System

Abstract

A system is provided.SOLUTION: A system comprising: means for providing a form for inputting information of a product or service provided by a user; means for analyzing the input information of the product or service and automatically generating an advertisement copy; means for optimizing the generated advertisement copy based on information of a target audience; means for automatically placing the advertisement copy on an optimal advertisement distribution platform; means for measuring an effect of the placed advertisement in real time; and means for generating and displaying a report based on the effect of the advertisement.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] Small businesses and SMEs face the challenge of placing ads due to a lack of expertise and resources in ad production and digital marketing. Furthermore, with so many ad distribution platforms available, it can be difficult to determine which platform is most effective. Therefore, there is a need for a method to easily generate high-quality ads, distribute them through the optimal advertising media, and maximize advertising effectiveness. [Means for solving the problem]

[0005] The system includes a means for providing a form for users to input information about products or services they offer, a means for analyzing the input product or service information and automatically generating advertising copy, a means for optimizing the generated advertising copy based on target audience information, a means for automatically publishing the advertising copy on the optimal advertising distribution platform, a means for measuring the effectiveness of the published advertisements in real time, and a means for generating and displaying reports based on the effectiveness of the advertisements. Furthermore, by including a means for analyzing target audience information and selecting the optimal advertising distribution platform, users can effectively implement advertising campaigns. Furthermore, by including a means for providing improvements and recommended strategies for the next advertising campaign based on the effectiveness of the advertisements, users can continuously improve their advertising strategies.

[0006] "User" refers to a representative or person in charge of a small business or small business who accesses and uses the System.

[0007] "Product or service information" refers to detailed information such as the name, features, and target customer demographic of the products or services provided by the user.

[0008] "Form" refers to an input screen provided by a server for a user to input information about a product or service.

[0009] "Analysis" refers to the process of analyzing data based on input information and adapting it to specific purposes or conditions.

[0010] "Advertising copy" refers to promotional content such as text and images created to advertise a user's products or services.

[0011] "Target audience" refers to the consumer demographic that is the primary target of an advertisement, and includes attribute information such as gender, age, and region.

[0012] "Optimization" refers to the process of tailoring ad copy to be most effective for your target audience.

[0013] "Advertising distribution platform" refers to websites and applications that provide services for distributing advertisements over the Internet.

[0014] "Automated advertising" refers to the process in which a system automatically delivers ads rather than requiring manual intervention.

[0015] Measuring "effectiveness" refers to the process of evaluating how successful an advertisement is using numbers and data.

[0016] "Report" refers to a result report that compiles data on the effectiveness of an advertisement and provides it to the user in a visual or written form.

[0017] "Strategy" refers to the plans and methods used to effectively implement an advertising campaign. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertising copy, and automatically posts the advertisements on the most suitable advertising distribution platform.

[0040] First, a form is displayed on the device for the user to enter information about the product or service. The form has fields for entering the product name, description, and target audience information (gender, age, region, etc.). The user enters detailed information about their product or service in these fields and clicks the submit button.

[0041] The server then stores the information in a database, which automatically analyzes it and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information the user provided.

[0042] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. Data such as gender, age, and location play an important role in this process. For example, casual language may be used for younger audiences, while phrases that convey a sense of trust may be selected for older audiences.

[0043] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0044] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0045] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server analyzes this data and generates an ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the data after posting, keywords and phrases to use in the next advertising campaign are suggested.

[0046] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, they can grasp the effectiveness of their advertisements in real time, allowing them to flexibly improve their advertising strategies.

[0047] The above is an embodiment of the present invention.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] User

[0051] The user accesses a form through their device to enter product information and target audience details, including the product name, description, target demographic (e.g., age, gender, region), etc. Once completed, they click the submit button.

[0052] Step 2:

[0053] server

[0054] When the user clicks the submit button, the input data is received and saved in a database. At this point, the input data includes the product name, description, and target audience details.

[0055] Step 3:

[0056] server

[0057] The server then runs a natural language processing (NLP) engine based on the stored data. The server analyzes product and target audience information and automatically generates ad copy, which includes keywords and phrases to enhance marketing effectiveness.

[0058] Step 4:

[0059] server

[0060] The generated ad copy is optimized based on target audience information. Attributes such as gender, age, and region are taken into account to adjust the ad copy for maximum effectiveness. For example, trendy wording is used for younger demographics, while phrases emphasizing trustworthiness are added for older demographics.

[0061] Step 5:

[0062] server

[0063] The optimized ad copy is then published to the appropriate ad distribution platform. The server automatically publishes the ad using the API of the selected platform (e.g., Facebook, Instagram, Google Ads).

[0064] Step 6:

[0065] server

[0066] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected and analyzed. This data is used to optimize ad delivery in the future.

[0067] Step 7:

[0068] server

[0069] Generate detailed reports based on the collected advertising effectiveness data, including advertising performance metrics (e.g., CTR, CPC, ROI) and target audience responses.

[0070] Step 8:

[0071] User

[0072] Users can view reports provided by the server on a dashboard, and can use the report content to consider strategies for their next advertising campaign.

[0073] Step 9:

[0074] server

[0075] Furthermore, it automatically suggests improvements and recommended strategies for the next advertising campaign based on advertising effectiveness, which users can use to improve their advertising strategies.

[0076] Step 10:

[0077] User

[0078] By entering information for your next advertising campaign and repeating the same process, you can continuously optimize your advertising effectiveness.

[0079] Example 1

[0080] 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."

[0081] For small businesses to easily create and distribute high-quality web advertisements requires a great deal of expertise and time. Furthermore, they have limited tools and resources to understand the effectiveness of their advertisements in real time and flexibly improve their strategies. To address these challenges, there is a need for a system that allows businesses to easily create high-quality advertisements without specialized knowledge, and monitor and improve their effectiveness in real time.

[0082] 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.

[0083] In this invention, the server includes means for providing a form including fields for users to input information about products or services they offer, means for saving the input product or service information in a database, means for analyzing the saved information using a natural language processing engine and automatically generating advertising copy, means for optimizing the generated advertising copy based on target audience information, means for automatically publishing the optimized advertising copy using an advertising distribution platform's API, means for measuring the number of impressions, click-through rates, and conversion rates of published advertisements in real time, and means for generating detailed reports based on the effectiveness of the advertisements and displaying them on a dashboard. This enables even small businesses without specialized knowledge to easily create and publish high-quality advertisements, understand their effectiveness in real time, and flexibly improve their advertising strategies.

[0084] A "form" is a screen display containing multiple fields for a user to enter product or service information.

[0085] "Database" means a digital storage system for storing product or service information entered by users.

[0086] A "natural language processing engine" is a software technology that analyzes input sentences and text information to generate sentences and perform semantic analysis.

[0087] "Ad copy" refers to a text message that introduces the product or service you offer and appeals to your target audience.

[0088] A "target audience" is a group of people with specific attributes to whom advertising is intentionally directed, such as people of a particular gender, age, location, etc.

[0089] "Optimization" refers to the process of adjusting generated ad copy based on target audience information to make it more effective.

[0090] An "advertising distribution platform" is an online system that distributes generated advertising copy and delivers it to many users.

[0091] An "API (Application Programming Interface)" is a set of definitions and protocols that allow different software systems to communicate with each other.

[0092] "Impressions" refers to the total number of times an advertisement is displayed on a user's screen.

[0093] "Click-through rate" refers to the percentage of users who click on an ad compared to the number of times it is displayed.

[0094] A "conversion rate" is the percentage of users who click on an ad and then actually take a specific action, such as purchasing a product or using a service.

[0095] A "report" is a written or digital output that provides a detailed analysis of the effectiveness of advertising and summarizes the results in an easy-to-understand format.

[0096] "Dashboard" means an interface that allows users to access the system's management screen and check advertising effectiveness and other important information in real time.

[0097] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically posts the advertisements on the most suitable advertisement distribution platform.

[0098] System configuration

[0099] User Input

[0100] The device displays a form for the user to enter product or service information. The form contains the following fields:

[0101] Product name

[0102] Product Description

[0103] Target audience information (gender, age, region, etc.)

[0104] The user enters the required information into these fields and clicks the submit button, which sends the information to the server.

[0105] Data storage and analysis

[0106] The server stores the received information in a database, where it is analyzed using a natural language processing (NLP) engine to automatically generate ad copy, which includes attractive keywords and phrases based on the information provided by the user.

[0107] Ad copy optimization

[0108] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. For example, ad copy aimed at younger audiences might use casual language, while phrases that exude trustworthiness might be selected for older audiences.

[0109] Automatic ad placement

[0110] The optimized ad copy is automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0111] Report generation and dashboard viewing

[0112] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0113] Specific examples

[0114] For example, consider a case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, its features (e.g., "healthy, made with organic ingredients"), and the target demographic (health-conscious women in their 20s) into a form.

[0115] The server then parses this data and generates ad copy like this:

[0116] "Try our healthy organic green tea now!"

[0117] The server then optimizes the ad copy for the target audience and automatically places it on platforms like Instagram, a platform for young people.The server then measures the number of impressions, click-through rates, conversion rates, and other data in real time, generating detailed reports that are displayed on the user's dashboard.

[0118] Prompt Sentence Examples

[0119] An example of a prompt to input to a generative AI model is as follows:

[0120] Please generate advertising copy promoting our new product, "Organic Green Tea," aimed at health-conscious women in their 20s. Please clearly state the product name and its features (healthy, uses organic ingredients), and use language that will resonate with the target audience.

[0121] This system allows small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, the effectiveness of advertisements can be monitored in real time, allowing for flexible improvements to advertising strategies.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1: Enter your information

[0124] The terminal displays a form for the user to enter product or service information. The form contains fields for entering the product name, product description, and target audience information (gender, age, region, etc.). The user enters the required information in these fields and clicks the submit button. The input for this step is the product or service information entered by the user in the form, and the output is the user-entered data that is sent to the server.

[0125] Step 2: Save your data

[0126] The server receives the information sent by the user. The server saves the entered information in a database. The input of this step is the product or service information sent by the user, and the output is the user information saved in the database.

[0127] Step 3: Analyze the data and generate ad copy

[0128] The server retrieves user information from a database and analyzes it using a natural language processing (NLP) engine. The server generates ad copy based on the input information. This ad copy contains attractive keywords and phrases based on the information the user provided. The input for this step is the user information stored in the database, and the output is the generated ad copy.

[0129] Step 4: Optimize your ad copy

[0130] The server optimizes the generated ad copy based on target audience information. The server analyzes data such as the target audience's gender, age, and region and adjusts the ad copy. For example, it selects casual language for younger demographics and phrases that convey trustworthiness for older demographics. The input for this step is the generated ad copy and target audience information, and the output is the optimized ad copy.

[0131] Step 5: Automated Ad Placement

[0132] The server automatically posts the optimized ad copy to the ad distribution platform. The server then uses the ad distribution platform's API to send the ad. The posted ad is then delivered to the specified target audience. The input for this step is the optimized ad copy and the ad distribution platform's API information, and the output is the ad posted to the distribution platform.

[0133] Step 6: Measuring advertising effectiveness

[0134] The server measures the effectiveness of advertising in real time after it is posted. The data measured includes the number of impressions, click rates, conversion rates, etc. The server collects and analyzes this data. The input to this step is the advertising effectiveness data obtained from the distribution platform, and the output is the analysis results.

[0135] Step 7: Generate reports and view dashboards

[0136] The server generates a detailed report based on the advertising effectiveness. The generated report is displayed on the user's dashboard. The user can check the performance of the advertising campaign through this report. It also displays improvements and recommended strategies for the next advertising campaign. The input of this step is the analyzed advertising effectiveness data, and the output is a detailed report that is displayed on the user's dashboard.

[0137] The above are the specific processing steps and details of this system, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[0138] (Application example 1)

[0139] 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."

[0140] Small businesses need a way to easily create and effectively distribute high-quality web advertisements. However, this requires specialized advertising knowledge and expensive software, making it difficult to achieve. It is also extremely difficult to measure the effectiveness of advertisements in real time and reflect the results in the next advertising campaign. For these reasons, there is an urgent need to provide a system that allows even small businesses to easily send out high-quality, effective advertisements.

[0141] 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.

[0142] In this invention, the server includes: means for providing a form for users to input information about products or services they offer; means for analyzing the input product or service information and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information; means for automatically publishing the advertising copy to the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means configured as an application executed on a smartphone, for generating advertising copy using a natural language processing engine and publishing the advertisement using the API of the advertising distribution platform; and means for users to input product information using a smartphone and distribute the generated advertising copy. This enables small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge.

[0143] 1. "Form for entering information about products or services provided by users" means an electronic form that allows users to enter information about the products they sell or the services they provide.

[0144] 2. "Means for analyzing input product or service information and automatically generating advertising copy" refers to a system element that automatically generates advertising copy based on product or service information provided by users using a natural language processing engine or similar.

[0145] 3. "Means for optimizing generated ad copy based on target audience information" refers to a system element that optimizes generated ad copy based on information such as the gender, age, and place of residence of the target audience.

[0146] 4. "Means for automatically posting ad copy on the most appropriate ad distribution platform" refers to a function that automatically posts generated and optimized ad copy on the appropriate ad distribution platform.

[0147] 5. "Means for measuring the effectiveness of published advertisements in real time" refers to a function that collects and measures performance data such as the number of times an advertisement is displayed, click rate, and conversion rate in real time after the advertisement has been published.

[0148] 6. "Means for generating and displaying reports based on advertising effectiveness" refers to a function that generates and displays reports in a format that is easy for users to understand, based on advertising effectiveness data measured in real time.

[0149] 7. "Applications running on smartphones" means application software that runs on smartphones and allows users to input product information and generate, submit, and manage advertisements.

[0150] 8. "Means for generating advertising copy using a natural language processing engine" refers to a system element that uses natural language processing technology to automatically create effective advertising copy from product or service information provided by users.

[0151] 9. "Means for placing advertisements using the API of an advertising distribution platform" refers to a system element that automatically places generated and optimized advertising copy using the API provided by the advertising distribution platform.

[0152] 10. "Means for users to input product information using a smartphone and distribute the generated advertising copy" refers to a function that enables users to input product or service information using a smartphone and distribute advertising copy generated based on that information.

[0153] MODE FOR CARRYING OUT THE INVENTION

[0154] Specific embodiments for carrying out the present invention will be described below.

[0155] System configuration

[0156] The system includes the following hardware and software.

[0157] Hardware:

[0158] Smartphone: The device used by the user

[0159] Server: A central device that generates, optimizes, places, and measures the effectiveness of advertisements.

[0160] software:

[0161] Flask: a web framework

[0162] requests: HTTP request library

[0163] nltk: Natural Language Processing Library

[0164] Processing flow

[0165] 1. User input:

[0166] Using their smartphone, users fill out a form with the product name, description, and target audience details (e.g., age, gender, and region).

[0167] 2. Transmission and storage of information:

[0168] The entered information is sent from the smartphone to the server and stored in a database.

[0169] 3. Generating ad copy:

[0170] The server generates ad copy using the NLTK natural language processing engine. For example, if a user wants to advertise "organic green tea," the server generates ad copy such as "New organic green tea, a delicious tea perfect for health-conscious people. Order now!"

[0171] 4. Ad copy optimization:

[0172] The generated ad copy is optimized based on target audience information (e.g., women in their 20s living in urban areas). For example, casual language is used for younger audiences, while phrases that enhance trustworthiness are used for older audiences.

[0173] 5. Advertising:

[0174] The optimized ad copy is sent to the ad distribution platform's API using the requests library and is automatically published.

[0175] 6. Measuring results and displaying reports:

[0176] The effectiveness of the ads is measured in real time. The server collects data such as the number of impressions, click rates, and conversion rates, and generates reports based on this data, which are then displayed on a dashboard on the smartphone.

[0177] 7. Next strategy proposal:

[0178] Based on advertising effectiveness data, we provide users with improvements and recommended strategies for their next advertising campaign.

[0179] Specific examples

[0180] For example, if a user wants to advertise "organic green tea," they enter the following information into a form on their smartphone:

[0181] Product name: Organic Green Tea

[0182] Description: A delicious organic green tea perfect for health-conscious individuals.

[0183] Target audience: Health-conscious women in their 20s

[0184] An example of a prompt generated based on the input information:

[0185] Prompt statement:

[0186] Product Name: Organic Green Tea

[0187] Description: A delicious organic green tea perfect for health-conscious individuals.

[0188] Target audience: Health-conscious women in their 20s

[0189] The ad copy generated by the server will read, "New organic green tea, delicious tea perfect for health-conscious people. Order now!" The generated ad copy will be automatically posted to the ad distribution platform, and users will be able to check the effectiveness of the ad in real time on their smartphones.

[0190] The above is an embodiment of the present invention, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[0191] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0192] Step 1:

[0193] The user uses a smartphone to input information about the product or service. The input includes the product name, description, and target audience information (e.g., age, gender, and region). Once the input is complete, the user clicks the "Submit" button. This action sends the input information from the smartphone to the server.

[0194] input:

[0195] Product name

[0196] explanation

[0197] Target Audience Information

[0198] output:

[0199] Transmission data

[0200] Step 2:

[0201] The server parses the received data and stores it in a database, including product name, description, and target audience information. Once the process is complete, the next ad copy generation process is triggered.

[0202] input:

[0203] Transmission data

[0204] output:

[0205] Stored Data

[0206] Step 3:

[0207] The server uses the stored data to generate ad copy using the NLTK natural language processing engine, which is an attractive representation of the product information provided by the user.

[0208] input:

[0209] Stored Data

[0210] output:

[0211] Generated ad text

[0212] Step 4:

[0213] The server then optimizes the generated ad copy based on target audience information, which includes adjusting the tone and content of the ad copy based on gender, age, region, etc. For example, casual language might be used for younger audiences, while phrases that convey a sense of trust might be selected for older audiences.

[0214] input:

[0215] Generated ad text

[0216] Target Audience Information

[0217] output:

[0218] Optimized ad text

[0219] Step 5:

[0220] The server uses the API of the ad distribution platform to publish the optimized ad copy. It uses the requests library to send the necessary data to the API endpoint.

[0221] input:

[0222] Optimized ad text

[0223] output:

[0224] Confirmation of completion of posting

[0225] Step 6:

[0226] The server measures the effectiveness of the published ads in real time, obtaining data such as the number of impressions, click rates, and conversion rates from the ad distribution platform and continuously monitoring them.

[0227] input:

[0228] Ads placed

[0229] output:

[0230] Effectiveness measurement data

[0231] Step 7:

[0232] The server generates an advertising campaign effectiveness report based on the effectiveness measurement data and displays it on the user's dashboard, which the user can then view on their smartphone.

[0233] input:

[0234] Effectiveness measurement data

[0235] output:

[0236] Effectiveness Report

[0237] Step 8:

[0238] The server analyzes the data from the effectiveness report and provides users with recommendations for improvements and strategies for their next advertising campaign, enabling them to continuously carry out effective advertising operations.

[0239] input:

[0240] Effectiveness Report

[0241] output:

[0242] Improvements and recommended strategies

[0243] 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.

[0244] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. In addition, by using an emotion engine, it analyzes user emotions and reflects them in the creation and optimization of advertisements.

[0245] First, the user accesses a form on their device to enter product information and target audience details. The form has fields for entering information such as the product name, description, and target demographic (e.g., age, gender, and region). The emotion engine then recognizes and analyzes the user's emotions as they type. Once the input is complete, the user clicks the submit button.

[0246] The server then stores the information and sentiment data in a database, which is then automatically analyzed and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information and sentiment of the user.

[0247] The generated ad copy is then further optimized. The server analyzes the target audience information and also adjusts the ad copy by taking into account the user's emotional data. For example, if the user is feeling positive, it will use cheerful and positive language, and if the user is feeling cautious, it will add reassuring phrases. In this process, the target audience's attributes (gender, age, region, etc.) and the user's emotional data play an important role.

[0248] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0249] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad's effectiveness and recommended strategies for the next ad campaign. The emotion engine also influences these improvements and recommended strategies, providing advice that takes the user's emotions into consideration.

[0250] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server, along with this data, uses an emotion engine to analyze the user's emotions and generates ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-post data, keywords and phrases to use in the next advertising campaign are suggested.

[0251] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. Furthermore, by utilizing emotion data, they can implement advertising strategies that match users' emotions and maximize advertising effectiveness. Furthermore, because the effectiveness of advertisements can be grasped in real time, advertising strategies can be flexibly improved.

[0252] The above is an embodiment of the present invention.

[0253] The processing flow will be explained below.

[0254] Step 1:

[0255] User

[0256] A user accesses the system through a terminal and accesses a form to enter product information and target audience details. The form has fields for product name, description, target demographic (e.g., age, gender, region), etc. The user enters information into these fields.

[0257] Step 2:

[0258] Terminal

[0259] While the user is entering information, the emotion engine built into the device monitors the user's input behavior, facial expressions, voice, etc. to recognize emotions. For example, it can analyze the user's facial expressions and tone of voice through a camera or microphone to obtain emotional data in real time.

[0260] Step 3:

[0261] User

[0262] Once the user has completed entering all the required information, they click the send button, which sends the entered data and emotion data to the server.

[0263] Step 4:

[0264] server

[0265] The server stores the received product information, target audience data, and user emotion data in a database, after which the data analysis process begins.

[0266] Step 5:

[0267] server

[0268] The stored data is fed into a natural language processing (NLP) engine, which analyzes product and target audience information to generate ad copy. The NLP engine then selects keywords and phrases to generate more compelling ad copy.

[0269] Step 6:

[0270] server

[0271] The generated ad copy is then further optimized. The server adjusts the copy based on the target audience information to make it more effective. The user's emotional data is also taken into account here. For example, if the user is positive, it uses cheerful and positive language, and if the user is cautious, it adds phrases that emphasize trustworthiness.

[0272] Step 7:

[0273] server

[0274] The optimized ad copy is automatically published on the selected ad distribution platform. The server uses the ad distribution platform's API to place the ad.

[0275] Step 8:

[0276] server

[0277] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected to analyze ad performance.

[0278] Step 9:

[0279] server

[0280] Based on the analysis results, detailed reports are generated, including ad performance metrics and target audience responses. The sentiment engine takes user sentiment data into account and adjusts the report content.

[0281] Step 10:

[0282] User

[0283] Users can view reports provided by the server on a dashboard to check the results of their advertising campaigns, and can use the results of the reports to plan their next advertising strategy.

[0284] Step 11:

[0285] server

[0286] Based on the collected advertising effectiveness data and user sentiment data, the system provides improvements and recommended strategies for the next advertising campaign, including specific advice that takes into account the user's emotions.

[0287] Step 12:

[0288] User

[0289] The user re-enters the information for the next advertising campaign and repeats the same process to continuously optimize advertising effectiveness.

[0290] Example 2

[0291] 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."

[0292] In today's world, even small businesses are required to run efficient and effective advertising campaigns. However, systems that consistently manage everything from creating advertising copy to distribution and measuring effectiveness are expensive and require specialized knowledge, making them unaffordable for many small businesses. Furthermore, creating and effectively distributing advertisements that are optimized for user emotions and target audiences is even more difficult. These issues need to be resolved.

[0293] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0294] In this invention, the server includes: means for analyzing information about products or services provided by a user and the user's emotions, and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information and user emotion data; means for automatically publishing the advertising copy on the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means for presenting improvements and recommended strategies for the next advertising campaign based on the user's emotion data; and means for using an emotion engine that simultaneously analyzes the user's input content and their emotions. This enables even small businesses to run consistently high-quality advertising campaigns without requiring specialized knowledge or high costs. It also enables the creation of advertisements optimized for the user's emotions and target audience, maximizing their effectiveness.

[0295] "User" means an individual or organization that utilizes the System to create and distribute advertising campaigns.

[0296] A "form" is an interface through which a user inputs product or service information.

[0297] "Product or Service Information" means details about the products or services you offer, including product names, descriptions, and target audience attributes (e.g., age, gender, location).

[0298] The "emotion engine" is a mechanism that analyzes the user's input and emotions.

[0299] A "natural language processing (NLP) engine" is a technology that analyzes input information and generates advertising copy in natural language.

[0300] "Ad copy" is a promotional copy automatically generated based on the information about the product or service provided by the user and the target audience.

[0301] A "target audience" is a specific group of users to whom an advertisement is intended to be delivered, and is defined by attributes such as age, gender, and region.

[0302] An "advertising distribution platform" is an online platform for distributing generated advertising copy.

[0303] An "API" (Application Programming Interface) is an interface that allows communication between an advertising distribution platform and a system.

[0304] "Effectiveness data" refers to data used to measure the effectiveness of an advertisement, such as the number of times an advertisement is displayed, click rate, and conversion rate.

[0305] "Report" means a report generated to analyze and demonstrate the effectiveness of an Advertising Campaign.

[0306] "Improvements and recommended strategies" are suggested optimizations and strategies for your next advertising campaign based on the results of your advertising campaign.

[0307] MODE FOR CARRYING OUT THE INVENTION

[0308] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. Additionally, it uses an emotion engine to analyze user emotions and reflect them in the creation and optimization of advertisements.

[0309] Hardware and software used

[0310] Terminal: A device through which a user inputs product or service information. Examples include personal computers (PCs), smartphones, and tablets.

[0311] Server: A device that stores information, analyzes it, generates and optimizes ad copy, places ads, measures their effectiveness, and generates reports. It may be a cloud server or on-premise server with high-performance data processing capabilities.

[0312] Database: A system for storing data obtained from users. A relational database (RDBMS) or a NoSQL database can be used.

[0313] Natural language processing (NLP) engine: Software for analyzing product and service information and generating advertising copy. Open source NLP libraries and commercial NLP tools are used.

[0314] Sentiment engine: Software for analyzing emotions in real time with user input, using machine learning models and sentiment analysis APIs.

[0315] Ad serving platform API: An interface for automatically placing ad copy. Includes Google Ads API, Facebook Ads API, etc.

[0316] Explaining program processing in natural language

[0317] User Input

[0318] The user accesses a dedicated form on the system using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, and region). As the user enters the information, the emotion engine analyzes the user's emotions in real time. When the user clicks the "Submit" button, the information is sent to the server.

[0319] Information storage and analysis

[0320] The server receives the information sent by the user and stores it in a database. The stored information is automatically analyzed using an NLP engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. The generated ad copy incorporates attractive keywords and phrases based on the user's emotional data analyzed by the emotion engine.

[0321] Ad copy optimization

[0322] The server then further optimizes the generated ad copy, taking into account target audience information and user sentiment data—for example, adding upbeat language if the user is expressing positive emotions, or reassuring phrases if the user is expressing caution.

[0323] Advertising and measuring effectiveness

[0324] The optimized ad copy is automatically placed via the server using the API of the ad distribution platform. Once the ad is placed, the server measures its effectiveness in real time, including data such as the number of impressions, click-through rate, and conversion rate.

[0325] Generate and view reports

[0326] The server generates a detailed report based on the effectiveness of the ads and displays it on the user's dashboard. Users can view this report through their devices to check the results of their ad campaigns. It also provides suggestions for improvements and recommended strategies for the next campaign. This allows users to maximize the effectiveness of their ads and receive useful feedback for their next campaign.

[0327] Examples of specific examples and prompts

[0328] As a specific example, consider a case where a user wants to advertise "organic green tea." The user enters the product name, features (e.g., natural, healthy), and target demographic (e.g., health-conscious women in their 20s) on their device. The emotion engine analyzes this data along with the user's emotions and generates ad copy such as "Try healthy organic green tea now!" This ad copy is automatically published on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-publication data, keywords and phrases to use in the next advertising campaign are suggested.

[0329] Example prompt sentence:

[0330] Write the name of your product, a description, and details about your target audience. Also, tell us how you feel these days and want to promote it.

[0331] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0332] Step 1: User Input

[0333] The user accesses the system's dedicated form using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, region). The entered information is simultaneously analyzed by an emotion engine to determine the user's emotions. Specifically, when the user clicks the "Submit" button, the entered data is sent to the server.

[0334] Input: Product name, product description, target demographic details, user sentiment

[0335] Output: User input data sent

[0336] Step 2: Storing information (server)

[0337] The server receives the information sent by the user. The received information is stored in a database. This information includes the product name, product description, target demographic details, and user emotion data. The server securely stores the information and then proceeds to the next analysis step.

[0338] Input: Data submitted by the user

[0339] Output: Data stored in the database

[0340] Step 3: Analyzing information and generating ad copy (server)

[0341] The server retrieves the information stored in the database. This information is then analyzed using a natural language processing (NLP) engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. Analysis data from the emotion engine is also used to add keywords and phrases based on user sentiment to the ad copy.

[0342] Input: Information retrieved from the database

[0343] Output: Generated ad copy

[0344] Step 4: Ad copy optimization (server)

[0345] The server further optimizes the generated ad copy, taking into account target audience information and user sentiment data. For example, it adds upbeat language if the user is expressing positive sentiment, or adds reassuring phrases if the user is expressing cautious sentiment.

[0346] Input: Generated ad copy, target audience information, user sentiment data

[0347] Output: Optimized ad copy

[0348] Step 5: Posting Ads (Server)

[0349] The server automatically places the optimized ad copy using the API of the ad distribution platform. The specific operation of the ad placement is that the server sends the ad copy to the platform via the API, completing the placement process.

[0350] Input: Optimized ad text

[0351] Output: Posting to ad distribution platform completed

[0352] Step 6: Measuring the results (server)

[0353] The server measures the effectiveness of the placed ads in real time. The measured data includes the number of impressions, click rates, conversion rates, etc. Effectiveness data is obtained from the ad distribution platform and analyzed to evaluate the effectiveness.

[0354] Input: Effectiveness data from advertising distribution platform

[0355] Output: Analyzed advertising effectiveness data

[0356] Step 7: Generate and view reports (server, terminal)

[0357] The server generates a detailed report based on the effectiveness of the ads, which is displayed on the user's dashboard and can be viewed via their device, along with suggestions for improvements and recommended strategies for the next campaign.

[0358] Input: Analyzed advertising effectiveness data

[0359] Output: Reports displayed on the user's dashboard, with suggestions for improvement and recommended strategies

[0360] (Application example 2)

[0361] 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."

[0362] It is extremely difficult for small businesses to create high-quality web advertisements on a daily basis and distribute them effectively due to limited expertise and resources. It is also difficult to understand the effectiveness of advertisements in real time and develop optimal advertising strategies based on emotions. For this reason, a system is needed that allows businesses to easily create advertisements, distribute them to appropriate platforms, quickly evaluate and analyze their effectiveness, and flexibly improve their strategies.

[0363] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0364] In this invention, the server includes means for providing a form for users to input information about products or services they offer, means for automatically generating advertising copy by analyzing the input product or service information and user emotion data, means for optimizing the generated advertising copy based on target audience information and user emotion data, means for automatically publishing the advertising copy to an optimal advertising distribution platform, means for measuring the effectiveness of the published advertisement in real time, means for generating and displaying a report based on the effectiveness of the advertisement, means for analyzing user emotion data, means for reflecting the emotion analysis in the generation of advertising copy, means for publishing advertisements using the API of the advertising distribution platform, and means for collecting user emotion data using a smartphone or other mobile device. This enables even small businesses to easily create high-quality advertisements, effectively publish them, measure their effectiveness in real time, and implement optimal advertising strategies using emotion data.

[0365] "Product or service information" is data related to detailed descriptions and attributes of specific products or services offered by users.

[0366] A "form" is an interface or input screen that allows a user to input information about a product or service.

[0367] "Analysis" is the process of understanding input data and extracting patterns and characteristics.

[0368] "Advertising copy" is text used to effectively promote a product or service.

[0369] A "target audience" is a specific consumer group to which an advertisement is directed.

[0370] "Emotion data" is data that includes information about the user's emotional state.

[0371] Optimization is the process of adjusting a system or process to achieve maximum effectiveness toward a specific goal.

[0372] An "advertising distribution platform" is an online service or system for displaying and distributing generated advertisements.

[0373] "Automatic posting" is the process of automatically sending the generated ad copy to a designated ad distribution platform.

[0374] "Real-time" refers to data being processed as soon as it is generated.

[0375] "Measurement" is the process of collecting and analyzing specific data or metrics.

[0376] "Report" means a document or display containing analytical results and statistical data regarding the effectiveness of an Advertising.

[0377] "Emotion analysis means" refers to techniques and functions for analyzing user emotion data.

[0378] "Means for collecting user emotional data" refers to methods or techniques for obtaining data about a user's emotional state using a smartphone or other mobile device.

[0379] "API" stands for Application Programming Interface, and is a means for mutual use of functions and data between different software programs.

[0380] This invention is a system that enables small businesses to create high-quality web advertisements using smartphones and mobile devices and maximize their effectiveness. Detailed embodiments of this system are described below.

[0381] First, this system provides a form for users to enter product or service information through a smartphone or mobile device application. Users enter information such as the product name, description, and target demographic (e.g., age, gender, and region), and simultaneously collect emotional data using a camera and microphone.

[0382] To analyze emotion data, we use the smartphone's camera and microphone and emotion analysis tools (e.g., Emotion API), which allows us to analyze the user's emotional state simultaneously with their input.

[0383] Once the data is entered, the server stores it in a database (e.g., AWS RDS). The stored data is then used to automatically generate ad copy using a natural language processing (NLP) engine (e.g., GPT-4). The generated ad copy is then further optimized based on user sentiment data and target audience information.

[0384] The generated ad copy is automatically submitted to an ad distribution platform (for example, Google Ads API or Facebook Ads API). After submission, the server measures the effectiveness of the ad (number of impressions, click-through rate, conversion rate, etc.) in real time, and generates a detailed report based on this information and displays it on the user's dashboard.

[0385] Users can view reports to check the results of their advertising campaigns and plan their next strategy. The system also provides suggestions for improvement and recommended strategies based on the effectiveness of advertising, providing advice that takes users' emotions into consideration.

[0386] As a concrete example, consider the case where a user wants to advertise a new product, "organic tea." The user enters "organic tea" as the product name and "health-conscious women in their 20s" as the target demographic in an application form, and emotional data is collected using a camera and microphone. The server analyzes this data and generates a positive ad copy such as "Try this organic tea that's good for your body now!" This ad copy is automatically posted on an ad distribution platform for young people, and its effectiveness is measured in real time.

[0387] An example of a prompt for a generative AI model is:

[0388] Product Name: Fruit Cake

[0389] Product Description: A delicious cake made with fresh fruit.

[0390] Target demographic: Young people (women in their 20s)

[0391] User Sentiment: Positive

[0392] What you should pay attention to: Fresh and healthy ingredients

[0393] Use this to generate compelling ad copy.

[0394] In this way, small businesses can easily create high-quality advertisements without specialized knowledge and flexibly maximize their effectiveness.

[0395] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0396] Step 1:

[0397] A user logs into a smartphone or mobile device application and inputs product or service information. The input information includes the product name, description, and target demographic (e.g., age, gender, and region). The camera and microphone are also used to collect user emotion data.

[0398] Input: Product name, description, target demographic, sentiment data

[0399] Output: Input information and emotion data

[0400] Step 2:

[0401] The terminal sends the collected data to the server. The server receives this data and stores it in a database (e.g., AWS RDS). Here, we check that the data is stored correctly.

[0402] Input: Input information and emotion data

[0403] Output: Data stored in the database

[0404] Step 3:

[0405] The server analyzes the stored data and uses a natural language processing (NLP) engine (e.g., GPT-4) to automatically generate ad copy based on the input information (product name, description, target demographic).

[0406] Input: Data stored in the database

[0407] Output: Auto-generated ad text

[0408] Step 4:

[0409] The server optimizes the generated ad copy based on the target user's emotional data and target audience information. For example, if the emotional data is positive, it uses upbeat and positive language, and if the emotional data is cautious, it adds reassuring phrases.

[0410] Input: ad copy, sentiment data, target audience information

[0411] Output: Optimized ad text

[0412] Step 5:

[0413] The server automatically posts the optimized ad copy using the API of the specified ad distribution platform (for example, Google Ads API or Facebook Ads API). When posting, the ad copy is adjusted to fit the terms and format of each platform.

[0414] Input: Optimized ad text

[0415] Output: Ads posted to ad serving platforms

[0416] Step 6:

[0417] The server measures the effectiveness of the advertisement (number of impressions, click rate, conversion rate) in real time after it is posted. The measured data is then saved in the database.

[0418] Input: Advertising effectiveness data

[0419] Output: Advertising effectiveness data stored in a database

[0420] Step 7:

[0421] The server generates detailed reports based on the advertising effectiveness data, which are displayed on the user's dashboard, allowing the user to check the performance of their advertising campaigns and plan their next strategy.

[0422] Input: Advertising effectiveness data stored in the database

[0423] Output: The report that appears on the user's dashboard

[0424] Step 8:

[0425] The server further calculates keywords and phrases to be used in the next advertising campaign, as well as areas for improvement and recommended strategies, based on the advertising effectiveness data and user emotion data, and provides these to the user.

[0426] Input: Advertising effectiveness data, emotion data

[0427] Output: Areas for improvement and recommended strategies

[0428] 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.

[0429] 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.

[0430] 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.

[0431] [Second embodiment]

[0432] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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).

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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."

[0444] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertising copy, and automatically posts the advertisements on the most suitable advertising distribution platform.

[0445] First, a form is displayed on the device for the user to enter information about the product or service. The form has fields for entering the product name, description, and target audience information (gender, age, region, etc.). The user enters detailed information about their product or service in these fields and clicks the submit button.

[0446] The server then stores the information in a database, which automatically analyzes it and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information the user provided.

[0447] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. Data such as gender, age, and location play an important role in this process. For example, casual language may be used for younger audiences, while phrases that convey a sense of trust may be selected for older audiences.

[0448] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0449] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0450] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server analyzes this data and generates an ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the data after posting, keywords and phrases to use in the next advertising campaign are suggested.

[0451] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, they can grasp the effectiveness of their advertisements in real time, allowing them to flexibly improve their advertising strategies.

[0452] The above is an embodiment of the present invention.

[0453] The processing flow will be explained below.

[0454] Step 1:

[0455] User

[0456] The user accesses a form through their device to enter product information and target audience details, including the product name, description, target demographic (e.g., age, gender, region), etc. Once completed, they click the submit button.

[0457] Step 2:

[0458] server

[0459] When the user clicks the submit button, the input data is received and saved in a database. At this point, the input data includes the product name, description, and target audience details.

[0460] Step 3:

[0461] server

[0462] The server then runs a natural language processing (NLP) engine based on the stored data. The server analyzes product and target audience information and automatically generates ad copy, which includes keywords and phrases to enhance marketing effectiveness.

[0463] Step 4:

[0464] server

[0465] The generated ad copy is optimized based on target audience information. Attributes such as gender, age, and region are taken into account to adjust the ad copy for maximum effectiveness. For example, trendy wording is used for younger demographics, while phrases emphasizing trustworthiness are added for older demographics.

[0466] Step 5:

[0467] server

[0468] The optimized ad copy is then published to the appropriate ad distribution platform. The server automatically publishes the ad using the API of the selected platform (e.g., Facebook, Instagram, Google Ads).

[0469] Step 6:

[0470] server

[0471] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected and analyzed. This data is used to optimize ad delivery in the future.

[0472] Step 7:

[0473] server

[0474] Generate detailed reports based on the collected advertising effectiveness data, including advertising performance metrics (e.g., CTR, CPC, ROI) and target audience responses.

[0475] Step 8:

[0476] User

[0477] Users can view reports provided by the server on a dashboard, and can use the report content to consider strategies for their next advertising campaign.

[0478] Step 9:

[0479] server

[0480] Furthermore, it automatically suggests improvements and recommended strategies for the next advertising campaign based on advertising effectiveness, which users can use to improve their advertising strategies.

[0481] Step 10:

[0482] User

[0483] By entering information for your next advertising campaign and repeating the same process, you can continuously optimize your advertising effectiveness.

[0484] Example 1

[0485] 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."

[0486] For small businesses to easily create and distribute high-quality web advertisements requires a great deal of expertise and time. Furthermore, they have limited tools and resources to understand the effectiveness of their advertisements in real time and flexibly improve their strategies. To address these challenges, there is a need for a system that allows businesses to easily create high-quality advertisements without specialized knowledge, and monitor and improve their effectiveness in real time.

[0487] 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.

[0488] In this invention, the server includes means for providing a form including fields for users to input information about products or services they offer, means for saving the input product or service information in a database, means for analyzing the saved information using a natural language processing engine and automatically generating advertising copy, means for optimizing the generated advertising copy based on target audience information, means for automatically publishing the optimized advertising copy using an advertising distribution platform's API, means for measuring the number of impressions, click-through rates, and conversion rates of published advertisements in real time, and means for generating detailed reports based on the effectiveness of the advertisements and displaying them on a dashboard. This enables even small businesses without specialized knowledge to easily create and publish high-quality advertisements, understand their effectiveness in real time, and flexibly improve their advertising strategies.

[0489] A "form" is a screen display containing multiple fields for a user to enter product or service information.

[0490] "Database" means a digital storage system for storing product or service information entered by users.

[0491] A "natural language processing engine" is a software technology that analyzes input sentences and text information to generate sentences and perform semantic analysis.

[0492] "Ad copy" refers to a text message that introduces the product or service you offer and appeals to your target audience.

[0493] A "target audience" is a group of people with specific attributes to whom advertising is intentionally directed, such as people of a particular gender, age, location, etc.

[0494] "Optimization" refers to the process of adjusting generated ad copy based on target audience information to make it more effective.

[0495] An "advertising distribution platform" is an online system that distributes generated advertising copy and delivers it to many users.

[0496] An "API (Application Programming Interface)" is a set of definitions and protocols that allow different software systems to communicate with each other.

[0497] "Impressions" refers to the total number of times an advertisement is displayed on a user's screen.

[0498] "Click-through rate" refers to the percentage of users who click on an ad compared to the number of times it is displayed.

[0499] A "conversion rate" is the percentage of users who click on an ad and then actually take a specific action, such as purchasing a product or using a service.

[0500] A "report" is a written or digital output that provides a detailed analysis of the effectiveness of advertising and summarizes the results in an easy-to-understand format.

[0501] "Dashboard" means an interface that allows users to access the system's management screen and check advertising effectiveness and other important information in real time.

[0502] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically posts the advertisements on the most suitable advertisement distribution platform.

[0503] System configuration

[0504] User Input

[0505] The device displays a form for the user to enter product or service information. The form contains the following fields:

[0506] Product name

[0507] Product Description

[0508] Target audience information (gender, age, region, etc.)

[0509] The user enters the required information into these fields and clicks the submit button, which sends the information to the server.

[0510] Data storage and analysis

[0511] The server stores the received information in a database, where it is analyzed using a natural language processing (NLP) engine to automatically generate ad copy, which includes attractive keywords and phrases based on the information provided by the user.

[0512] Ad copy optimization

[0513] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. For example, ad copy aimed at younger audiences might use casual language, while phrases that exude trustworthiness might be selected for older audiences.

[0514] Automatic ad placement

[0515] The optimized ad copy is automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0516] Report generation and dashboard viewing

[0517] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0518] Specific examples

[0519] For example, consider a case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, its features (e.g., "healthy, made with organic ingredients"), and the target demographic (health-conscious women in their 20s) into a form.

[0520] The server then parses this data and generates ad copy like this:

[0521] "Try our healthy organic green tea now!"

[0522] The server then optimizes the ad copy for the target audience and automatically places it on platforms like Instagram, a platform for young people.The server then measures the number of impressions, click-through rates, conversion rates, and other data in real time, generating detailed reports that are displayed on the user's dashboard.

[0523] Prompt Sentence Examples

[0524] An example of a prompt to input to a generative AI model is as follows:

[0525] Please generate advertising copy promoting our new product, "Organic Green Tea," aimed at health-conscious women in their 20s. Please clearly state the product name and its features (healthy, uses organic ingredients), and use language that will resonate with the target audience.

[0526] This system allows small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, the effectiveness of advertisements can be monitored in real time, allowing for flexible improvements to advertising strategies.

[0527] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0528] Step 1: Enter your information

[0529] The terminal displays a form for the user to enter product or service information. The form contains fields for entering the product name, product description, and target audience information (gender, age, region, etc.). The user enters the required information in these fields and clicks the submit button. The input for this step is the product or service information entered by the user in the form, and the output is the user-entered data that is sent to the server.

[0530] Step 2: Save your data

[0531] The server receives the information sent by the user. The server saves the entered information in a database. The input of this step is the product or service information sent by the user, and the output is the user information saved in the database.

[0532] Step 3: Analyze the data and generate ad copy

[0533] The server retrieves user information from a database and analyzes it using a natural language processing (NLP) engine. The server generates ad copy based on the input information. This ad copy contains attractive keywords and phrases based on the information the user provided. The input for this step is the user information stored in the database, and the output is the generated ad copy.

[0534] Step 4: Optimize your ad copy

[0535] The server optimizes the generated ad copy based on target audience information. The server analyzes data such as the target audience's gender, age, and region and adjusts the ad copy. For example, it selects casual language for younger demographics and phrases that convey trustworthiness for older demographics. The input for this step is the generated ad copy and target audience information, and the output is the optimized ad copy.

[0536] Step 5: Automated Ad Placement

[0537] The server automatically posts the optimized ad copy to the ad distribution platform. The server then uses the ad distribution platform's API to send the ad. The posted ad is then delivered to the specified target audience. The input for this step is the optimized ad copy and the ad distribution platform's API information, and the output is the ad posted to the distribution platform.

[0538] Step 6: Measuring advertising effectiveness

[0539] The server measures the effectiveness of advertising in real time after it is posted. The data measured includes the number of impressions, click rates, conversion rates, etc. The server collects and analyzes this data. The input to this step is the advertising effectiveness data obtained from the distribution platform, and the output is the analysis results.

[0540] Step 7: Generate reports and view dashboards

[0541] The server generates a detailed report based on the advertising effectiveness. The generated report is displayed on the user's dashboard. The user can check the performance of the advertising campaign through this report. It also displays improvements and recommended strategies for the next advertising campaign. The input of this step is the analyzed advertising effectiveness data, and the output is a detailed report that is displayed on the user's dashboard.

[0542] The above are the specific processing steps and details of this system, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[0543] (Application example 1)

[0544] 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."

[0545] Small businesses need a way to easily create and effectively distribute high-quality web advertisements. However, this requires specialized advertising knowledge and expensive software, making it difficult to achieve. It is also extremely difficult to measure the effectiveness of advertisements in real time and reflect the results in the next advertising campaign. For these reasons, there is an urgent need to provide a system that allows even small businesses to easily send out high-quality, effective advertisements.

[0546] 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.

[0547] In this invention, the server includes: means for providing a form for users to input information about products or services they offer; means for analyzing the input product or service information and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information; means for automatically publishing the advertising copy to the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means configured as an application executed on a smartphone, for generating advertising copy using a natural language processing engine and publishing the advertisement using the API of the advertising distribution platform; and means for users to input product information using a smartphone and distribute the generated advertising copy. This enables small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge.

[0548] 1. "Form for entering information about products or services provided by users" means an electronic form that allows users to enter information about the products they sell or the services they provide.

[0549] 2. "Means for analyzing input product or service information and automatically generating advertising copy" refers to a system element that automatically generates advertising copy based on product or service information provided by users using a natural language processing engine or similar.

[0550] 3. "Means for optimizing generated ad copy based on target audience information" refers to a system element that optimizes generated ad copy based on information such as the gender, age, and place of residence of the target audience.

[0551] 4. "Means for automatically posting ad copy on the most appropriate ad distribution platform" refers to a function that automatically posts generated and optimized ad copy on the appropriate ad distribution platform.

[0552] 5. "Means for measuring the effectiveness of published advertisements in real time" refers to a function that collects and measures performance data such as the number of times an advertisement is displayed, click rate, and conversion rate in real time after the advertisement has been published.

[0553] 6. "Means for generating and displaying reports based on advertising effectiveness" refers to a function that generates and displays reports in a format that is easy for users to understand, based on advertising effectiveness data measured in real time.

[0554] 7. "Applications running on smartphones" means application software that runs on smartphones and allows users to input product information and generate, submit, and manage advertisements.

[0555] 8. "Means for generating advertising copy using a natural language processing engine" refers to a system element that uses natural language processing technology to automatically create effective advertising copy from product or service information provided by users.

[0556] 9. "Means for placing advertisements using the API of an advertising distribution platform" refers to a system element that automatically places generated and optimized advertising copy using the API provided by the advertising distribution platform.

[0557] 10. "Means for users to input product information using a smartphone and distribute the generated advertising copy" refers to a function that enables users to input product or service information using a smartphone and distribute advertising copy generated based on that information.

[0558] MODE FOR CARRYING OUT THE INVENTION

[0559] Specific embodiments for carrying out the present invention will be described below.

[0560] System configuration

[0561] The system includes the following hardware and software.

[0562] Hardware:

[0563] Smartphone: The device used by the user

[0564] Server: A central device that generates, optimizes, places, and measures the effectiveness of advertisements.

[0565] software:

[0566] Flask: a web framework

[0567] requests: HTTP request library

[0568] nltk: Natural Language Processing Library

[0569] Processing flow

[0570] 1. User input:

[0571] Using their smartphone, users fill out a form with the product name, description, and target audience details (e.g., age, gender, and region).

[0572] 2. Transmission and storage of information:

[0573] The entered information is sent from the smartphone to the server and stored in a database.

[0574] 3. Generating ad copy:

[0575] The server generates ad copy using the NLTK natural language processing engine. For example, if a user wants to advertise "organic green tea," the server generates ad copy such as "New organic green tea, a delicious tea perfect for health-conscious people. Order now!"

[0576] 4. Ad copy optimization:

[0577] The generated ad copy is optimized based on target audience information (e.g., women in their 20s living in urban areas). For example, casual language is used for younger audiences, while phrases that enhance trustworthiness are used for older audiences.

[0578] 5. Advertising:

[0579] The optimized ad copy is sent to the ad distribution platform's API using the requests library and is automatically published.

[0580] 6. Measuring results and displaying reports:

[0581] The effectiveness of the ads is measured in real time. The server collects data such as the number of impressions, click rates, and conversion rates, and generates reports based on this data, which are then displayed on a dashboard on the smartphone.

[0582] 7. Next strategy proposal:

[0583] Based on advertising effectiveness data, we provide users with improvements and recommended strategies for their next advertising campaign.

[0584] Specific examples

[0585] For example, if a user wants to advertise "organic green tea," they enter the following information into a form on their smartphone:

[0586] Product name: Organic Green Tea

[0587] Description: A delicious organic green tea perfect for health-conscious individuals.

[0588] Target audience: Health-conscious women in their 20s

[0589] An example of a prompt generated based on the input information:

[0590] Prompt statement:

[0591] Product Name: Organic Green Tea

[0592] Description: A delicious organic green tea perfect for health-conscious individuals.

[0593] Target audience: Health-conscious women in their 20s

[0594] The ad copy generated by the server will read, "New organic green tea, delicious tea perfect for health-conscious people. Order now!" The generated ad copy will be automatically posted to the ad distribution platform, and users will be able to check the effectiveness of the ad in real time on their smartphones.

[0595] The above is an embodiment of the present invention, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[0596] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0597] Step 1:

[0598] The user uses a smartphone to input information about the product or service. The input includes the product name, description, and target audience information (e.g., age, gender, and region). Once the input is complete, the user clicks the "Submit" button. This action sends the input information from the smartphone to the server.

[0599] input:

[0600] Product name

[0601] explanation

[0602] Target Audience Information

[0603] output:

[0604] Transmission data

[0605] Step 2:

[0606] The server parses the received data and stores it in a database, including product name, description, and target audience information. Once the process is complete, the next ad copy generation process is triggered.

[0607] input:

[0608] Transmission data

[0609] output:

[0610] Stored Data

[0611] Step 3:

[0612] The server uses the stored data to generate ad copy using the NLTK natural language processing engine, which is an attractive representation of the product information provided by the user.

[0613] input:

[0614] Stored Data

[0615] output:

[0616] Generated ad text

[0617] Step 4:

[0618] The server then optimizes the generated ad copy based on target audience information, which includes adjusting the tone and content of the ad copy based on gender, age, region, etc. For example, casual language might be used for younger audiences, while phrases that convey a sense of trust might be selected for older audiences.

[0619] input:

[0620] Generated ad text

[0621] Target Audience Information

[0622] output:

[0623] Optimized ad text

[0624] Step 5:

[0625] The server uses the API of the ad distribution platform to publish the optimized ad copy. It uses the requests library to send the necessary data to the API endpoint.

[0626] input:

[0627] Optimized ad text

[0628] output:

[0629] Confirmation of completion of posting

[0630] Step 6:

[0631] The server measures the effectiveness of the published ads in real time, obtaining data such as the number of impressions, click rates, and conversion rates from the ad distribution platform and continuously monitoring them.

[0632] input:

[0633] Ads placed

[0634] output:

[0635] Effectiveness measurement data

[0636] Step 7:

[0637] The server generates an advertising campaign effectiveness report based on the effectiveness measurement data and displays it on the user's dashboard, which the user can then view on their smartphone.

[0638] input:

[0639] Effectiveness measurement data

[0640] output:

[0641] Effectiveness Report

[0642] Step 8:

[0643] The server analyzes the data from the effectiveness report and provides users with recommendations for improvements and strategies for their next advertising campaign, enabling them to continuously carry out effective advertising operations.

[0644] input:

[0645] Effectiveness Report

[0646] output:

[0647] Improvements and recommended strategies

[0648] 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.

[0649] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. In addition, by using an emotion engine, it analyzes user emotions and reflects them in the creation and optimization of advertisements.

[0650] First, the user accesses a form on their device to enter product information and target audience details. The form has fields for entering information such as the product name, description, and target demographic (e.g., age, gender, and region). The emotion engine then recognizes and analyzes the user's emotions as they type. Once the input is complete, the user clicks the submit button.

[0651] The server then stores the information and sentiment data in a database, which is then automatically analyzed and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information and sentiment of the user.

[0652] The generated ad copy is then further optimized. The server analyzes the target audience information and also adjusts the ad copy by taking into account the user's emotional data. For example, if the user is feeling positive, it will use cheerful and positive language, and if the user is feeling cautious, it will add reassuring phrases. In this process, the target audience's attributes (gender, age, region, etc.) and the user's emotional data play an important role.

[0653] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0654] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad's effectiveness and recommended strategies for the next ad campaign. The emotion engine also influences these improvements and recommended strategies, providing advice that takes the user's emotions into consideration.

[0655] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server, along with this data, uses an emotion engine to analyze the user's emotions and generates ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-post data, keywords and phrases to use in the next advertising campaign are suggested.

[0656] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. Furthermore, by utilizing emotion data, they can implement advertising strategies that match users' emotions and maximize advertising effectiveness. Furthermore, because the effectiveness of advertisements can be grasped in real time, advertising strategies can be flexibly improved.

[0657] The above is an embodiment of the present invention.

[0658] The processing flow will be explained below.

[0659] Step 1:

[0660] User

[0661] A user accesses the system through a terminal and accesses a form to enter product information and target audience details. The form has fields for product name, description, target demographic (e.g., age, gender, region), etc. The user enters information into these fields.

[0662] Step 2:

[0663] Terminal

[0664] While the user is entering information, the emotion engine built into the device monitors the user's input behavior, facial expressions, voice, etc. to recognize emotions. For example, it can analyze the user's facial expressions and tone of voice through a camera or microphone to obtain emotional data in real time.

[0665] Step 3:

[0666] User

[0667] Once the user has completed entering all the required information, they click the send button, which sends the entered data and emotion data to the server.

[0668] Step 4:

[0669] server

[0670] The server stores the received product information, target audience data, and user emotion data in a database, after which the data analysis process begins.

[0671] Step 5:

[0672] server

[0673] The stored data is fed into a natural language processing (NLP) engine, which analyzes product and target audience information to generate ad copy. The NLP engine then selects keywords and phrases to generate more compelling ad copy.

[0674] Step 6:

[0675] server

[0676] The generated ad copy is then further optimized. The server adjusts the copy based on the target audience information to make it more effective. The user's emotional data is also taken into account here. For example, if the user is positive, it uses cheerful and positive language, and if the user is cautious, it adds phrases that emphasize trustworthiness.

[0677] Step 7:

[0678] server

[0679] The optimized ad copy is automatically published on the selected ad distribution platform. The server uses the ad distribution platform's API to place the ad.

[0680] Step 8:

[0681] server

[0682] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected to analyze ad performance.

[0683] Step 9:

[0684] server

[0685] Based on the analysis results, detailed reports are generated, including ad performance metrics and target audience responses. The sentiment engine takes user sentiment data into account and adjusts the report content.

[0686] Step 10:

[0687] User

[0688] Users can view reports provided by the server on a dashboard to check the results of their advertising campaigns, and can use the results of the reports to plan their next advertising strategy.

[0689] Step 11:

[0690] server

[0691] Based on the collected advertising effectiveness data and user sentiment data, the system provides improvements and recommended strategies for the next advertising campaign, including specific advice that takes into account the user's emotions.

[0692] Step 12:

[0693] User

[0694] The user re-enters the information for the next advertising campaign and repeats the same process to continuously optimize advertising effectiveness.

[0695] Example 2

[0696] 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."

[0697] In today's world, even small businesses are required to run efficient and effective advertising campaigns. However, systems that consistently manage everything from creating advertising copy to distribution and measuring effectiveness are expensive and require specialized knowledge, making them unaffordable for many small businesses. Furthermore, creating and effectively distributing advertisements that are optimized for user emotions and target audiences is even more difficult. These issues need to be resolved.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0699] In this invention, the server includes: means for analyzing information about products or services provided by a user and the user's emotions, and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information and user emotion data; means for automatically publishing the advertising copy on the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means for presenting improvements and recommended strategies for the next advertising campaign based on the user's emotion data; and means for using an emotion engine that simultaneously analyzes the user's input content and their emotions. This enables even small businesses to run consistently high-quality advertising campaigns without requiring specialized knowledge or high costs. It also enables the creation of advertisements optimized for the user's emotions and target audience, maximizing their effectiveness.

[0700] "User" means an individual or organization that utilizes the System to create and distribute advertising campaigns.

[0701] A "form" is an interface through which a user inputs product or service information.

[0702] "Product or Service Information" means details about the products or services you offer, including product names, descriptions, and target audience attributes (e.g., age, gender, location).

[0703] The "emotion engine" is a mechanism that analyzes the user's input and emotions.

[0704] A "natural language processing (NLP) engine" is a technology that analyzes input information and generates advertising copy in natural language.

[0705] "Ad copy" is a promotional copy automatically generated based on the information about the product or service provided by the user and the target audience.

[0706] A "target audience" is a specific group of users to whom an advertisement is intended to be delivered, and is defined by attributes such as age, gender, and region.

[0707] An "advertising distribution platform" is an online platform for distributing generated advertising copy.

[0708] An "API" (Application Programming Interface) is an interface that allows communication between an advertising distribution platform and a system.

[0709] "Effectiveness data" refers to data used to measure the effectiveness of an advertisement, such as the number of times an advertisement is displayed, click rate, and conversion rate.

[0710] "Report" means a report generated to analyze and demonstrate the effectiveness of an Advertising Campaign.

[0711] "Improvements and recommended strategies" are suggested optimizations and strategies for your next advertising campaign based on the results of your advertising campaign.

[0712] MODE FOR CARRYING OUT THE INVENTION

[0713] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. Additionally, it uses an emotion engine to analyze user emotions and reflect them in the creation and optimization of advertisements.

[0714] Hardware and software used

[0715] Terminal: A device through which a user inputs product or service information. Examples include personal computers (PCs), smartphones, and tablets.

[0716] Server: A device that stores information, analyzes it, generates and optimizes ad copy, places ads, measures their effectiveness, and generates reports. It may be a cloud server or on-premise server with high-performance data processing capabilities.

[0717] Database: A system for storing data obtained from users. A relational database (RDBMS) or a NoSQL database can be used.

[0718] Natural language processing (NLP) engine: Software for analyzing product and service information and generating advertising copy. Open source NLP libraries and commercial NLP tools are used.

[0719] Sentiment engine: Software for analyzing emotions in real time with user input, using machine learning models and sentiment analysis APIs.

[0720] Ad serving platform API: An interface for automatically placing ad copy. Includes Google Ads API, Facebook Ads API, etc.

[0721] Explaining program processing in natural language

[0722] User Input

[0723] The user accesses a dedicated form on the system using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, and region). As the user enters the information, the emotion engine analyzes the user's emotions in real time. When the user clicks the "Submit" button, the information is sent to the server.

[0724] Information storage and analysis

[0725] The server receives the information sent by the user and stores it in a database. The stored information is automatically analyzed using an NLP engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. The generated ad copy incorporates attractive keywords and phrases based on the user's emotional data analyzed by the emotion engine.

[0726] Ad copy optimization

[0727] The server then further optimizes the generated ad copy, taking into account target audience information and user sentiment data—for example, adding upbeat language if the user is expressing positive emotions, or reassuring phrases if the user is expressing caution.

[0728] Advertising and measuring effectiveness

[0729] The optimized ad copy is automatically placed via the server using the API of the ad distribution platform. Once the ad is placed, the server measures its effectiveness in real time, including data such as the number of impressions, click-through rate, and conversion rate.

[0730] Generate and view reports

[0731] The server generates a detailed report based on the effectiveness of the ads and displays it on the user's dashboard. Users can view this report through their devices to check the results of their ad campaigns. It also provides suggestions for improvements and recommended strategies for the next campaign. This allows users to maximize the effectiveness of their ads and receive useful feedback for their next campaign.

[0732] Examples of specific examples and prompts

[0733] As a specific example, consider a case where a user wants to advertise "organic green tea." The user enters the product name, features (e.g., natural, healthy), and target demographic (e.g., health-conscious women in their 20s) on their device. The emotion engine analyzes this data along with the user's emotions and generates ad copy such as "Try healthy organic green tea now!" This ad copy is automatically published on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-publication data, keywords and phrases to use in the next advertising campaign are suggested.

[0734] Example prompt sentence:

[0735] Write the name of your product, a description, and details about your target audience. Also, tell us how you feel these days and want to promote it.

[0736] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0737] Step 1: User Input

[0738] The user accesses the system's dedicated form using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, region). The entered information is simultaneously analyzed by an emotion engine to determine the user's emotions. Specifically, when the user clicks the "Submit" button, the entered data is sent to the server.

[0739] Input: Product name, product description, target demographic details, user sentiment

[0740] Output: User input data sent

[0741] Step 2: Storing information (server)

[0742] The server receives the information sent by the user. The received information is stored in a database. This information includes the product name, product description, target demographic details, and user emotion data. The server securely stores the information and then proceeds to the next analysis step.

[0743] Input: Data submitted by the user

[0744] Output: Data stored in the database

[0745] Step 3: Analyzing information and generating ad copy (server)

[0746] The server retrieves the information stored in the database. This information is then analyzed using a natural language processing (NLP) engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. Analysis data from the emotion engine is also used to add keywords and phrases based on user sentiment to the ad copy.

[0747] Input: Information retrieved from the database

[0748] Output: Generated ad copy

[0749] Step 4: Ad copy optimization (server)

[0750] The server further optimizes the generated ad copy, taking into account target audience information and user sentiment data. For example, it adds upbeat language if the user is expressing positive sentiment, or adds reassuring phrases if the user is expressing cautious sentiment.

[0751] Input: Generated ad copy, target audience information, user sentiment data

[0752] Output: Optimized ad copy

[0753] Step 5: Posting Ads (Server)

[0754] The server automatically places the optimized ad copy using the API of the ad distribution platform. The specific operation of the ad placement is that the server sends the ad copy to the platform via the API, completing the placement process.

[0755] Input: Optimized ad text

[0756] Output: Posting to ad distribution platform completed

[0757] Step 6: Measuring the results (server)

[0758] The server measures the effectiveness of the placed ads in real time. The measured data includes the number of impressions, click rates, conversion rates, etc. Effectiveness data is obtained from the ad distribution platform and analyzed to evaluate the effectiveness.

[0759] Input: Effectiveness data from advertising distribution platform

[0760] Output: Analyzed advertising effectiveness data

[0761] Step 7: Generate and view reports (server, terminal)

[0762] The server generates a detailed report based on the effectiveness of the ads, which is displayed on the user's dashboard and can be viewed via their device, along with suggestions for improvements and recommended strategies for the next campaign.

[0763] Input: Analyzed advertising effectiveness data

[0764] Output: Reports displayed on the user's dashboard, with suggestions for improvement and recommended strategies

[0765] (Application example 2)

[0766] 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."

[0767] It is extremely difficult for small businesses to create high-quality web advertisements on a daily basis and distribute them effectively due to limited expertise and resources. It is also difficult to understand the effectiveness of advertisements in real time and develop optimal advertising strategies based on emotions. For this reason, a system is needed that allows businesses to easily create advertisements, distribute them to appropriate platforms, quickly evaluate and analyze their effectiveness, and flexibly improve their strategies.

[0768] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0769] In this invention, the server includes means for providing a form for users to input information about products or services they offer, means for automatically generating advertising copy by analyzing the input product or service information and user emotion data, means for optimizing the generated advertising copy based on target audience information and user emotion data, means for automatically publishing the advertising copy to an optimal advertising distribution platform, means for measuring the effectiveness of the published advertisement in real time, means for generating and displaying a report based on the effectiveness of the advertisement, means for analyzing user emotion data, means for reflecting the emotion analysis in the generation of advertising copy, means for publishing advertisements using the API of the advertising distribution platform, and means for collecting user emotion data using a smartphone or other mobile device. This enables even small businesses to easily create high-quality advertisements, effectively publish them, measure their effectiveness in real time, and implement optimal advertising strategies using emotion data.

[0770] "Product or service information" is data related to detailed descriptions and attributes of specific products or services offered by users.

[0771] A "form" is an interface or input screen that allows a user to input information about a product or service.

[0772] "Analysis" is the process of understanding input data and extracting patterns and characteristics.

[0773] "Advertising copy" is text used to effectively promote a product or service.

[0774] A "target audience" is a specific consumer group to which an advertisement is directed.

[0775] "Emotion data" is data that includes information about the user's emotional state.

[0776] Optimization is the process of adjusting a system or process to achieve maximum effectiveness toward a specific goal.

[0777] An "advertising distribution platform" is an online service or system for displaying and distributing generated advertisements.

[0778] "Automatic posting" is the process of automatically sending the generated ad copy to a designated ad distribution platform.

[0779] "Real-time" refers to data being processed as soon as it is generated.

[0780] "Measurement" is the process of collecting and analyzing specific data or metrics.

[0781] "Report" means a document or display containing analytical results and statistical data regarding the effectiveness of an Advertising.

[0782] "Emotion analysis means" refers to techniques and functions for analyzing user emotion data.

[0783] "Means for collecting user emotional data" refers to methods or techniques for obtaining data about a user's emotional state using a smartphone or other mobile device.

[0784] "API" stands for Application Programming Interface, and is a means for mutual use of functions and data between different software programs.

[0785] This invention is a system that enables small businesses to create high-quality web advertisements using smartphones and mobile devices and maximize their effectiveness. Detailed embodiments of this system are described below.

[0786] First, this system provides a form for users to enter product or service information through a smartphone or mobile device application. Users enter information such as the product name, description, and target demographic (e.g., age, gender, and region), and simultaneously collect emotional data using a camera and microphone.

[0787] To analyze emotion data, we use the smartphone's camera and microphone and emotion analysis tools (e.g., Emotion API), which allows us to analyze the user's emotional state simultaneously with their input.

[0788] Once the data is entered, the server stores it in a database (e.g., AWS RDS). The stored data is then used to automatically generate ad copy using a natural language processing (NLP) engine (e.g., GPT-4). The generated ad copy is then further optimized based on user sentiment data and target audience information.

[0789] The generated ad copy is automatically submitted to an ad distribution platform (for example, Google Ads API or Facebook Ads API). After submission, the server measures the effectiveness of the ad (number of impressions, click-through rate, conversion rate, etc.) in real time, and generates a detailed report based on this information and displays it on the user's dashboard.

[0790] Users can view reports to check the results of their advertising campaigns and plan their next strategy. The system also provides suggestions for improvement and recommended strategies based on the effectiveness of advertising, providing advice that takes users' emotions into consideration.

[0791] As a concrete example, consider the case where a user wants to advertise a new product, "organic tea." The user enters "organic tea" as the product name and "health-conscious women in their 20s" as the target demographic in an application form, and emotional data is collected using a camera and microphone. The server analyzes this data and generates a positive ad copy such as "Try this organic tea that's good for your body now!" This ad copy is automatically posted on an ad distribution platform for young people, and its effectiveness is measured in real time.

[0792] An example of a prompt for a generative AI model is:

[0793] Product Name: Fruit Cake

[0794] Product Description: A delicious cake made with fresh fruit.

[0795] Target demographic: Young people (women in their 20s)

[0796] User Sentiment: Positive

[0797] What you should pay attention to: Fresh and healthy ingredients

[0798] Use this to generate compelling ad copy.

[0799] In this way, small businesses can easily create high-quality advertisements without specialized knowledge and flexibly maximize their effectiveness.

[0800] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0801] Step 1:

[0802] A user logs into a smartphone or mobile device application and inputs product or service information. The input information includes the product name, description, and target demographic (e.g., age, gender, and region). The camera and microphone are also used to collect user emotion data.

[0803] Input: Product name, description, target demographic, sentiment data

[0804] Output: Input information and emotion data

[0805] Step 2:

[0806] The terminal sends the collected data to the server. The server receives this data and stores it in a database (e.g., AWS RDS). Here, we check that the data is stored correctly.

[0807] Input: Input information and emotion data

[0808] Output: Data stored in the database

[0809] Step 3:

[0810] The server analyzes the stored data and uses a natural language processing (NLP) engine (e.g., GPT-4) to automatically generate ad copy based on the input information (product name, description, target demographic).

[0811] Input: Data stored in the database

[0812] Output: Auto-generated ad text

[0813] Step 4:

[0814] The server optimizes the generated ad copy based on the target user's emotional data and target audience information. For example, if the emotional data is positive, it uses upbeat and positive language, and if the emotional data is cautious, it adds reassuring phrases.

[0815] Input: ad copy, sentiment data, target audience information

[0816] Output: Optimized ad text

[0817] Step 5:

[0818] The server automatically posts the optimized ad copy using the API of the specified ad distribution platform (for example, Google Ads API or Facebook Ads API). When posting, the ad copy is adjusted to fit the terms and format of each platform.

[0819] Input: Optimized ad text

[0820] Output: Ads posted to ad serving platforms

[0821] Step 6:

[0822] The server measures the effectiveness of the advertisement (number of impressions, click rate, conversion rate) in real time after it is posted. The measured data is then saved in the database.

[0823] Input: Advertising effectiveness data

[0824] Output: Advertising effectiveness data stored in a database

[0825] Step 7:

[0826] The server generates detailed reports based on the advertising effectiveness data, which are displayed on the user's dashboard, allowing the user to check the performance of their advertising campaigns and plan their next strategy.

[0827] Input: Advertising effectiveness data stored in the database

[0828] Output: The report that appears on the user's dashboard

[0829] Step 8:

[0830] The server further calculates keywords and phrases to be used in the next advertising campaign, as well as areas for improvement and recommended strategies, based on the advertising effectiveness data and user emotion data, and provides these to the user.

[0831] Input: Advertising effectiveness data, emotion data

[0832] Output: Areas for improvement and recommended strategies

[0833] 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.

[0834] 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.

[0835] 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.

[0836] [Third embodiment]

[0837] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0838] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0839] 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).

[0840] 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.

[0841] 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.

[0842] 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).

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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."

[0849] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertising copy, and automatically posts the advertisements on the most suitable advertising distribution platform.

[0850] First, a form is displayed on the device for the user to enter information about the product or service. The form has fields for entering the product name, description, and target audience information (gender, age, region, etc.). The user enters detailed information about their product or service in these fields and clicks the submit button.

[0851] The server then stores the information in a database, which automatically analyzes it and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information the user provided.

[0852] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. Data such as gender, age, and location play an important role in this process. For example, casual language may be used for younger audiences, while phrases that convey a sense of trust may be selected for older audiences.

[0853] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0854] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0855] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server analyzes this data and generates an ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the data after posting, keywords and phrases to use in the next advertising campaign are suggested.

[0856] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, they can grasp the effectiveness of their advertisements in real time, allowing them to flexibly improve their advertising strategies.

[0857] The above is an embodiment of the present invention.

[0858] The processing flow will be explained below.

[0859] Step 1:

[0860] User

[0861] The user accesses a form through their device to enter product information and target audience details, including the product name, description, target demographic (e.g., age, gender, region), etc. Once completed, they click the submit button.

[0862] Step 2:

[0863] server

[0864] When the user clicks the submit button, the input data is received and saved in a database. At this point, the input data includes the product name, description, and target audience details.

[0865] Step 3:

[0866] server

[0867] The server then runs a natural language processing (NLP) engine based on the stored data. The server analyzes product and target audience information and automatically generates ad copy, which includes keywords and phrases to enhance marketing effectiveness.

[0868] Step 4:

[0869] server

[0870] The generated ad copy is optimized based on target audience information. Attributes such as gender, age, and region are taken into account to adjust the ad copy for maximum effectiveness. For example, trendy wording is used for younger demographics, while phrases emphasizing trustworthiness are added for older demographics.

[0871] Step 5:

[0872] server

[0873] The optimized ad copy is then published to the appropriate ad distribution platform. The server automatically publishes the ad using the API of the selected platform (e.g., Facebook, Instagram, Google Ads).

[0874] Step 6:

[0875] server

[0876] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected and analyzed. This data is used to optimize ad delivery in the future.

[0877] Step 7:

[0878] server

[0879] Generate detailed reports based on the collected advertising effectiveness data, including advertising performance metrics (e.g., CTR, CPC, ROI) and target audience responses.

[0880] Step 8:

[0881] User

[0882] Users can view reports provided by the server on a dashboard, and can use the report content to consider strategies for their next advertising campaign.

[0883] Step 9:

[0884] server

[0885] Furthermore, it automatically suggests improvements and recommended strategies for the next advertising campaign based on advertising effectiveness, which users can use to improve their advertising strategies.

[0886] Step 10:

[0887] User

[0888] By entering information for your next advertising campaign and repeating the same process, you can continuously optimize your advertising effectiveness.

[0889] Example 1

[0890] 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."

[0891] For small businesses to easily create and distribute high-quality web advertisements requires a great deal of expertise and time. Furthermore, they have limited tools and resources to understand the effectiveness of their advertisements in real time and flexibly improve their strategies. To address these challenges, there is a need for a system that allows businesses to easily create high-quality advertisements without specialized knowledge, and monitor and improve their effectiveness in real time.

[0892] 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.

[0893] In this invention, the server includes means for providing a form including fields for users to input information about products or services they offer, means for saving the input product or service information in a database, means for analyzing the saved information using a natural language processing engine and automatically generating advertising copy, means for optimizing the generated advertising copy based on target audience information, means for automatically publishing the optimized advertising copy using an advertising distribution platform's API, means for measuring the number of impressions, click-through rates, and conversion rates of published advertisements in real time, and means for generating detailed reports based on the effectiveness of the advertisements and displaying them on a dashboard. This enables even small businesses without specialized knowledge to easily create and publish high-quality advertisements, understand their effectiveness in real time, and flexibly improve their advertising strategies.

[0894] A "form" is a screen display containing multiple fields for a user to enter product or service information.

[0895] "Database" means a digital storage system for storing product or service information entered by users.

[0896] A "natural language processing engine" is a software technology that analyzes input sentences and text information to generate sentences and perform semantic analysis.

[0897] "Ad copy" refers to a text message that introduces the product or service you offer and appeals to your target audience.

[0898] A "target audience" is a group of people with specific attributes to whom advertising is intentionally directed, such as people of a particular gender, age, location, etc.

[0899] "Optimization" refers to the process of adjusting generated ad copy based on target audience information to make it more effective.

[0900] An "advertising distribution platform" is an online system that distributes generated advertising copy and delivers it to many users.

[0901] An "API (Application Programming Interface)" is a set of definitions and protocols that allow different software systems to communicate with each other.

[0902] "Impressions" refers to the total number of times an advertisement is displayed on a user's screen.

[0903] "Click-through rate" refers to the percentage of users who click on an ad compared to the number of times it is displayed.

[0904] A "conversion rate" is the percentage of users who click on an ad and then actually take a specific action, such as purchasing a product or using a service.

[0905] A "report" is a written or digital output that provides a detailed analysis of the effectiveness of advertising and summarizes the results in an easy-to-understand format.

[0906] "Dashboard" means an interface that allows users to access the system's management screen and check advertising effectiveness and other important information in real time.

[0907] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically posts the advertisements on the most suitable advertisement distribution platform.

[0908] System configuration

[0909] User Input

[0910] The device displays a form for the user to enter product or service information. The form contains the following fields:

[0911] Product name

[0912] Product Description

[0913] Target audience information (gender, age, region, etc.)

[0914] The user enters the required information into these fields and clicks the submit button, which sends the information to the server.

[0915] Data storage and analysis

[0916] The server stores the received information in a database, where it is analyzed using a natural language processing (NLP) engine to automatically generate ad copy, which includes attractive keywords and phrases based on the information provided by the user.

[0917] Ad copy optimization

[0918] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. For example, ad copy aimed at younger audiences might use casual language, while phrases that exude trustworthiness might be selected for older audiences.

[0919] Automatic ad placement

[0920] The optimized ad copy is automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[0921] Report generation and dashboard viewing

[0922] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[0923] Specific examples

[0924] For example, consider a case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, its features (e.g., "healthy, made with organic ingredients"), and the target demographic (health-conscious women in their 20s) into a form.

[0925] The server then parses this data and generates ad copy like this:

[0926] "Try our healthy organic green tea now!"

[0927] The server then optimizes the ad copy for the target audience and automatically places it on platforms like Instagram, a platform for young people.The server then measures the number of impressions, click-through rates, conversion rates, and other data in real time, generating detailed reports that are displayed on the user's dashboard.

[0928] Prompt Sentence Examples

[0929] An example of a prompt to input to a generative AI model is as follows:

[0930] Please generate advertising copy promoting our new product, "Organic Green Tea," aimed at health-conscious women in their 20s. Please clearly state the product name and its features (healthy, uses organic ingredients), and use language that will resonate with the target audience.

[0931] This system allows small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, the effectiveness of advertisements can be monitored in real time, allowing for flexible improvements to advertising strategies.

[0932] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0933] Step 1: Enter your information

[0934] The terminal displays a form for the user to enter product or service information. The form contains fields for entering the product name, product description, and target audience information (gender, age, region, etc.). The user enters the required information in these fields and clicks the submit button. The input for this step is the product or service information entered by the user in the form, and the output is the user-entered data that is sent to the server.

[0935] Step 2: Save your data

[0936] The server receives the information sent by the user. The server saves the entered information in a database. The input of this step is the product or service information sent by the user, and the output is the user information saved in the database.

[0937] Step 3: Analyze the data and generate ad copy

[0938] The server retrieves user information from a database and analyzes it using a natural language processing (NLP) engine. The server generates ad copy based on the input information. This ad copy contains attractive keywords and phrases based on the information the user provided. The input for this step is the user information stored in the database, and the output is the generated ad copy.

[0939] Step 4: Optimize your ad copy

[0940] The server optimizes the generated ad copy based on target audience information. The server analyzes data such as the target audience's gender, age, and region and adjusts the ad copy. For example, it selects casual language for younger demographics and phrases that convey trustworthiness for older demographics. The input for this step is the generated ad copy and target audience information, and the output is the optimized ad copy.

[0941] Step 5: Automated Ad Placement

[0942] The server automatically posts the optimized ad copy to the ad distribution platform. The server then uses the ad distribution platform's API to send the ad. The posted ad is then delivered to the specified target audience. The input for this step is the optimized ad copy and the ad distribution platform's API information, and the output is the ad posted to the distribution platform.

[0943] Step 6: Measuring advertising effectiveness

[0944] The server measures the effectiveness of advertising in real time after it is posted. The data measured includes the number of impressions, click rates, conversion rates, etc. The server collects and analyzes this data. The input to this step is the advertising effectiveness data obtained from the distribution platform, and the output is the analysis results.

[0945] Step 7: Generate reports and view dashboards

[0946] The server generates a detailed report based on the advertising effectiveness. The generated report is displayed on the user's dashboard. The user can check the performance of the advertising campaign through this report. It also displays improvements and recommended strategies for the next advertising campaign. The input of this step is the analyzed advertising effectiveness data, and the output is a detailed report that is displayed on the user's dashboard.

[0947] The above are the specific processing steps and details of this system, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[0948] (Application example 1)

[0949] 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."

[0950] Small businesses need a way to easily create and effectively distribute high-quality web advertisements. However, this requires specialized advertising knowledge and expensive software, making it difficult to achieve. It is also extremely difficult to measure the effectiveness of advertisements in real time and reflect the results in the next advertising campaign. For these reasons, there is an urgent need to provide a system that allows even small businesses to easily send out high-quality, effective advertisements.

[0951] 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.

[0952] In this invention, the server includes: means for providing a form for users to input information about products or services they offer; means for analyzing the input product or service information and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information; means for automatically publishing the advertising copy to the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means configured as an application executed on a smartphone, for generating advertising copy using a natural language processing engine and publishing the advertisement using the API of the advertising distribution platform; and means for users to input product information using a smartphone and distribute the generated advertising copy. This enables small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge.

[0953] 1. "Form for entering information about products or services provided by users" means an electronic form that allows users to enter information about the products they sell or the services they provide.

[0954] 2. "Means for analyzing input product or service information and automatically generating advertising copy" refers to a system element that automatically generates advertising copy based on product or service information provided by users using a natural language processing engine or similar.

[0955] 3. "Means for optimizing generated ad copy based on target audience information" refers to a system element that optimizes generated ad copy based on information such as the gender, age, and place of residence of the target audience.

[0956] 4. "Means for automatically posting ad copy on the most appropriate ad distribution platform" refers to a function that automatically posts generated and optimized ad copy on the appropriate ad distribution platform.

[0957] 5. "Means for measuring the effectiveness of published advertisements in real time" refers to a function that collects and measures performance data such as the number of times an advertisement is displayed, click rate, and conversion rate in real time after the advertisement has been published.

[0958] 6. "Means for generating and displaying reports based on advertising effectiveness" refers to a function that generates and displays reports in a format that is easy for users to understand, based on advertising effectiveness data measured in real time.

[0959] 7. "Applications running on smartphones" means application software that runs on smartphones and allows users to input product information and generate, submit, and manage advertisements.

[0960] 8. "Means for generating advertising copy using a natural language processing engine" refers to a system element that uses natural language processing technology to automatically create effective advertising copy from product or service information provided by users.

[0961] 9. "Means for placing advertisements using the API of an advertising distribution platform" refers to a system element that automatically places generated and optimized advertising copy using the API provided by the advertising distribution platform.

[0962] 10. "Means for users to input product information using a smartphone and distribute the generated advertising copy" refers to a function that enables users to input product or service information using a smartphone and distribute advertising copy generated based on that information.

[0963] MODE FOR CARRYING OUT THE INVENTION

[0964] Specific embodiments for carrying out the present invention will be described below.

[0965] System configuration

[0966] The system includes the following hardware and software.

[0967] Hardware:

[0968] Smartphone: The device used by the user

[0969] Server: A central device that generates, optimizes, places, and measures the effectiveness of advertisements.

[0970] software:

[0971] Flask: a web framework

[0972] requests: HTTP request library

[0973] nltk: Natural Language Processing Library

[0974] Processing flow

[0975] 1. User input:

[0976] Using their smartphone, users fill out a form with the product name, description, and target audience details (e.g., age, gender, and region).

[0977] 2. Transmission and storage of information:

[0978] The entered information is sent from the smartphone to the server and stored in a database.

[0979] 3. Generating ad copy:

[0980] The server generates ad copy using the NLTK natural language processing engine. For example, if a user wants to advertise "organic green tea," the server generates ad copy such as "New organic green tea, a delicious tea perfect for health-conscious people. Order now!"

[0981] 4. Ad copy optimization:

[0982] The generated ad copy is optimized based on target audience information (e.g., women in their 20s living in urban areas). For example, casual language is used for younger audiences, while phrases that enhance trustworthiness are used for older audiences.

[0983] 5. Advertising:

[0984] The optimized ad copy is sent to the ad distribution platform's API using the requests library and is automatically published.

[0985] 6. Measuring results and displaying reports:

[0986] The effectiveness of the ads is measured in real time. The server collects data such as the number of impressions, click rates, and conversion rates, and generates reports based on this data, which are then displayed on a dashboard on the smartphone.

[0987] 7. Next strategy proposal:

[0988] Based on advertising effectiveness data, we provide users with improvements and recommended strategies for their next advertising campaign.

[0989] Specific examples

[0990] For example, if a user wants to advertise "organic green tea," they enter the following information into a form on their smartphone:

[0991] Product name: Organic Green Tea

[0992] Description: A delicious organic green tea perfect for health-conscious individuals.

[0993] Target audience: Health-conscious women in their 20s

[0994] An example of a prompt generated based on the input information:

[0995] Prompt statement:

[0996] Product Name: Organic Green Tea

[0997] Description: A delicious organic green tea perfect for health-conscious individuals.

[0998] Target audience: Health-conscious women in their 20s

[0999] The ad copy generated by the server will read, "New organic green tea, delicious tea perfect for health-conscious people. Order now!" The generated ad copy will be automatically posted to the ad distribution platform, and users will be able to check the effectiveness of the ad in real time on their smartphones.

[1000] The above is an embodiment of the present invention, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[1001] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1002] Step 1:

[1003] The user uses a smartphone to input information about the product or service. The input includes the product name, description, and target audience information (e.g., age, gender, and region). Once the input is complete, the user clicks the "Submit" button. This action sends the input information from the smartphone to the server.

[1004] input:

[1005] Product name

[1006] explanation

[1007] Target Audience Information

[1008] output:

[1009] Transmission data

[1010] Step 2:

[1011] The server parses the received data and stores it in a database, including product name, description, and target audience information. Once the process is complete, the next ad copy generation process is triggered.

[1012] input:

[1013] Transmission data

[1014] output:

[1015] Stored Data

[1016] Step 3:

[1017] The server uses the stored data to generate ad copy using the NLTK natural language processing engine, which is an attractive representation of the product information provided by the user.

[1018] input:

[1019] Stored Data

[1020] output:

[1021] Generated ad text

[1022] Step 4:

[1023] The server then optimizes the generated ad copy based on target audience information, which includes adjusting the tone and content of the ad copy based on gender, age, region, etc. For example, casual language might be used for younger audiences, while phrases that convey a sense of trust might be selected for older audiences.

[1024] input:

[1025] Generated ad text

[1026] Target Audience Information

[1027] output:

[1028] Optimized ad text

[1029] Step 5:

[1030] The server uses the API of the ad distribution platform to publish the optimized ad copy. It uses the requests library to send the necessary data to the API endpoint.

[1031] input:

[1032] Optimized ad text

[1033] output:

[1034] Confirmation of completion of posting

[1035] Step 6:

[1036] The server measures the effectiveness of the published ads in real time, obtaining data such as the number of impressions, click rates, and conversion rates from the ad distribution platform and continuously monitoring them.

[1037] input:

[1038] Ads placed

[1039] output:

[1040] Effectiveness measurement data

[1041] Step 7:

[1042] The server generates an advertising campaign effectiveness report based on the effectiveness measurement data and displays it on the user's dashboard, which the user can then view on their smartphone.

[1043] input:

[1044] Effectiveness measurement data

[1045] output:

[1046] Effectiveness Report

[1047] Step 8:

[1048] The server analyzes the data from the effectiveness report and provides users with recommendations for improvements and strategies for their next advertising campaign, enabling them to continuously carry out effective advertising operations.

[1049] input:

[1050] Effectiveness Report

[1051] output:

[1052] Improvements and recommended strategies

[1053] 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.

[1054] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. In addition, by using an emotion engine, it analyzes user emotions and reflects them in the creation and optimization of advertisements.

[1055] First, the user accesses a form on their device to enter product information and target audience details. The form has fields for entering information such as the product name, description, and target demographic (e.g., age, gender, and region). The emotion engine then recognizes and analyzes the user's emotions as they type. Once the input is complete, the user clicks the submit button.

[1056] The server then stores the information and sentiment data in a database, which is then automatically analyzed and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information and sentiment of the user.

[1057] The generated ad copy is then further optimized. The server analyzes the target audience information and also adjusts the ad copy by taking into account the user's emotional data. For example, if the user is feeling positive, it will use cheerful and positive language, and if the user is feeling cautious, it will add reassuring phrases. In this process, the target audience's attributes (gender, age, region, etc.) and the user's emotional data play an important role.

[1058] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[1059] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad's effectiveness and recommended strategies for the next ad campaign. The emotion engine also influences these improvements and recommended strategies, providing advice that takes the user's emotions into consideration.

[1060] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server, along with this data, uses an emotion engine to analyze the user's emotions and generates ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-post data, keywords and phrases to use in the next advertising campaign are suggested.

[1061] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. Furthermore, by utilizing emotion data, they can implement advertising strategies that match users' emotions and maximize advertising effectiveness. Furthermore, because the effectiveness of advertisements can be grasped in real time, advertising strategies can be flexibly improved.

[1062] The above is an embodiment of the present invention.

[1063] The processing flow will be explained below.

[1064] Step 1:

[1065] User

[1066] A user accesses the system through a terminal and accesses a form to enter product information and target audience details. The form has fields for product name, description, target demographic (e.g., age, gender, region), etc. The user enters information into these fields.

[1067] Step 2:

[1068] Terminal

[1069] While the user is entering information, the emotion engine built into the device monitors the user's input behavior, facial expressions, voice, etc. to recognize emotions. For example, it can analyze the user's facial expressions and tone of voice through a camera or microphone to obtain emotional data in real time.

[1070] Step 3:

[1071] User

[1072] Once the user has completed entering all the required information, they click the send button, which sends the entered data and emotion data to the server.

[1073] Step 4:

[1074] server

[1075] The server stores the received product information, target audience data, and user emotion data in a database, after which the data analysis process begins.

[1076] Step 5:

[1077] server

[1078] The stored data is fed into a natural language processing (NLP) engine, which analyzes product and target audience information to generate ad copy. The NLP engine then selects keywords and phrases to generate more compelling ad copy.

[1079] Step 6:

[1080] server

[1081] The generated ad copy is then further optimized. The server adjusts the copy based on the target audience information to make it more effective. The user's emotional data is also taken into account here. For example, if the user is positive, it uses cheerful and positive language, and if the user is cautious, it adds phrases that emphasize trustworthiness.

[1082] Step 7:

[1083] server

[1084] The optimized ad copy is automatically published on the selected ad distribution platform. The server uses the ad distribution platform's API to place the ad.

[1085] Step 8:

[1086] server

[1087] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected to analyze ad performance.

[1088] Step 9:

[1089] server

[1090] Based on the analysis results, detailed reports are generated, including ad performance metrics and target audience responses. The sentiment engine takes user sentiment data into account and adjusts the report content.

[1091] Step 10:

[1092] User

[1093] Users can view reports provided by the server on a dashboard to check the results of their advertising campaigns, and can use the results of the reports to plan their next advertising strategy.

[1094] Step 11:

[1095] server

[1096] Based on the collected advertising effectiveness data and user sentiment data, the system provides improvements and recommended strategies for the next advertising campaign, including specific advice that takes into account the user's emotions.

[1097] Step 12:

[1098] User

[1099] The user re-enters the information for the next advertising campaign and repeats the same process to continuously optimize advertising effectiveness.

[1100] Example 2

[1101] 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."

[1102] In today's world, even small businesses are required to run efficient and effective advertising campaigns. However, systems that consistently manage everything from creating advertising copy to distribution and measuring effectiveness are expensive and require specialized knowledge, making them unaffordable for many small businesses. Furthermore, creating and effectively distributing advertisements that are optimized for user emotions and target audiences is even more difficult. These issues need to be resolved.

[1103] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1104] In this invention, the server includes: means for analyzing information about products or services provided by a user and the user's emotions, and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information and user emotion data; means for automatically publishing the advertising copy on the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means for presenting improvements and recommended strategies for the next advertising campaign based on the user's emotion data; and means for using an emotion engine that simultaneously analyzes the user's input content and their emotions. This enables even small businesses to run consistently high-quality advertising campaigns without requiring specialized knowledge or high costs. It also enables the creation of advertisements optimized for the user's emotions and target audience, maximizing their effectiveness.

[1105] "User" means an individual or organization that utilizes the System to create and distribute advertising campaigns.

[1106] A "form" is an interface through which a user inputs product or service information.

[1107] "Product or Service Information" means details about the products or services you offer, including product names, descriptions, and target audience attributes (e.g., age, gender, location).

[1108] The "emotion engine" is a mechanism that analyzes the user's input and emotions.

[1109] A "natural language processing (NLP) engine" is a technology that analyzes input information and generates advertising copy in natural language.

[1110] "Ad copy" is a promotional copy automatically generated based on the information about the product or service provided by the user and the target audience.

[1111] A "target audience" is a specific group of users to whom an advertisement is intended to be delivered, and is defined by attributes such as age, gender, and region.

[1112] An "advertising distribution platform" is an online platform for distributing generated advertising copy.

[1113] An "API" (Application Programming Interface) is an interface that allows communication between an advertising distribution platform and a system.

[1114] "Effectiveness data" refers to data used to measure the effectiveness of an advertisement, such as the number of times an advertisement is displayed, click rate, and conversion rate.

[1115] "Report" means a report generated to analyze and demonstrate the effectiveness of an Advertising Campaign.

[1116] "Improvements and recommended strategies" are suggested optimizations and strategies for your next advertising campaign based on the results of your advertising campaign.

[1117] MODE FOR CARRYING OUT THE INVENTION

[1118] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. Additionally, it uses an emotion engine to analyze user emotions and reflect them in the creation and optimization of advertisements.

[1119] Hardware and software used

[1120] Terminal: A device through which a user inputs product or service information. Examples include personal computers (PCs), smartphones, and tablets.

[1121] Server: A device that stores information, analyzes it, generates and optimizes ad copy, places ads, measures their effectiveness, and generates reports. It may be a cloud server or on-premise server with high-performance data processing capabilities.

[1122] Database: A system for storing data obtained from users. A relational database (RDBMS) or a NoSQL database can be used.

[1123] Natural language processing (NLP) engine: Software for analyzing product and service information and generating advertising copy. Open source NLP libraries and commercial NLP tools are used.

[1124] Sentiment engine: Software for analyzing emotions in real time with user input, using machine learning models and sentiment analysis APIs.

[1125] Ad serving platform API: An interface for automatically placing ad copy. Includes Google Ads API, Facebook Ads API, etc.

[1126] Explaining program processing in natural language

[1127] User Input

[1128] The user accesses a dedicated form on the system using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, and region). As the user enters the information, the emotion engine analyzes the user's emotions in real time. When the user clicks the "Submit" button, the information is sent to the server.

[1129] Information storage and analysis

[1130] The server receives the information sent by the user and stores it in a database. The stored information is automatically analyzed using an NLP engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. The generated ad copy incorporates attractive keywords and phrases based on the user's emotional data analyzed by the emotion engine.

[1131] Ad copy optimization

[1132] The server then further optimizes the generated ad copy, taking into account target audience information and user sentiment data—for example, adding upbeat language if the user is expressing positive emotions, or reassuring phrases if the user is expressing caution.

[1133] Advertising and measuring effectiveness

[1134] The optimized ad copy is automatically placed via the server using the API of the ad distribution platform. Once the ad is placed, the server measures its effectiveness in real time, including data such as the number of impressions, click-through rate, and conversion rate.

[1135] Generate and view reports

[1136] The server generates a detailed report based on the effectiveness of the ads and displays it on the user's dashboard. Users can view this report through their devices to check the results of their ad campaigns. It also provides suggestions for improvements and recommended strategies for the next campaign. This allows users to maximize the effectiveness of their ads and receive useful feedback for their next campaign.

[1137] Examples of specific examples and prompts

[1138] As a specific example, consider a case where a user wants to advertise "organic green tea." The user enters the product name, features (e.g., natural, healthy), and target demographic (e.g., health-conscious women in their 20s) on their device. The emotion engine analyzes this data along with the user's emotions and generates ad copy such as "Try healthy organic green tea now!" This ad copy is automatically published on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-publication data, keywords and phrases to use in the next advertising campaign are suggested.

[1139] Example prompt sentence:

[1140] Write the name of your product, a description, and details about your target audience. Also, tell us how you feel these days and want to promote it.

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1: User Input

[1143] The user accesses the system's dedicated form using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, region). The entered information is simultaneously analyzed by an emotion engine to determine the user's emotions. Specifically, when the user clicks the "Submit" button, the entered data is sent to the server.

[1144] Input: Product name, product description, target demographic details, user sentiment

[1145] Output: User input data sent

[1146] Step 2: Storing information (server)

[1147] The server receives the information sent by the user. The received information is stored in a database. This information includes the product name, product description, target demographic details, and user emotion data. The server securely stores the information and then proceeds to the next analysis step.

[1148] Input: Data submitted by the user

[1149] Output: Data stored in the database

[1150] Step 3: Analyzing information and generating ad copy (server)

[1151] The server retrieves the information stored in the database. This information is then analyzed using a natural language processing (NLP) engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. Analysis data from the emotion engine is also used to add keywords and phrases based on user sentiment to the ad copy.

[1152] Input: Information retrieved from the database

[1153] Output: Generated ad copy

[1154] Step 4: Ad copy optimization (server)

[1155] The server further optimizes the generated ad copy, taking into account target audience information and user sentiment data. For example, it adds upbeat language if the user is expressing positive sentiment, or adds reassuring phrases if the user is expressing cautious sentiment.

[1156] Input: Generated ad copy, target audience information, user sentiment data

[1157] Output: Optimized ad copy

[1158] Step 5: Posting Ads (Server)

[1159] The server automatically places the optimized ad copy using the API of the ad distribution platform. The specific operation of the ad placement is that the server sends the ad copy to the platform via the API, completing the placement process.

[1160] Input: Optimized ad text

[1161] Output: Posting to ad distribution platform completed

[1162] Step 6: Measuring the results (server)

[1163] The server measures the effectiveness of the placed ads in real time. The measured data includes the number of impressions, click rates, conversion rates, etc. Effectiveness data is obtained from the ad distribution platform and analyzed to evaluate the effectiveness.

[1164] Input: Effectiveness data from advertising distribution platform

[1165] Output: Analyzed advertising effectiveness data

[1166] Step 7: Generate and view reports (server, terminal)

[1167] The server generates a detailed report based on the effectiveness of the ads, which is displayed on the user's dashboard and can be viewed via their device, along with suggestions for improvements and recommended strategies for the next campaign.

[1168] Input: Analyzed advertising effectiveness data

[1169] Output: Reports displayed on the user's dashboard, with suggestions for improvement and recommended strategies

[1170] (Application example 2)

[1171] 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."

[1172] It is extremely difficult for small businesses to create high-quality web advertisements on a daily basis and distribute them effectively due to limited expertise and resources. It is also difficult to understand the effectiveness of advertisements in real time and develop optimal advertising strategies based on emotions. For this reason, a system is needed that allows businesses to easily create advertisements, distribute them to appropriate platforms, quickly evaluate and analyze their effectiveness, and flexibly improve their strategies.

[1173] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1174] In this invention, the server includes means for providing a form for users to input information about products or services they offer, means for automatically generating advertising copy by analyzing the input product or service information and user emotion data, means for optimizing the generated advertising copy based on target audience information and user emotion data, means for automatically publishing the advertising copy to an optimal advertising distribution platform, means for measuring the effectiveness of the published advertisement in real time, means for generating and displaying a report based on the effectiveness of the advertisement, means for analyzing user emotion data, means for reflecting the emotion analysis in the generation of advertising copy, means for publishing advertisements using the API of the advertising distribution platform, and means for collecting user emotion data using a smartphone or other mobile device. This enables even small businesses to easily create high-quality advertisements, effectively publish them, measure their effectiveness in real time, and implement optimal advertising strategies using emotion data.

[1175] "Product or service information" is data related to detailed descriptions and attributes of specific products or services offered by users.

[1176] A "form" is an interface or input screen that allows a user to input information about a product or service.

[1177] "Analysis" is the process of understanding input data and extracting patterns and characteristics.

[1178] "Advertising copy" is text used to effectively promote a product or service.

[1179] A "target audience" is a specific consumer group to which an advertisement is directed.

[1180] "Emotion data" is data that includes information about the user's emotional state.

[1181] Optimization is the process of adjusting a system or process to achieve maximum effectiveness toward a specific goal.

[1182] An "advertising distribution platform" is an online service or system for displaying and distributing generated advertisements.

[1183] "Automatic posting" is the process of automatically sending the generated ad copy to a designated ad distribution platform.

[1184] "Real-time" refers to data being processed as soon as it is generated.

[1185] "Measurement" is the process of collecting and analyzing specific data or metrics.

[1186] "Report" means a document or display containing analytical results and statistical data regarding the effectiveness of an Advertising.

[1187] "Emotion analysis means" refers to techniques and functions for analyzing user emotion data.

[1188] "Means for collecting user emotional data" refers to methods or techniques for obtaining data about a user's emotional state using a smartphone or other mobile device.

[1189] "API" stands for Application Programming Interface, and is a means for mutual use of functions and data between different software programs.

[1190] This invention is a system that enables small businesses to create high-quality web advertisements using smartphones and mobile devices and maximize their effectiveness. Detailed embodiments of this system are described below.

[1191] First, this system provides a form for users to enter product or service information through a smartphone or mobile device application. Users enter information such as the product name, description, and target demographic (e.g., age, gender, and region), and simultaneously collect emotional data using a camera and microphone.

[1192] To analyze emotion data, we use the smartphone's camera and microphone and emotion analysis tools (e.g., Emotion API), which allows us to analyze the user's emotional state simultaneously with their input.

[1193] Once the data is entered, the server stores it in a database (e.g., AWS RDS). The stored data is then used to automatically generate ad copy using a natural language processing (NLP) engine (e.g., GPT-4). The generated ad copy is then further optimized based on user sentiment data and target audience information.

[1194] The generated ad copy is automatically submitted to an ad distribution platform (for example, Google Ads API or Facebook Ads API). After submission, the server measures the effectiveness of the ad (number of impressions, click-through rate, conversion rate, etc.) in real time, and generates a detailed report based on this information and displays it on the user's dashboard.

[1195] Users can view reports to check the results of their advertising campaigns and plan their next strategy. The system also provides suggestions for improvement and recommended strategies based on the effectiveness of advertising, providing advice that takes users' emotions into consideration.

[1196] As a concrete example, consider the case where a user wants to advertise a new product, "organic tea." The user enters "organic tea" as the product name and "health-conscious women in their 20s" as the target demographic in an application form, and emotional data is collected using a camera and microphone. The server analyzes this data and generates a positive ad copy such as "Try this organic tea that's good for your body now!" This ad copy is automatically posted on an ad distribution platform for young people, and its effectiveness is measured in real time.

[1197] An example of a prompt for a generative AI model is:

[1198] Product Name: Fruit Cake

[1199] Product Description: A delicious cake made with fresh fruit.

[1200] Target demographic: Young people (women in their 20s)

[1201] User Sentiment: Positive

[1202] What you should pay attention to: Fresh and healthy ingredients

[1203] Use this to generate compelling ad copy.

[1204] In this way, small businesses can easily create high-quality advertisements without specialized knowledge and flexibly maximize their effectiveness.

[1205] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1206] Step 1:

[1207] A user logs into a smartphone or mobile device application and inputs product or service information. The input information includes the product name, description, and target demographic (e.g., age, gender, and region). The camera and microphone are also used to collect user emotion data.

[1208] Input: Product name, description, target demographic, sentiment data

[1209] Output: Input information and emotion data

[1210] Step 2:

[1211] The terminal sends the collected data to the server. The server receives this data and stores it in a database (e.g., AWS RDS). Here, we check that the data is stored correctly.

[1212] Input: Input information and emotion data

[1213] Output: Data stored in the database

[1214] Step 3:

[1215] The server analyzes the stored data and uses a natural language processing (NLP) engine (e.g., GPT-4) to automatically generate ad copy based on the input information (product name, description, target demographic).

[1216] Input: Data stored in the database

[1217] Output: Auto-generated ad text

[1218] Step 4:

[1219] The server optimizes the generated ad copy based on the target user's emotional data and target audience information. For example, if the emotional data is positive, it uses upbeat and positive language, and if the emotional data is cautious, it adds reassuring phrases.

[1220] Input: ad copy, sentiment data, target audience information

[1221] Output: Optimized ad text

[1222] Step 5:

[1223] The server automatically posts the optimized ad copy using the API of the specified ad distribution platform (for example, Google Ads API or Facebook Ads API). When posting, the ad copy is adjusted to fit the terms and format of each platform.

[1224] Input: Optimized ad text

[1225] Output: Ads posted to ad serving platforms

[1226] Step 6:

[1227] The server measures the effectiveness of the advertisement (number of impressions, click rate, conversion rate) in real time after it is posted. The measured data is then saved in the database.

[1228] Input: Advertising effectiveness data

[1229] Output: Advertising effectiveness data stored in a database

[1230] Step 7:

[1231] The server generates detailed reports based on the advertising effectiveness data, which are displayed on the user's dashboard, allowing the user to check the performance of their advertising campaigns and plan their next strategy.

[1232] Input: Advertising effectiveness data stored in the database

[1233] Output: The report that appears on the user's dashboard

[1234] Step 8:

[1235] The server further calculates keywords and phrases to be used in the next advertising campaign, as well as areas for improvement and recommended strategies, based on the advertising effectiveness data and user emotion data, and provides these to the user.

[1236] Input: Advertising effectiveness data, emotion data

[1237] Output: Areas for improvement and recommended strategies

[1238] 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.

[1239] 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.

[1240] 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.

[1241] [Fourth embodiment]

[1242] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1243] 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.

[1244] 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).

[1245] 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.

[1246] 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.

[1247] 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).

[1248] 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.

[1249] 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.

[1250] 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.

[1251] 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.

[1252] 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.

[1253] 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.

[1254] 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."

[1255] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertising copy, and automatically posts the advertisements on the most suitable advertising distribution platform.

[1256] First, a form is displayed on the device for the user to enter information about the product or service. The form has fields for entering the product name, description, and target audience information (gender, age, region, etc.). The user enters detailed information about their product or service in these fields and clicks the submit button.

[1257] The server then stores the information in a database, which automatically analyzes it and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information the user provided.

[1258] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. Data such as gender, age, and location play an important role in this process. For example, casual language may be used for younger audiences, while phrases that convey a sense of trust may be selected for older audiences.

[1259] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[1260] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[1261] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server analyzes this data and generates an ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the data after posting, keywords and phrases to use in the next advertising campaign are suggested.

[1262] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, they can grasp the effectiveness of their advertisements in real time, allowing them to flexibly improve their advertising strategies.

[1263] The above is an embodiment of the present invention.

[1264] The processing flow will be explained below.

[1265] Step 1:

[1266] User

[1267] The user accesses a form through their device to enter product information and target audience details, including the product name, description, target demographic (e.g., age, gender, region), etc. Once completed, they click the submit button.

[1268] Step 2:

[1269] server

[1270] When the user clicks the submit button, the input data is received and saved in a database. At this point, the input data includes the product name, description, and target audience details.

[1271] Step 3:

[1272] server

[1273] The server then runs a natural language processing (NLP) engine based on the stored data. The server analyzes product and target audience information and automatically generates ad copy, which includes keywords and phrases to enhance marketing effectiveness.

[1274] Step 4:

[1275] server

[1276] The generated ad copy is optimized based on target audience information. Attributes such as gender, age, and region are taken into account to adjust the ad copy for maximum effectiveness. For example, trendy wording is used for younger demographics, while phrases emphasizing trustworthiness are added for older demographics.

[1277] Step 5:

[1278] server

[1279] The optimized ad copy is then published to the appropriate ad distribution platform. The server automatically publishes the ad using the API of the selected platform (e.g., Facebook, Instagram, Google Ads).

[1280] Step 6:

[1281] server

[1282] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected and analyzed. This data is used to optimize ad delivery in the future.

[1283] Step 7:

[1284] server

[1285] Generate detailed reports based on the collected advertising effectiveness data, including advertising performance metrics (e.g., CTR, CPC, ROI) and target audience responses.

[1286] Step 8:

[1287] User

[1288] Users can view reports provided by the server on a dashboard, and can use the report content to consider strategies for their next advertising campaign.

[1289] Step 9:

[1290] server

[1291] Furthermore, it automatically suggests improvements and recommended strategies for the next advertising campaign based on advertising effectiveness, which users can use to improve their advertising strategies.

[1292] Step 10:

[1293] User

[1294] By entering information for your next advertising campaign and repeating the same process, you can continuously optimize your advertising effectiveness.

[1295] Example 1

[1296] 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."

[1297] For small businesses to easily create and distribute high-quality web advertisements requires a great deal of expertise and time. Furthermore, they have limited tools and resources to understand the effectiveness of their advertisements in real time and flexibly improve their strategies. To address these challenges, there is a need for a system that allows businesses to easily create high-quality advertisements without specialized knowledge, and monitor and improve their effectiveness in real time.

[1298] 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.

[1299] In this invention, the server includes means for providing a form including fields for users to input information about products or services they offer, means for saving the input product or service information in a database, means for analyzing the saved information using a natural language processing engine and automatically generating advertising copy, means for optimizing the generated advertising copy based on target audience information, means for automatically publishing the optimized advertising copy using an advertising distribution platform's API, means for measuring the number of impressions, click-through rates, and conversion rates of published advertisements in real time, and means for generating detailed reports based on the effectiveness of the advertisements and displaying them on a dashboard. This enables even small businesses without specialized knowledge to easily create and publish high-quality advertisements, understand their effectiveness in real time, and flexibly improve their advertising strategies.

[1300] A "form" is a screen display containing multiple fields for a user to enter product or service information.

[1301] "Database" means a digital storage system for storing product or service information entered by users.

[1302] A "natural language processing engine" is a software technology that analyzes input sentences and text information to generate sentences and perform semantic analysis.

[1303] "Ad copy" refers to a text message that introduces the product or service you offer and appeals to your target audience.

[1304] A "target audience" is a group of people with specific attributes to whom advertising is intentionally directed, such as people of a particular gender, age, location, etc.

[1305] "Optimization" refers to the process of adjusting generated ad copy based on target audience information to make it more effective.

[1306] An "advertising distribution platform" is an online system that distributes generated advertising copy and delivers it to many users.

[1307] An "API (Application Programming Interface)" is a set of definitions and protocols that allow different software systems to communicate with each other.

[1308] "Impressions" refers to the total number of times an advertisement is displayed on a user's screen.

[1309] "Click-through rate" refers to the percentage of users who click on an ad compared to the number of times it is displayed.

[1310] A "conversion rate" is the percentage of users who click on an ad and then actually take a specific action, such as purchasing a product or using a service.

[1311] A "report" is a written or digital output that provides a detailed analysis of the effectiveness of advertising and summarizes the results in an easy-to-understand format.

[1312] "Dashboard" means an interface that allows users to access the system's management screen and check advertising effectiveness and other important information in real time.

[1313] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically posts the advertisements on the most suitable advertisement distribution platform.

[1314] System configuration

[1315] User Input

[1316] The device displays a form for the user to enter product or service information. The form contains the following fields:

[1317] Product name

[1318] Product Description

[1319] Target audience information (gender, age, region, etc.)

[1320] The user enters the required information into these fields and clicks the submit button, which sends the information to the server.

[1321] Data storage and analysis

[1322] The server stores the received information in a database, where it is analyzed using a natural language processing (NLP) engine to automatically generate ad copy, which includes attractive keywords and phrases based on the information provided by the user.

[1323] Ad copy optimization

[1324] The generated ad copy is then further optimized. The server analyzes information about the target audience and adjusts the copy to best resonate with them. For example, ad copy aimed at younger audiences might use casual language, while phrases that exude trustworthiness might be selected for older audiences.

[1325] Automatic ad placement

[1326] The optimized ad copy is automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[1327] Report generation and dashboard viewing

[1328] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad effectiveness and recommended strategies for the next ad campaign.

[1329] Specific examples

[1330] For example, consider a case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, its features (e.g., "healthy, made with organic ingredients"), and the target demographic (health-conscious women in their 20s) into a form.

[1331] The server then parses this data and generates ad copy like this:

[1332] "Try our healthy organic green tea now!"

[1333] The server then optimizes the ad copy for the target audience and automatically places it on platforms like Instagram, a platform for young people.The server then measures the number of impressions, click-through rates, conversion rates, and other data in real time, generating detailed reports that are displayed on the user's dashboard.

[1334] Prompt Sentence Examples

[1335] An example of a prompt to input to a generative AI model is as follows:

[1336] Please generate advertising copy promoting our new product, "Organic Green Tea," aimed at health-conscious women in their 20s. Please clearly state the product name and its features (healthy, uses organic ingredients), and use language that will resonate with the target audience.

[1337] This system allows small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. In addition, the effectiveness of advertisements can be monitored in real time, allowing for flexible improvements to advertising strategies.

[1338] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1339] Step 1: Enter your information

[1340] The terminal displays a form for the user to enter product or service information. The form contains fields for entering the product name, product description, and target audience information (gender, age, region, etc.). The user enters the required information in these fields and clicks the submit button. The input for this step is the product or service information entered by the user in the form, and the output is the user-entered data that is sent to the server.

[1341] Step 2: Save your data

[1342] The server receives the information sent by the user. The server saves the entered information in a database. The input of this step is the product or service information sent by the user, and the output is the user information saved in the database.

[1343] Step 3: Analyze the data and generate ad copy

[1344] The server retrieves user information from a database and analyzes it using a natural language processing (NLP) engine. The server generates ad copy based on the input information. This ad copy contains attractive keywords and phrases based on the information the user provided. The input for this step is the user information stored in the database, and the output is the generated ad copy.

[1345] Step 4: Optimize your ad copy

[1346] The server optimizes the generated ad copy based on target audience information. The server analyzes data such as the target audience's gender, age, and region and adjusts the ad copy. For example, it selects casual language for younger demographics and phrases that convey trustworthiness for older demographics. The input for this step is the generated ad copy and target audience information, and the output is the optimized ad copy.

[1347] Step 5: Automated Ad Placement

[1348] The server automatically posts the optimized ad copy to the ad distribution platform. The server then uses the ad distribution platform's API to send the ad. The posted ad is then delivered to the specified target audience. The input for this step is the optimized ad copy and the ad distribution platform's API information, and the output is the ad posted to the distribution platform.

[1349] Step 6: Measuring advertising effectiveness

[1350] The server measures the effectiveness of advertising in real time after it is posted. The data measured includes the number of impressions, click rates, conversion rates, etc. The server collects and analyzes this data. The input to this step is the advertising effectiveness data obtained from the distribution platform, and the output is the analysis results.

[1351] Step 7: Generate reports and view dashboards

[1352] The server generates a detailed report based on the advertising effectiveness. The generated report is displayed on the user's dashboard. The user can check the performance of the advertising campaign through this report. It also displays improvements and recommended strategies for the next advertising campaign. The input of this step is the analyzed advertising effectiveness data, and the output is a detailed report that is displayed on the user's dashboard.

[1353] The above are the specific processing steps and details of this system, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[1354] (Application example 1)

[1355] 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."

[1356] Small businesses need a way to easily create and effectively distribute high-quality web advertisements. However, this requires specialized advertising knowledge and expensive software, making it difficult to achieve. It is also extremely difficult to measure the effectiveness of advertisements in real time and reflect the results in the next advertising campaign. For these reasons, there is an urgent need to provide a system that allows even small businesses to easily send out high-quality, effective advertisements.

[1357] 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.

[1358] In this invention, the server includes: means for providing a form for users to input information about products or services they offer; means for analyzing the input product or service information and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information; means for automatically publishing the advertising copy to the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means configured as an application executed on a smartphone, for generating advertising copy using a natural language processing engine and publishing the advertisement using the API of the advertising distribution platform; and means for users to input product information using a smartphone and distribute the generated advertising copy. This enables small businesses to easily create high-quality advertisements and distribute them effectively, even without specialized knowledge.

[1359] 1. "Form for entering information about products or services provided by users" means an electronic form that allows users to enter information about the products they sell or the services they provide.

[1360] 2. "Means for analyzing input product or service information and automatically generating advertising copy" refers to a system element that automatically generates advertising copy based on product or service information provided by users using a natural language processing engine or similar.

[1361] 3. "Means for optimizing generated ad copy based on target audience information" refers to a system element that optimizes generated ad copy based on information such as the gender, age, and place of residence of the target audience.

[1362] 4. "Means for automatically posting ad copy on the most appropriate ad distribution platform" refers to a function that automatically posts generated and optimized ad copy on the appropriate ad distribution platform.

[1363] 5. "Means for measuring the effectiveness of published advertisements in real time" refers to a function that collects and measures performance data such as the number of times an advertisement is displayed, click rate, and conversion rate in real time after the advertisement has been published.

[1364] 6. "Means for generating and displaying reports based on advertising effectiveness" refers to a function that generates and displays reports in a format that is easy for users to understand, based on advertising effectiveness data measured in real time.

[1365] 7. "Applications running on smartphones" means application software that runs on smartphones and allows users to input product information and generate, submit, and manage advertisements.

[1366] 8. "Means for generating advertising copy using a natural language processing engine" refers to a system element that uses natural language processing technology to automatically create effective advertising copy from product or service information provided by users.

[1367] 9. "Means for placing advertisements using the API of an advertising distribution platform" refers to a system element that automatically places generated and optimized advertising copy using the API provided by the advertising distribution platform.

[1368] 10. "Means for users to input product information using a smartphone and distribute the generated advertising copy" refers to a function that enables users to input product or service information using a smartphone and distribute advertising copy generated based on that information.

[1369] MODE FOR CARRYING OUT THE INVENTION

[1370] Specific embodiments for carrying out the present invention will be described below.

[1371] System configuration

[1372] The system includes the following hardware and software.

[1373] Hardware:

[1374] Smartphone: The device used by the user

[1375] Server: A central device that generates, optimizes, places, and measures the effectiveness of advertisements.

[1376] software:

[1377] Flask: a web framework

[1378] requests: HTTP request library

[1379] nltk: Natural Language Processing Library

[1380] Processing flow

[1381] 1. User input:

[1382] Using their smartphone, users fill out a form with the product name, description, and target audience details (e.g., age, gender, and region).

[1383] 2. Transmission and storage of information:

[1384] The entered information is sent from the smartphone to the server and stored in a database.

[1385] 3. Generating ad copy:

[1386] The server generates ad copy using the NLTK natural language processing engine. For example, if a user wants to advertise "organic green tea," the server generates ad copy such as "New organic green tea, a delicious tea perfect for health-conscious people. Order now!"

[1387] 4. Ad copy optimization:

[1388] The generated ad copy is optimized based on target audience information (e.g., women in their 20s living in urban areas). For example, casual language is used for younger audiences, while phrases that enhance trustworthiness are used for older audiences.

[1389] 5. Advertising:

[1390] The optimized ad copy is sent to the ad distribution platform's API using the requests library and is automatically published.

[1391] 6. Measuring results and displaying reports:

[1392] The effectiveness of the ads is measured in real time. The server collects data such as the number of impressions, click rates, and conversion rates, and generates reports based on this data, which are then displayed on a dashboard on the smartphone.

[1393] 7. Next strategy proposal:

[1394] Based on advertising effectiveness data, we provide users with improvements and recommended strategies for their next advertising campaign.

[1395] Specific examples

[1396] For example, if a user wants to advertise "organic green tea," they enter the following information into a form on their smartphone:

[1397] Product name: Organic Green Tea

[1398] Description: A delicious organic green tea perfect for health-conscious individuals.

[1399] Target audience: Health-conscious women in their 20s

[1400] An example of a prompt generated based on the input information:

[1401] Prompt statement:

[1402] Product Name: Organic Green Tea

[1403] Description: A delicious organic green tea perfect for health-conscious individuals.

[1404] Target audience: Health-conscious women in their 20s

[1405] The ad copy generated by the server will read, "New organic green tea, delicious tea perfect for health-conscious people. Order now!" The generated ad copy will be automatically posted to the ad distribution platform, and users will be able to check the effectiveness of the ad in real time on their smartphones.

[1406] The above is an embodiment of the present invention, which enables small businesses to easily create and effectively distribute high-quality advertisements without requiring specialized knowledge.

[1407] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1408] Step 1:

[1409] The user uses a smartphone to input information about the product or service. The input includes the product name, description, and target audience information (e.g., age, gender, and region). Once the input is complete, the user clicks the "Submit" button. This action sends the input information from the smartphone to the server.

[1410] input:

[1411] Product name

[1412] explanation

[1413] Target Audience Information

[1414] output:

[1415] Transmission data

[1416] Step 2:

[1417] The server parses the received data and stores it in a database, including product name, description, and target audience information. Once the process is complete, the next ad copy generation process is triggered.

[1418] input:

[1419] Transmission data

[1420] output:

[1421] Stored Data

[1422] Step 3:

[1423] The server uses the stored data to generate ad copy using the NLTK natural language processing engine, which is an attractive representation of the product information provided by the user.

[1424] input:

[1425] Stored Data

[1426] output:

[1427] Generated ad text

[1428] Step 4:

[1429] The server then optimizes the generated ad copy based on target audience information, which includes adjusting the tone and content of the ad copy based on gender, age, region, etc. For example, casual language might be used for younger audiences, while phrases that convey a sense of trust might be selected for older audiences.

[1430] input:

[1431] Generated ad text

[1432] Target Audience Information

[1433] output:

[1434] Optimized ad text

[1435] Step 5:

[1436] The server uses the API of the ad distribution platform to publish the optimized ad copy. It uses the requests library to send the necessary data to the API endpoint.

[1437] input:

[1438] Optimized ad text

[1439] output:

[1440] Confirmation of completion of posting

[1441] Step 6:

[1442] The server measures the effectiveness of the published ads in real time, obtaining data such as the number of impressions, click rates, and conversion rates from the ad distribution platform and continuously monitoring them.

[1443] input:

[1444] Ads placed

[1445] output:

[1446] Effectiveness measurement data

[1447] Step 7:

[1448] The server generates an advertising campaign effectiveness report based on the effectiveness measurement data and displays it on the user's dashboard, which the user can then view on their smartphone.

[1449] input:

[1450] Effectiveness measurement data

[1451] output:

[1452] Effectiveness Report

[1453] Step 8:

[1454] The server analyzes the data from the effectiveness report and provides users with recommendations for improvements and strategies for their next advertising campaign, enabling them to continuously carry out effective advertising operations.

[1455] input:

[1456] Effectiveness Report

[1457] output:

[1458] Improvements and recommended strategies

[1459] 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.

[1460] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. In addition, by using an emotion engine, it analyzes user emotions and reflects them in the creation and optimization of advertisements.

[1461] First, the user accesses a form on their device to enter product information and target audience details. The form has fields for entering information such as the product name, description, and target demographic (e.g., age, gender, and region). The emotion engine then recognizes and analyzes the user's emotions as they type. Once the input is complete, the user clicks the submit button.

[1462] The server then stores the information and sentiment data in a database, which is then automatically analyzed and uses a natural language processing (NLP) engine to generate ad copy, which includes attractive keywords and phrases based on the information and sentiment of the user.

[1463] The generated ad copy is then further optimized. The server analyzes the target audience information and also adjusts the ad copy by taking into account the user's emotional data. For example, if the user is feeling positive, it will use cheerful and positive language, and if the user is feeling cautious, it will add reassuring phrases. In this process, the target audience's attributes (gender, age, region, etc.) and the user's emotional data play an important role.

[1464] The optimized ad copy is then automatically published on the ad distribution platform. The server uses the ad distribution platform's API to publish the ad and measures the effectiveness of the post-publishing ad in real time. The measured data includes the number of impressions, click-through rate, conversion rate, etc.

[1465] A detailed report based on the effectiveness of the ads is generated and displayed on the user's dashboard. By viewing this report, users can check the results of their ad campaigns and plan their next strategy. The system also provides improvements based on the ad's effectiveness and recommended strategies for the next ad campaign. The emotion engine also influences these improvements and recommended strategies, providing advice that takes the user's emotions into consideration.

[1466] As a concrete example, consider the case where a user wants to advertise a new product, "Organic Green Tea." The user enters the product name, features, target demographic (health-conscious women in their 20s), etc. into a form. The server, along with this data, uses an emotion engine to analyze the user's emotions and generates ad copy such as "Try our healthy organic green tea now!" This ad copy is automatically posted on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-post data, keywords and phrases to use in the next advertising campaign are suggested.

[1467] In this way, small businesses can easily create high-quality advertisements and distribute them effectively, even without specialized knowledge. Furthermore, by utilizing emotion data, they can implement advertising strategies that match users' emotions and maximize advertising effectiveness. Furthermore, because the effectiveness of advertisements can be grasped in real time, advertising strategies can be flexibly improved.

[1468] The above is an embodiment of the present invention.

[1469] The processing flow will be explained below.

[1470] Step 1:

[1471] User

[1472] A user accesses the system through a terminal and accesses a form to enter product information and target audience details. The form has fields for product name, description, target demographic (e.g., age, gender, region), etc. The user enters information into these fields.

[1473] Step 2:

[1474] Terminal

[1475] While the user is entering information, the emotion engine built into the device monitors the user's input behavior, facial expressions, voice, etc. to recognize emotions. For example, it can analyze the user's facial expressions and tone of voice through a camera or microphone to obtain emotional data in real time.

[1476] Step 3:

[1477] User

[1478] Once the user has completed entering all the required information, they click the send button, which sends the entered data and emotion data to the server.

[1479] Step 4:

[1480] server

[1481] The server stores the received product information, target audience data, and user emotion data in a database, after which the data analysis process begins.

[1482] Step 5:

[1483] server

[1484] The stored data is fed into a natural language processing (NLP) engine, which analyzes product and target audience information to generate ad copy. The NLP engine then selects keywords and phrases to generate more compelling ad copy.

[1485] Step 6:

[1486] server

[1487] The generated ad copy is then further optimized. The server adjusts the copy based on the target audience information to make it more effective. The user's emotional data is also taken into account here. For example, if the user is positive, it uses cheerful and positive language, and if the user is cautious, it adds phrases that emphasize trustworthiness.

[1488] Step 7:

[1489] server

[1490] The optimized ad copy is automatically published on the selected ad distribution platform. The server uses the ad distribution platform's API to place the ad.

[1491] Step 8:

[1492] server

[1493] The effectiveness of published ads is measured in real time. Data such as the number of impressions, click rates, and conversion rates is collected to analyze ad performance.

[1494] Step 9:

[1495] server

[1496] Based on the analysis results, detailed reports are generated, including ad performance metrics and target audience responses. The sentiment engine takes user sentiment data into account and adjusts the report content.

[1497] Step 10:

[1498] User

[1499] Users can view reports provided by the server on a dashboard to check the results of their advertising campaigns, and can use the results of the reports to plan their next advertising strategy.

[1500] Step 11:

[1501] server

[1502] Based on the collected advertising effectiveness data and user sentiment data, the system provides improvements and recommended strategies for the next advertising campaign, including specific advice that takes into account the user's emotions.

[1503] Step 12:

[1504] User

[1505] The user re-enters the information for the next advertising campaign and repeats the same process to continuously optimize advertising effectiveness.

[1506] Example 2

[1507] 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."

[1508] In today's world, even small businesses are required to run efficient and effective advertising campaigns. However, systems that consistently manage everything from creating advertising copy to distribution and measuring effectiveness are expensive and require specialized knowledge, making them unaffordable for many small businesses. Furthermore, creating and effectively distributing advertisements that are optimized for user emotions and target audiences is even more difficult. These issues need to be resolved.

[1509] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1510] In this invention, the server includes: means for analyzing information about products or services provided by a user and the user's emotions, and automatically generating advertising copy; means for optimizing the generated advertising copy based on target audience information and user emotion data; means for automatically publishing the advertising copy on the optimal advertising distribution platform; means for measuring the effectiveness of the published advertisement in real time; means for generating and displaying a report based on the effectiveness of the advertisement; means for presenting improvements and recommended strategies for the next advertising campaign based on the user's emotion data; and means for using an emotion engine that simultaneously analyzes the user's input content and their emotions. This enables even small businesses to run consistently high-quality advertising campaigns without requiring specialized knowledge or high costs. It also enables the creation of advertisements optimized for the user's emotions and target audience, maximizing their effectiveness.

[1511] "User" means an individual or organization that utilizes the System to create and distribute advertising campaigns.

[1512] A "form" is an interface through which a user inputs product or service information.

[1513] "Product or Service Information" means details about the products or services you offer, including product names, descriptions, and target audience attributes (e.g., age, gender, location).

[1514] The "emotion engine" is a mechanism that analyzes the user's input and emotions.

[1515] A "natural language processing (NLP) engine" is a technology that analyzes input information and generates advertising copy in natural language.

[1516] "Ad copy" is a promotional copy automatically generated based on the information about the product or service provided by the user and the target audience.

[1517] A "target audience" is a specific group of users to whom an advertisement is intended to be delivered, and is defined by attributes such as age, gender, and region.

[1518] An "advertising distribution platform" is an online platform for distributing generated advertising copy.

[1519] An "API" (Application Programming Interface) is an interface that allows communication between an advertising distribution platform and a system.

[1520] "Effectiveness data" refers to data used to measure the effectiveness of an advertisement, such as the number of times an advertisement is displayed, click rate, and conversion rate.

[1521] "Report" means a report generated to analyze and demonstrate the effectiveness of an Advertising Campaign.

[1522] "Improvements and recommended strategies" are suggested optimizations and strategies for your next advertising campaign based on the results of your advertising campaign.

[1523] MODE FOR CARRYING OUT THE INVENTION

[1524] This invention relates to an AI-assisted platform that enables small businesses to easily create and distribute high-quality web advertisements and maximize their effectiveness. This system allows users to input information about the products and services they offer, analyzes that information, generates effective advertisement copy, and automatically submits the advertisement to the optimal advertisement distribution platform. Additionally, it uses an emotion engine to analyze user emotions and reflect them in the creation and optimization of advertisements.

[1525] Hardware and software used

[1526] Terminal: A device through which a user inputs product or service information. Examples include personal computers (PCs), smartphones, and tablets.

[1527] Server: A device that stores information, analyzes it, generates and optimizes ad copy, places ads, measures their effectiveness, and generates reports. It may be a cloud server or on-premise server with high-performance data processing capabilities.

[1528] Database: A system for storing data obtained from users. A relational database (RDBMS) or a NoSQL database can be used.

[1529] Natural language processing (NLP) engine: Software for analyzing product and service information and generating advertising copy. Open source NLP libraries and commercial NLP tools are used.

[1530] Sentiment engine: Software for analyzing emotions in real time with user input, using machine learning models and sentiment analysis APIs.

[1531] Ad serving platform API: An interface for automatically placing ad copy. Includes Google Ads API, Facebook Ads API, etc.

[1532] Explaining program processing in natural language

[1533] User Input

[1534] The user accesses a dedicated form on the system using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, and region). As the user enters the information, the emotion engine analyzes the user's emotions in real time. When the user clicks the "Submit" button, the information is sent to the server.

[1535] Information storage and analysis

[1536] The server receives the information sent by the user and stores it in a database. The stored information is automatically analyzed using an NLP engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. The generated ad copy incorporates attractive keywords and phrases based on the user's emotional data analyzed by the emotion engine.

[1537] Ad copy optimization

[1538] The server then further optimizes the generated ad copy, taking into account target audience information and user sentiment data—for example, adding upbeat language if the user is expressing positive emotions, or reassuring phrases if the user is expressing caution.

[1539] Advertising and measuring effectiveness

[1540] The optimized ad copy is automatically placed via the server using the API of the ad distribution platform. Once the ad is placed, the server measures its effectiveness in real time, including data such as the number of impressions, click-through rate, and conversion rate.

[1541] Generate and view reports

[1542] The server generates a detailed report based on the effectiveness of the ads and displays it on the user's dashboard. Users can view this report through their devices to check the results of their ad campaigns. It also provides suggestions for improvements and recommended strategies for the next campaign. This allows users to maximize the effectiveness of their ads and receive useful feedback for their next campaign.

[1543] Examples of specific examples and prompts

[1544] As a specific example, consider a case where a user wants to advertise "organic green tea." The user enters the product name, features (e.g., natural, healthy), and target demographic (e.g., health-conscious women in their 20s) on their device. The emotion engine analyzes this data along with the user's emotions and generates ad copy such as "Try healthy organic green tea now!" This ad copy is automatically published on platforms aimed at young people, such as Instagram, and its effectiveness is measured in real time. Based on the post-publication data, keywords and phrases to use in the next advertising campaign are suggested.

[1545] Example prompt sentence:

[1546] Write the name of your product, a description, and details about your target audience. Also, tell us how you feel these days and want to promote it.

[1547] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1548] Step 1: User Input

[1549] The user accesses the system's dedicated form using a terminal. The form has fields for entering the product name, product description, and target demographic details (e.g., age, gender, region). The entered information is simultaneously analyzed by an emotion engine to determine the user's emotions. Specifically, when the user clicks the "Submit" button, the entered data is sent to the server.

[1550] Input: Product name, product description, target demographic details, user sentiment

[1551] Output: User input data sent

[1552] Step 2: Storing information (server)

[1553] The server receives the information sent by the user. The received information is stored in a database. This information includes the product name, product description, target demographic details, and user emotion data. The server securely stores the information and then proceeds to the next analysis step.

[1554] Input: Data submitted by the user

[1555] Output: Data stored in the database

[1556] Step 3: Analyzing information and generating ad copy (server)

[1557] The server retrieves the information stored in the database. This information is then analyzed using a natural language processing (NLP) engine. Based on this analysis, ad copy is generated based on the product name, description, and target demographic information. Analysis data from the emotion engine is also used to add keywords and phrases based on user sentiment to the ad copy.

[1558] Input: Information retrieved from the database

[1559] Output: Generated ad copy

[1560] Step 4: Ad copy optimization (server)

[1561] The server further optimizes the generated ad copy, taking into account target audience information and user sentiment data. For example, it adds upbeat language if the user is expressing positive sentiment, or adds reassuring phrases if the user is expressing cautious sentiment.

[1562] Input: Generated ad copy, target audience information, user sentiment data

[1563] Output: Optimized ad copy

[1564] Step 5: Posting Ads (Server)

[1565] The server automatically places the optimized ad copy using the API of the ad distribution platform. The specific operation of the ad placement is that the server sends the ad copy to the platform via the API, completing the placement process.

[1566] Input: Optimized ad text

[1567] Output: Posting to ad distribution platform completed

[1568] Step 6: Measuring the results (server)

[1569] The server measures the effectiveness of the placed ads in real time. The measured data includes the number of impressions, click rates, conversion rates, etc. Effectiveness data is obtained from the ad distribution platform and analyzed to evaluate the effectiveness.

[1570] Input: Effectiveness data from advertising distribution platform

[1571] Output: Analyzed advertising effectiveness data

[1572] Step 7: Generate and view reports (server, terminal)

[1573] The server generates a detailed report based on the effectiveness of the ads, which is displayed on the user's dashboard and can be viewed via their device, along with suggestions for improvements and recommended strategies for the next campaign.

[1574] Input: Analyzed advertising effectiveness data

[1575] Output: Reports displayed on the user's dashboard, with suggestions for improvement and recommended strategies

[1576] (Application example 2)

[1577] 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."

[1578] It is extremely difficult for small businesses to create high-quality web advertisements on a daily basis and distribute them effectively due to limited expertise and resources. It is also difficult to understand the effectiveness of advertisements in real time and develop optimal advertising strategies based on emotions. For this reason, a system is needed that allows businesses to easily create advertisements, distribute them to appropriate platforms, quickly evaluate and analyze their effectiveness, and flexibly improve their strategies.

[1579] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1580] In this invention, the server includes means for providing a form for users to input information about products or services they offer, means for automatically generating advertising copy by analyzing the input product or service information and user emotion data, means for optimizing the generated advertising copy based on target audience information and user emotion data, means for automatically publishing the advertising copy to an optimal advertising distribution platform, means for measuring the effectiveness of the published advertisement in real time, means for generating and displaying a report based on the effectiveness of the advertisement, means for analyzing user emotion data, means for reflecting the emotion analysis in the generation of advertising copy, means for publishing advertisements using the API of the advertising distribution platform, and means for collecting user emotion data using a smartphone or other mobile device. This enables even small businesses to easily create high-quality advertisements, effectively publish them, measure their effectiveness in real time, and implement optimal advertising strategies using emotion data.

[1581] "Product or service information" is data related to detailed descriptions and attributes of specific products or services offered by users.

[1582] A "form" is an interface or input screen that allows a user to input information about a product or service.

[1583] "Analysis" is the process of understanding input data and extracting patterns and characteristics.

[1584] "Advertising copy" is text used to effectively promote a product or service.

[1585] A "target audience" is a specific consumer group to which an advertisement is directed.

[1586] "Emotion data" is data that includes information about the user's emotional state.

[1587] Optimization is the process of adjusting a system or process to achieve maximum effectiveness toward a specific goal.

[1588] An "advertising distribution platform" is an online service or system for displaying and distributing generated advertisements.

[1589] "Automatic posting" is the process of automatically sending the generated ad copy to a designated ad distribution platform.

[1590] "Real-time" refers to data being processed as soon as it is generated.

[1591] "Measurement" is the process of collecting and analyzing specific data or metrics.

[1592] "Report" means a document or display containing analytical results and statistical data regarding the effectiveness of an Advertising.

[1593] "Emotion analysis means" refers to techniques and functions for analyzing user emotion data.

[1594] "Means for collecting user emotional data" refers to methods or techniques for obtaining data about a user's emotional state using a smartphone or other mobile device.

[1595] "API" stands for Application Programming Interface, and is a means for mutual use of functions and data between different software programs.

[1596] This invention is a system that enables small businesses to create high-quality web advertisements using smartphones and mobile devices and maximize their effectiveness. Detailed embodiments of this system are described below.

[1597] First, this system provides a form for users to enter product or service information through a smartphone or mobile device application. Users enter information such as the product name, description, and target demographic (e.g., age, gender, and region), and simultaneously collect emotional data using a camera and microphone.

[1598] To analyze emotion data, we use the smartphone's camera and microphone and emotion analysis tools (e.g., Emotion API), which allows us to analyze the user's emotional state simultaneously with their input.

[1599] Once the data is entered, the server stores it in a database (e.g., AWS RDS). The stored data is then used to automatically generate ad copy using a natural language processing (NLP) engine (e.g., GPT-4). The generated ad copy is then further optimized based on user sentiment data and target audience information.

[1600] The generated ad copy is automatically submitted to an ad distribution platform (for example, Google Ads API or Facebook Ads API). After submission, the server measures the effectiveness of the ad (number of impressions, click-through rate, conversion rate, etc.) in real time, and generates a detailed report based on this information and displays it on the user's dashboard.

[1601] Users can view reports to check the results of their advertising campaigns and plan their next strategy. The system also provides suggestions for improvement and recommended strategies based on the effectiveness of advertising, providing advice that takes users' emotions into consideration.

[1602] As a concrete example, consider the case where a user wants to advertise a new product, "organic tea." The user enters "organic tea" as the product name and "health-conscious women in their 20s" as the target demographic in an application form, and emotional data is collected using a camera and microphone. The server analyzes this data and generates a positive ad copy such as "Try this organic tea that's good for your body now!" This ad copy is automatically posted on an ad distribution platform for young people, and its effectiveness is measured in real time.

[1603] An example of a prompt for a generative AI model is:

[1604] Product Name: Fruit Cake

[1605] Product Description: A delicious cake made with fresh fruit.

[1606] Target demographic: Young people (women in their 20s)

[1607] User Sentiment: Positive

[1608] What you should pay attention to: Fresh and healthy ingredients

[1609] Use this to generate compelling ad copy.

[1610] In this way, small businesses can easily create high-quality advertisements without specialized knowledge and flexibly maximize their effectiveness.

[1611] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1612] Step 1:

[1613] A user logs into a smartphone or mobile device application and inputs product or service information. The input information includes the product name, description, and target demographic (e.g., age, gender, and region). The camera and microphone are also used to collect user emotion data.

[1614] Input: Product name, description, target demographic, sentiment data

[1615] Output: Input information and emotion data

[1616] Step 2:

[1617] The terminal sends the collected data to the server. The server receives this data and stores it in a database (e.g., AWS RDS). Here, we check that the data is stored correctly.

[1618] Input: Input information and emotion data

[1619] Output: Data stored in the database

[1620] Step 3:

[1621] The server analyzes the stored data and uses a natural language processing (NLP) engine (e.g., GPT-4) to automatically generate ad copy based on the input information (product name, description, target demographic).

[1622] Input: Data stored in the database

[1623] Output: Auto-generated ad text

[1624] Step 4:

[1625] The server optimizes the generated ad copy based on the target user's emotional data and target audience information. For example, if the emotional data is positive, it uses upbeat and positive language, and if the emotional data is cautious, it adds reassuring phrases.

[1626] Input: ad copy, sentiment data, target audience information

[1627] Output: Optimized ad text

[1628] Step 5:

[1629] The server automatically posts the optimized ad copy using the API of the specified ad distribution platform (for example, Google Ads API or Facebook Ads API). When posting, the ad copy is adjusted to fit the terms and format of each platform.

[1630] Input: Optimized ad text

[1631] Output: Ads posted to ad serving platforms

[1632] Step 6:

[1633] The server measures the effectiveness of the advertisement (number of impressions, click rate, conversion rate) in real time after it is posted. The measured data is then saved in the database.

[1634] Input: Advertising effectiveness data

[1635] Output: Advertising effectiveness data stored in a database

[1636] Step 7:

[1637] The server generates detailed reports based on the advertising effectiveness data, which are displayed on the user's dashboard, allowing the user to check the performance of their advertising campaigns and plan their next strategy.

[1638] Input: Advertising effectiveness data stored in the database

[1639] Output: The report that appears on the user's dashboard

[1640] Step 8:

[1641] The server further calculates keywords and phrases to be used in the next advertising campaign, as well as areas for improvement and recommended strategies, based on the advertising effectiveness data and user emotion data, and provides these to the user.

[1642] Input: Advertising effectiveness data, emotion data

[1643] Output: Areas for improvement and recommended strategies

[1644] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1645] 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.

[1646] 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 robot 414.

[1647] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1648] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1649] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1650] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1651] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1652] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1653] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1654] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1655] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1656] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1657] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1658] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1659] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1660] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1661] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1662] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1663] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1664] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1665] The following is further disclosed regarding the above embodiment.

[1666] (Claim 1)

[1667] means for providing a form for a user to enter information about a product or service to be offered;

[1668] A means for analyzing input product or service information and automatically generating advertising copy;

[1669] A way to optimize the generated ad copy based on target audience information,

[1670] A means to automatically post ad copy to the optimal ad distribution platform,

[1671] A means to measure the effectiveness of placed advertisements in real time,

[1672] A system including means for generating and displaying reports based on the effectiveness of advertisements.

[1673] (Claim 2)

[1674] 10. The system of claim 1, further comprising means for analyzing information about the target audience and selecting an optimal advertising distribution platform.

[1675] (Claim 3)

[1676] 10. The system of claim 1, further comprising means for providing the user with improvements and recommended strategies for the next advertising campaign based on the effectiveness of the advertisement.

[1677] "Example 1"

[1678] (Claim 1)

[1679] means for providing a form including fields for a user to enter information about a product or service to be offered;

[1680] means for storing the entered product or service information in a database;

[1681] A means for analyzing the stored information using a natural language processing engine and automatically generating advertising copy;

[1682] A means for optimizing the generated ad copy based on target audience information;

[1683] A method to automatically place optimized ad copy using the API of the ad distribution platform,

[1684] A means to measure the number of impressions, click rates, and conversion rates of published ads in real time,

[1685] The system includes a means for generating detailed reports based on the effectiveness of advertising and displaying them on a dashboard.

[1686] (Claim 2)

[1687] 10. The system of claim 1, further comprising means for analyzing information about the target audience and selecting an optimal advertising delivery platform.

[1688] (Claim 3)

[1689] 10. The system of claim 1, further comprising means for providing the user with improvements and recommended strategies for their next advertising campaign based on the effectiveness of the advertisement.

[1690] "Application Example 1"

[1691] (Claim 1)

[1692] means for providing a form for a user to enter information about a product or service to be offered;

[1693] A means for analyzing input product or service information and automatically generating advertising copy;

[1694] A way to optimize the generated ad copy based on target audience information,

[1695] A means to automatically post ad copy to the optimal ad distribution platform,

[1696] A means to measure the effectiveness of placed advertisements in real time,

[1697] means for generating and displaying reports based on the effectiveness of the advertisements;

[1698] It is configured as an application that runs on a smartphone,

[1699] Generate ad copy using a natural language processing engine,

[1700] A means of placing ads using the API of an ad distribution platform,

[1701] A system that includes a means for a user to input product information using a smartphone and distribute the generated advertising copy.

[1702] (Claim 2)

[1703] Further includes means for analyzing target audience information and selecting the most suitable advertising distribution platform.

[1704] 10. The system of claim 1.

[1705] (Claim 3)

[1706] Further includes a means to provide users with improvements and recommended strategies for their next advertising campaign based on the effectiveness of their advertising.

[1707] 10. The system of claim 1.

[1708] "Example 2: Combining Emotion Engines"

[1709] (Claim 1)

[1710] means for providing a form for a user to enter information about a product or service to be offered;

[1711] A means for automatically generating advertising copy by analyzing input product or service information and user sentiment;

[1712] A means for optimizing the generated advertising copy based on target audience information and user sentiment data;

[1713] A means to automatically post ad copy to the optimal ad distribution platform,

[1714] A means to measure the effectiveness of placed advertisements in real time,

[1715] means for generating and displaying reports based on the effectiveness of the advertisements;

[1716] A means to suggest improvements and recommended strategies for the next advertising campaign based on user sentiment data;

[1717] A method using an emotion engine that simultaneously analyzes user input and its emotions

[1718] A system including:

[1719] (Claim 2)

[1720] Further includes means for analyzing target audience information and selecting the most suitable advertising distribution platform.

[1721] 10. The system of claim 1.

[1722] (Claim 3)

[1723] Further includes a means to provide users with improvements and recommended strategies for their next advertising campaign based on the effectiveness of their advertising.

[1724] 10. The system of claim 1.

[1725] "Application example 2 when combining emotion engines"

[1726] (Claim 1)

[1727] means for providing a form for a user to enter information about a product or service to be offered;

[1728] A means for analyzing input product or service information and automatically generating advertising copy;

[1729] A means for optimizing the generated advertising copy based on target audience information and user sentiment data;

[1730] A means to automatically post ad copy to the optimal ad distribution platform,

[1731] A means to measure the effectiveness of placed advertisements in real time,

[1732] means for generating and displaying reports based on the effectiveness of the advertisements;

[1733] emotion analysis means for analyzing emotion data of a user;

[1734] A means for reflecting the sentiment analysis in the generation of advertising copy;

[1735] A means of placing ads using the API of an ad distribution platform,

[1736] A system including means for collecting user emotion data using a smartphone or other mobile device.

[1737] (Claim 2)

[1738] 10. The system of claim 1, further comprising means for analyzing information about the target audience and selecting an optimal advertising delivery platform.

[1739] (Claim 3)

[1740] 10. The system of claim 1, further comprising means for providing the user with improvements and recommended strategies for the next advertising campaign based on the effectiveness of the advertisement. [Explanation of symbols]

[1741] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for providing a form for a user to enter information about a product or service to be offered; A means for analyzing input product or service information and automatically generating advertising copy; A way to optimize the generated ad copy based on target audience information, A means to automatically post ad copy to the optimal ad distribution platform, A means to measure the effectiveness of placed advertisements in real time, A system including means for generating and displaying reports based on the effectiveness of advertisements.

2. 10. The system of claim 1, further comprising means for analyzing information about the target audience and selecting an optimal advertisement distribution platform.

3. 10. The system of claim 1, further comprising means for providing the user with improvements and recommended strategies for the next advertising campaign based on the effectiveness of the advertisement.

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