertising creatives based on the advertising requirements, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to a distribution network, a means for collecting advertising performance results and generating reports, and a means for recognizing emotion data in real time and utilizing it in generating and adjusting advertising creatives. This makes it possible to streamline the advertising management process and generate advertising creatives that take user emotions into consideration. Furthermore, utilizing emotion data can be expected to propose more effective advertising strategies and improve advertising effectiveness.

[2060] "Advertising requirements" refers to all information required to create and distribute an advertisement, including, but not limited to, the title, description, images, target audience, budget, and distribution period.

[2061] "Generation means" refers to technologies and algorithms for automatically generating advertising creatives based on input advertising requirements, and includes artificial intelligence technologies such as machine learning models.

[2062] "Inspection methods" refers to technologies and algorithms used to filter the content of generated advertising creatives and remove inappropriate elements.

[2063] "Delivery Network" means the online and offline outlets and platforms through which advertising is delivered to a target audience, including, specifically, major online advertising networks and partnerships.

[2064] "Advertising performance results" refers to data on the effect that delivered advertisements had on users, including the number of impressions, click-through rate, engagement rate, and number of conversions.

[2065] "Report generation" refers to the process of evaluating and analyzing advertising campaigns based on collected advertising performance results and compiling the results into a document.

[2066] "Emotion data" refers to an emotional state recognized based on data such as a user's facial expression, voice, and operation log.

[2067] "Advertising creative" refers to advertising materials generated based on advertising requirements, and specifically includes images, text, layout, etc.

[2068] "Generative AI engine" refers to a platform or algorithm that uses artificial intelligence technology to automatically generate advertising creatives based on input data.

[2069] The present invention is a system for efficiently performing a series of advertising management processes, from inputting advertising requirements to distribution and report generation, and is combined with an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[2070] Enter your advertising requirements

[2071] User Action:

[2072] Users start the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. The form contains fields for entering details such as the ad title, description, image, target audience, budget, and delivery period. For example, users enter the following information:

[2073] Title: "Experience the next generation smartphone now"

[2074] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[2075] Image: New product photos

[2076] Target audience: Technology-interested men and women aged 25-45

[2077] Budget: 500,000 yen

[2078] Distribution period: November 1st to December 31st, 2023

[2079] Terminal processing:

[2080] The terminal provides an interface for sending information entered by the user to the server, converting the input data into a structured format such as JSON and sending it to the server.

[2081] Ad creative generation

[2082] Server side:

[2083] The server passes the advertising requirements received from the device to the generation AI engine and requests it to generate advertising creatives. The generation AI engine automatically generates advertising materials (images, text, layout, etc.) based on the input information. The generated advertising creatives are then sent back to the server.

[2084] Examples of prompts include:

[2085] Please use the information below to generate advertising creative for next-generation smartphones.

[2086] Title: Experience the next generation smartphone now

[2087] Description: A next-generation smartphone with innovative features and design. Learn more here.

[2088] Image: [URL of new product photo]

[2089] Target audience: Technology-interested men and women aged 25-45

[2090] Emotion recognition by emotion engine

[2091] Terminal processing:

[2092] The device uses an emotion engine to recognize the user's emotions in real time while the user is operating the input form. Emotion data is acquired based on data such as the user's facial expressions, voice, and operation logs.

[2093] Server side:

[2094] The acquired emotional data is used to generate and adjust the ad creative. The server analyzes the emotional data and adjusts the ad creative accordingly based on the user's emotions. For example, if there are a lot of positive emotions, the server selects designs and copy that emphasize those emotions.

[2095] Inspection and distribution of advertising materials

[2096] Server side:

[2097] The generated ad creatives are inspected by the server's inspection means to check whether the ad contains violent or inappropriate content, and if any inappropriate content is found, it is automatically corrected or instructed to be regenerated. Ad creatives that pass inspection are delivered in a format optimized for each delivery network.

[2098] Ad performance collection and reporting

[2099] Server side:

[2100] After an ad is delivered, ad performance data such as the number of impressions, click-through rate, engagement rate, and number of conversions are collected. The collected data is analyzed and a detailed report is automatically generated. This report details the effectiveness of the ad and areas for improvement.

[2101] Utilizing emotion data and next-generation strategies

[2102] Server side:

[2103] The collected emotional data is also included in ad performance reports. A detailed understanding of emotional responses can be used to suggest future advertising strategies. For example, analyzing past emotional data can suggest which creative elements were most effective in the next campaign.

[2104] Terminal side processing and user side processing:

[2105] The generated report is sent to the terminal and displayed to the user. The user can use the report to consider their next advertising strategy and receive specific suggestions for improvement using the system's strategy suggestion function.

[2106] In this way, the system of the present invention allows advertisers to easily and efficiently carry out a series of processes from generating advertising creatives to distributing them, measuring their effectiveness, and utilizing emotional data.

[2107] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2108] Step 1:

[2109] User Action:

[2110] The user starts the ad creation process by clicking the "Create Ad" button on the dedicated management screen. This action displays an input form for creating an ad. Specifically, the user enters the following information into the form:

[2111] title

[2112] Description

[2113] image

[2114] Target Audience

[2115] budget

[2116] Distribution period

[2117] Input: Ad details (title, description, image, target audience, budget, delivery period)

[2118] Output: Data entered in the input form

[2119] Step 2:

[2120] Terminal processing:

[2121] The terminal converts the contents of the input form into a structured data format (for example, JSON format) and sends it to the server. Specifically, the data is structured as follows:

[2122] Ad title: "Experience the next generation smartphone now"

[2123] Description: "A next-generation smartphone with innovative features and design. Learn more here."

[2124] Image URL: "example.com / image.png"

[2125] Target audience: "Men and women aged 25-45 who are interested in technology"

[2126] Budget: 500,000 yen

[2127] Distribution period: November 1st to December 31st, 2023

[2128] Input: Data entered into an input form

[2129] Output: Structured data to send to the server

[2130] Step 3:

[2131] Server side:

[2132] The server stores the received advertising requirements in a database and requests the AI ​​engine to generate advertising creatives. Specifically, the server sends the following prompt to the AI ​​engine:

[2133] Please use the information below to generate advertising creative for next-generation smartphones.

[2134] Title: Experience the next generation smartphone now

[2135] Description: A next-generation smartphone with innovative features and design. Learn more here.

[2136] Image: example.com / image.png

[2137] Target audience: Technology-interested men and women aged 25-45

[2138] Input: Structured ad requirements data

[2139] Output: Prompt sent to the generative AI engine

[2140] Step 4:

[2141] Processing by the generative AI engine:

[2142] The generative AI engine automatically generates ad creatives based on prompt text. Specifically, it generates the following data:

[2143] Advertising banner image

[2144] Ad text

[2145] Layout Information

[2146] Input: Prompt received from the server

[2147] Output: Generated ad creative data (images, text, layout)

[2148] Step 5:

[2149] Server side:

[2150] The ad creative returned by the generation AI engine is received and passed to the inspection means. Specifically, the ad creative content is checked to see if there is any inappropriate content.

[2151] Input: Generated ad creative data

[2152] Output: Ad creative data that passes inspection

[2153] Step 6:

[2154] Server side:

[2155] After the ad creative passes inspection, it is provided to the distribution network in an optimized format, for example, by adapting the creative to the format of each distribution network.

[2156] Input: Ad creative data that has passed inspection

[2157] Output: Ad creative data optimized for each distribution network

[2158] Step 7:

[2159] Terminal processing:

[2160] The generated ad creative is sent to the terminal and displayed for user confirmation, specifically displaying a screen that allows the user to preview the ad creative.

[2161] Input: Ad creative data optimized for each distribution network

[2162] Output: Ad creative displayed on device

[2163] Step 8:

[2164] User Action:

[2165] The user can review the ad and click the "Approve" button for final confirmation. If necessary, they can request corrections.

[2166] Input: Previewed ad creative

[2167] Output: Approval or correction request

[2168] Step 9:

[2169] Server side:

[2170] Once final approval is received, the schedule and delivery settings for ad delivery are set, including the delivery start date, end date, target audience characteristics, and budget allocation.

[2171] Input: User authorization data

[2172] Output: Ad delivery schedule and delivery setting data

[2173] Step 10:

[2174] Server side:

[2175] The advertisements are distributed to each distribution network according to a set schedule. Specifically, the advertisement material is transmitted to the distribution network.

[2176] Input: Distribution setting data

[2177] Output: Ad creative sent to the delivery network

[2178] Step 11:

[2179] Server side:

[2180] It collects ad performance results and generates reports. Specifically, it collects and analyzes the following data:

[2181] Impressions

[2182] Click-through rate

[2183] Engagement Rate

[2184] Conversions

[2185] Input: Performance data of delivered ads

[2186] Output: Ad performance report

[2187] Step 12:

[2188] Server side:

[2189] The system analyzes emotional data included in advertising campaign reports and uses it to propose next-generation strategies. Specifically, it compares past emotional data with advertising performance and proposes optimal creatives.

[2190] Input: Ad performance reports and sentiment data

[2191] Output: Proposal data for next advertising strategy

[2192] Step 13:

[2193] Terminal processing:

[2194] The generated report is sent to the terminal and displayed to the user.

[2195] Input: Ad Performance Report

[2196] Output: Report displayed on terminal

[2197] These processing steps allow advertisers to efficiently generate, distribute, measure the effectiveness of their ads, and develop next-generation strategies. Furthermore, by utilizing emotion data, they can create ad creatives that are more relevant to their target audience.

[2198] (Application example 2)

[2199] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2200] Traditional ad management systems generate ad creatives without considering user emotions, making it difficult to resonate with the target audience. Furthermore, the ad creative generation process is complex and time-consuming, and there is insufficient measurement of ad effectiveness after delivery. This makes it difficult for advertisers to optimize their ad campaigns, potentially resulting in wasted budgets.

[2201] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for accepting input of advertising requirements, a generation means for generating advertising creatives based on the advertising requirements, an emotion recognition means for recognizing user emotions in real time, a means for using emotion data to generate and adjust advertising creatives, a means for inspecting the generated advertising creatives, a means for delivering advertising creatives that pass inspection to an ad network, and a means for collecting advertising performance results and generating reports. This enables the generation of advertising creatives that take user emotions into consideration, thereby increasing empathy with the target audience. It also streamlines the process from ad generation to delivery and effectiveness measurement, making it easier to optimize advertising campaigns.

[2202] "Advertising requirements" refers to a collection of information required to run an advertising campaign, including details such as the ad title, description, images, target audience, budget, and distribution period.

[2203] "Generative method" refers to the process of using machine learning models or generative AI to automatically generate advertising creative based on input advertising requirements.

[2204] An "emotion recognition means" is a combination of a device and software for analyzing a user's facial expressions and voice in real time and acquiring emotional data.

[2205] "Emotion data" is information about the user's emotional state obtained by the emotion recognition means, and is used to generate and adjust advertising creatives.

[2206] "Inspection method" refers to the process used to filter generated ad creatives to ensure they do not contain inappropriate content.

[2207] "Delivery method" refers to the process by which the inspected ad creative is sent to the ad network, which then displays the ad to the target audience.

[2208] "Advertising performance" refers to performance indicators after an advertisement is delivered, and specifically includes the number of impressions, click-through rate, engagement rate, number of conversions, etc.

[2209] "Collection means" refers to the process for collecting performance data after advertisement delivery, which is used to measure the effectiveness of the advertisement.

[2210] "Report generation means" refers to a process for analyzing collected advertising performance results and automatically generating reports.

[2211] "Camera and microphone" are input devices that capture the user's facial expressions and voice to provide data for emotion recognition.

[2212] An "emotion recognition engine" is software that analyzes data acquired by a camera and microphone and estimates the user's emotional state.

[2213] A "machine learning model" is a collection of algorithms that learn patterns from input data and automatically generate advertising creatives.

[2214] "Filtering measures" are processes used to inspect the advertising creative generated by the machine learning model to ensure it does not contain inappropriate content.

[2215] This invention provides a system that automates a series of processes from inputting advertising requirements to generating advertising creatives, recognizing emotions, delivering advertisements, and measuring their effectiveness. Specific embodiments of this ...

Claims

1. means for accepting input of advertising requirements; A generating means for generating an advertising creative based on the advertising requirements; means for inspecting the generated advertising creative; A means to deliver the inspected ad creative to the ad network, a means of collecting and generating reports on advertising performance; A system including:

2. means for displaying an input form for advertising requirements; means for transmitting said advertising requirements to a server; a means for displaying the generated advertising creative; a means to view reports on ad performance; The system of claim 1 further comprising:

3. a means for using machine learning models for generating advertising creative; means for filtering the advertising creatives generated by the machine learning model; The system of claim 1 further comprising:

4. a means of scheduling the placement of advertisements; A means to manage settings for ad delivery; The system of claim 1 further comprising:

5. A method to propose the next advertising strategy based on the results of advertising, means for automatically updating advertising requirements based on the proposed advertising strategy; The system of claim 1 further comprising:

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