Information processing device, information processing method, and program

Abstract

The framework and workflow, which systematize multiple appeal axes, allows for the highly reproducible selection of the optimal appeal tailored to the product and target audience. [Solution] The information acquisition unit 51 acquires information about a predetermined product or service that the target wants to appeal to, as the target information, and acquires information about the target as the target information. The appeal axis selection unit 52 uses axes to which predetermined appeal characteristics are assigned as appeal axes, and based on the target information and target information, selects an appeal axis from among multiple appeal axes that is suitable for appealing the target to the target. The appeal content generation unit 53 generates appeal content that includes content to appeal to the target with the appeal characteristics corresponding to the selected appeal axis.

Description

Technical Field

[0006] , ,

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

Background Art

[0002] Conventionally, there are technologies for selecting an appeal method and generating appeal content in marketing communication (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in recent years, since the appeal method in marketing communication is personal and there is no framework for a systematic appeal axis, there is a demand for a problem that it is difficult to reproducibly select an optimal appeal according to a product or a target, but the conventional technologies including the technology of Patent Document 1 cannot sufficiently meet such a demand.

[0005] The present invention has been made in view of such a situation, and an object thereof is to be able to reproducibly select an optimal appeal according to a product or a target by a framework and a workflow in which a plurality of appeal axes are systematized.

Means for Solving the Problems

[0006] To achieve the above object, an information processing apparatus according to an aspect of the present invention [[ID= forty-seven ]] information acquisition means for acquiring information related to a target as target information and information related to a predetermined product or service to be appealed to a target as appeal target information, with the predetermined product or service to be appealed to the target as an appeal target; A means for selecting an appeal axis from among a plurality of appeal axes, based on the appeal target information and the target information, using axes to which predetermined appeal characteristics are assigned as appeal axes, the appeal axis being selected as the appropriate appeal axis for appealing to the target, A means for generating appeal content that generates appeal content, which includes content that appeals to the target audience with the appeal characteristics corresponding to the selected appeal axis, It is equipped with.

[0007] Each of the information processing method and program according to one aspect of the present invention corresponds to each of the method and program corresponding to the information processing apparatus according to one aspect of the present invention. [Effects of the Invention]

[0008] According to the present invention, a framework and workflow that systematizes multiple appeal axes makes it possible to reliably select the optimal appeal according to the product and target audience. [Brief explanation of the drawing]

[0009] [Figure 1] This figure shows an overview of the service that can be realized by an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 2] This figure shows an example of the configuration of an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 3] Figure 2 is a block diagram showing an example of the server hardware configuration in the information processing system. [Figure 4] This is a functional block diagram showing an example of the functional configuration of the server in Figure 3 that constitutes the information processing system in Figure 2. [Figure 5] Figures 1 to 4 show an overview of the marketing communications field according to this embodiment. [Figure 6] Figures 1 to 4 show the systematic appeal axis for this embodiment. [Figure 7]A diagram showing the continuous improvement cycle of the marketing process for the present embodiment in FIGS. 1 to 4. [Figure 8] A diagram showing the implementation configuration of result-oriented marketing creativity for the present embodiment in FIGS. 1 to 4. [Figure 9] A diagram showing the detailed process of economic environment analysis for the present embodiment in FIGS. 1 to 4. [Figure 10] A diagram showing the detailed process of technological environment analysis for the present embodiment in FIGS. 1 to 4. [Figure 11] A diagram showing the detailed process of political and social environment analysis for the present embodiment in FIGS. 1 to 4. [Figure 12] A diagram showing the details of price and promotion in the 4P measures for the present embodiment in FIGS. 1 to 4. [Figure 13] A diagram showing the detailed process of USP design for the present embodiment in FIGS. 1 to 4. [Figure 14] A diagram showing the first aspect of the role sharing between humans and AI for the present embodiment in FIGS. 1 to 4. [Figure 15] A diagram showing the second aspect of the role sharing between humans and AI for the present embodiment in FIGS. 1 to 4. [Figure 16] A diagram showing the first aspect of the appeal axis selection matrix for the present embodiment in FIGS. 1 to 4. [Figure 17] A diagram showing the second aspect of the appeal axis selection matrix for the present embodiment in FIGS. 1 to 4. [Figure 18] A diagram showing the process from target identification to USP extraction for the present embodiment in FIGS. 1 to 4. [Figure 19] A diagram showing the information sorting process in target analysis for the present embodiment in FIGS. 1 to 4. [Figure 20] A diagram showing the process of targeting and segmentation for the present embodiment in FIGS. 1 to 4. [Figure 21]It is a diagram showing the integrated marketing flow of WHO·WHAT·HOW for the present embodiment of FIGS. 1 to 4. [Figure 22] It is a diagram showing a list screen of appeal contents in the user interface section for the present embodiment of FIGS. 1 to 4. [Figure 23] It is a diagram showing a measure management screen in the user interface section for the present embodiment of FIGS. 1 to 4. [Figure 24] It is a diagram showing an editing / regeneration screen in the user interface section for the present embodiment of FIGS. 1 to 4. [Figure 25] It is a diagram showing a detailed display screen of appeal contents in the user interface section for the present embodiment of FIGS. 1 to 4. [Figure 26] It is a diagram showing a detailed process flow of the WHO area for the present embodiment of FIGS. 1 to 4. [Figure 27] It is a diagram showing a detailed hierarchical structure of the appeal axis for the present embodiment of FIGS. 1 to 4. [Figure 28] It is a diagram showing an appeal content generation process in the first specific example for the present embodiment of FIGS. 1 to 4. [Figure 29] It is a diagram showing a detailed display screen of appeal contents in the first specific example for the present embodiment of FIGS. 1 to 4. [Figure 30] It is a diagram showing the concept of automation by the integration of LLM and workflow for the present embodiment of FIGS. 1 to 4. [Figure 31] It is a diagram showing the marketing efficiency improvement and CO2 reduction effect by data structuring for the present embodiment of FIGS. 1 to 4. [Figure 32] It is a diagram showing the integrated marketing framework for the present embodiment of FIGS. 1 to 4.

Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0011] First, with reference to Figure 1, an overview of the service (hereinafter referred to as "this service") that can be realized by an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied will be described. Figure 1 shows an overview of the service that can be realized by an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied.

[0012] This service is a marketing communication service that systematically selects appeal axes to effectively target a product or service, and automatically generates appeal content based on the selected appeal axes.

[0013] Specifically, Figure 1 shows a series of steps from step S1 to step S7. In step S1, product information is registered as target information from the user terminal 2. As a specific example of this embodiment, for example, information such as the product name "Moist Care" lotion, price, ingredients, and features is entered. Specifically, detailed product information such as "Moist Care" as the product name, "3000 yen" as the price, "Hyaluronic acid, ceramide, collagen" as the main ingredients, and "High moisturizing, fragrance-free, suitable for sensitive skin" as features is entered. This registration of product information is performed by the user entering the necessary items on the screen of the user terminal 2, or by reading from an existing database.

[0014] In step S2, Server 1 acquires product information for the lotion "Moist Care" as target information, information on women in their 30s who suffer from dry skin as target information, and information on competitor lotions A, B, and C as competitor information. The target information includes detailed attribute information such as age group 30s, gender female, skin type dry skin, and main concerns "dry skin," "fine lines," and "poor makeup application." The competitor information includes information such as the price of competitor lotion A is 2500 yen and its characteristic is "emphasis on whitening," the price of competitor lotion B is 4000 yen and its characteristic is "emphasis on anti-aging care," and the price of competitor lotion C is 2000 yen and its characteristic is "low price appeal." At this time, Server 1 acquires market analysis data from external database 3. The market analysis data includes data such as the size of the overall lotion market, growth rate, consumer purchasing trends, seasonal demand fluctuations, market share by price range, and preferences by age group. This information is stored in a database on server 1 and used in subsequent analysis processes. This allows for analysis based on multifaceted information.

[0015] In step S3, Server 1 performs target analysis, specifically target insight analysis, to understand the target's psychological state, such as skin problems due to dryness or a focus on moisturizing. The insight analysis identifies specific concerns faced by women in their 30s, such as "makeup doesn't apply well in the morning," "skin feels tight by the evening," and "skin breaks out during seasonal changes." It also identifies the target's ideal state, such as "moist skin all day long," "makeup doesn't smudge," and "healthy, radiant skin." Furthermore, Server 1 performs positioning analysis using a 3C analysis to identify points of differentiation from competitors. For example, the 3C analysis identifies the needs of women in their 30s with dry skin as Customer, the strengths and weaknesses of competitor lotions A, B, and C as Competitors, and the uniqueness of the lotion "Moist Care" as Company. As a result, the differentiating points of "Moist Care" are identified as "balanced blend of highly moisturizing ingredients," "safe for sensitive skin," and "affordable price." This organizes the basic information necessary for selecting the key selling points.

[0016] In step S4, Server 1 selects the optimal appeal axis from among multiple appeal axes. In this embodiment, the appeal axes include functional feature appeal axis, benefit appeal axis, advantage appeal axis, authority appeal axis, evidence appeal axis, price appeal axis, rarity appeal axis, social proof appeal axis, etc., and the appeal axis that best suits the target and product characteristics is selected from among these. In the example of the lotion "Moist Care" in this embodiment, the advantage appeal axis (appealing to a good future state of "long-lasting moist skin"), the evidence appeal axis (appealing to scientific evidence such as "proven in clinical trials"), and the authority appeal axis (appealing to expert recommendation such as "recommended by dermatologists") are selected. The selection of the appeal axis is performed based on the target information, competitor information, market analysis data obtained in step S2, and the results of the target analysis and positioning analysis performed in step S3. For example, if the analysis reveals that the target audience, women in their 30s, tend to value "scientific evidence" and "expert opinions," then an evidence-based appeal or an authority-based appeal will be selected. Similarly, if "long-lasting moisturizing effect" is identified as a key differentiating factor from competitors, then a benefit-based appeal will be selected. In this way, the most impactful appeal is automatically selected based on target audience information, competitor information, and other relevant data.

[0017] In step S5, Server 1 generates a specialized prompt corresponding to the selected appeal axis and inputs it into AI(LLM)4. A specialized prompt is not simply a generic prompt such as "Generate an appeal statement," but a detailed prompt that clearly specifies the target audience, target, and appeal axis. For example, in this embodiment, a specialized prompt is generated that reads, "Generate an appeal statement for a lotion targeting women in their 30s with dry skin, focusing on benefits. Specifically, emphasize the comfort of the skin due to the all-day moisturizing effect." Furthermore, for evidence-based and authority-based appeals, specialized prompts are also generated, such as, "Emphatically emphasize that the moisturizing effect has been demonstrated in clinical trials," and "Emphatically emphasize that it is recommended by dermatologists." When these specialized prompts are input into AI(LLM)4, AI(LLM)4 generates appealing content such as, "For moisturized skin that never dries out. Protect your skin with moisturizing power that lasts from morning to night. Contains dermatologist-recommended moisturizing ingredients, and its moisturizing effect has been proven in clinical trials. Change your daily skincare routine with moist care." Traditionally, marketing personnel would spend several hours to several days creating multiple appeal drafts and deciding on the final version after repeated reviews with their superiors and colleagues. However, in this embodiment, by utilizing LLM, multiple appeal drafts can be automatically generated in just a few minutes, significantly reducing the amount of work required. In addition, the generated appeals are created based on the selected appeal axis, so they are likely to resonate with the target audience.

[0018] In step S6, Server 1 stores the target information, selected appeal axes, and generated appeal content in a database, associating them with each other. Specifically, for example, product information such as the lotion "Moist Care," target information such as women in their 30s with dry skin, selected appeal axes such as benefit appeal axis, evidence appeal axis, and authority appeal axis, and generated appeal content such as "For moisturized skin that is free from dryness..." are stored as a single record, associating them with each other. By storing them in this association, it is possible to refer to all at once later to see "for which product," "for which target," "using which appeal axes," and "what kind of appeal content was generated." Furthermore, by analyzing past appeal results, insights such as "benefit appeal axes are effective for women in their 30s" can be accumulated. This allows for the analysis of past appeal results and the acceleration of the hypothesis testing and improvement process. In addition, when generating appeal content for similar products and targets, it becomes possible to select more effective appeal axes by referring to past success stories, for example.

[0019] In step S7, Server 1 displays the generated appeal content on User Terminal 2. The screen of User Terminal 2 displays multiple generated appeal content in card or list format. The user can review the displayed appeal content, select the ones they like, edit them as needed, or instruct the system to regenerate them. For example, if the user wants to include more specific numbers, they can edit the phrase "moisturizing power that lasts from morning to night" to "moisturizing power that lasts for 12 hours." Also, if the generated appeal content does not meet expectations, the user can input feedback such as "Please make the expression more emotional" and instruct the system to regenerate it. Upon receiving feedback from the user, Server 1 adjusts the specialized prompts and inputs them back into AI(LLM)4 to generate new appeal content. In this way, rather than being fully automated, the system involves collaboration between humans and AI, enabling fine-tuning that would not be possible with full automation, and creating appeal content that is more suitable for practical use.

[0020] As described above, this service provides a framework that systematizes the appeal axis and a workflow that will become the new standard for marketing communications through automation utilizing LLM. The marketing communications process, which was previously highly dependent on individual expertise and difficult to reproduce, is systematized into a clear workflow through this service, enabling anyone to generate high-quality appeal content.

[0021] Next, with reference to Figure 2, we will describe the configuration of an information processing system to which an information processing system that realizes the provision of the above-mentioned service, i.e., an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. Figure 2 shows an example of the configuration of an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied.

[0022] The information processing system shown in Figure 2 is configured to include a server 1, user terminals 2-1 to 2-n, an external database 3, and an AI (LLM) 4. Server 1, user terminals 2-1 to 2-n, external database 3, and AI(LLM) 4 are interconnected via a network N such as the Internet. Furthermore, if there is no need to distinguish between user terminals 2-1 through 2-n individually, they will be collectively referred to as "user terminal 2".

[0023] Server 1 is an information processing device managed by the service provider of this service. Server 1 performs various processes necessary to realize this service while communicating with user terminal 2, external database 3, and AI(LLM) 4 as needed. User terminal 2 is an information processing device operated by a marketing person, and consists of a smartphone, tablet, personal computer, etc. External database 3 is an information processing device that provides market analysis data, consumer trends, purchasing behavior data, etc. AI(LLM)4 is an information processing device equipped with a large-scale language model used for generating compelling content.

[0024] Figure 3 is a block diagram showing an example of the server hardware configuration in the information processing system shown in Figure 2.

[0025] Server 1 comprises a CPU (Central Processing Unit) 11, ROM (Read Only Memory) 12, RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0026] The CPU 11 executes various processes according to the program recorded in the ROM 12 or the program loaded from the storage unit 18 into the RAM 13. RAM13 also stores data and other information necessary for the CPU11 to perform various processes.

[0027] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. An input / output interface 15 is connected to an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0028] The input unit 16 is configured, for example, with a keyboard, and is used to input various types of information. The output unit 17 consists of a display such as an LCD and a speaker, and outputs various information as images and sounds. The memory unit 18 is composed of DRAM (Dynamic Random Access Memory) and stores various types of data. The communication unit 19 communicates with other devices (for example, the user terminal 2 in Figure 2, the external database 3, and the AI(LLM) 4) via a network N including the Internet.

[0029] The drive 20 is appropriately fitted with removable media 21, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory. Programs read from the removable media 21 by the drive 20 are installed in the storage unit 18 as needed. Furthermore, the removable media 21 can store various types of data stored in the storage unit 18, just as the storage unit 18 does.

[0030] Although not shown in the diagram, the user terminal 2, external database 3, and AI(LLM) 4 in Figure 2 can have essentially the same hardware configuration as shown in Figure 3. Therefore, a description of the hardware configuration of user terminal 2, external database 3, and AI(LLM) 4 will be omitted.

[0031] Through the cooperation of various hardware and software components that make up the information processing system in Figure 2, including Server 1 in Figure 3, various processes for providing the service in Figure 1 can be executed.

[0032] Figure 4 is a functional block diagram showing an example of the functional configuration of the server in Figure 3 within the information processing system shown in Figure 2.

[0033] As shown in Figure 4, the CPU 11 of server 1 functions as follows: information acquisition unit 51, appeal axis selection unit 52, appeal content generation unit 53, user interface unit 54, and data storage unit 55. Furthermore, one area of ​​the storage unit 18 of server 1 is provided with target information DB71, target information DB72, competitor information DB73, market analysis data DB74, appeal axis DB75, and appeal content DB76.

[0034] The information acquisition unit 51 acquires information about a designated product or service that it wants to appeal to a target audience as the target information, and information about the target audience as the target information. Specifically, for example, it acquires product information for a lotion called "Moist Care" as the target information, and acquires information about women in their 30s who suffer from dry skin as the target information. The information acquisition unit 51 also acquires information about competitors as competitor information and acquires market analysis data from the external database 3. The acquired target information is stored in the target information DB 71, the target information is stored in the target information DB 72, the competitor information is stored in the competitor information DB 73, and the market analysis data is stored in the market analysis data DB 74.

[0035] The appeal axis selection unit 52 uses axes assigned predetermined appeal characteristics as appeal axes and, based on the target information and target information, selects an appeal axis from among multiple appeal axes that is suitable for appealing to the target audience. The appeal axis selection unit 52 extracts multiple appeal axes from the appeal axis DB 75 and selects the optimal appeal axis based on the information stored in the target information DB 71, target information DB 72, competitor information DB 73, and market analysis data DB 74. The appeal axis selection unit 52 performs a target analysis based on the target information and selects an appeal axis based on the results of the target analysis. In addition, the appeal axis selection unit 52 extracts competitor information from the competitor information DB 73, performs a positioning analysis based on the competitor information, and selects an appeal axis based on the results of the positioning analysis. Specifically, for example, by organizing information on the company, customers, and competitors using 3C analysis and creating a positioning map, the points of differentiation from competitors are clarified. Furthermore, the appeal axis selection unit 52 extracts market analysis data from the market analysis data DB 74 and uses this market analysis data to select appeal axes. This makes it possible to create appeals that reflect market trends and consumer behavior.

[0036] The appeal content generation unit 53 generates appeal content that includes content to appeal to the target audience with appeal characteristics corresponding to the selected appeal axis. The appeal content generation unit 53 obtains specialized prompts corresponding to the selected appeal axis from the appeal axis DB 75 and generates appeal content by inputting these specialized prompts into the large-scale language model. Specifically, for example, a specialized prompt such as "Generate appeal text for lotion targeting women in their 30s with dry skin, focusing on benefits" is input into the AI(LLM) 4 to generate appeal content. The generated appeal content is stored in the appeal content DB 76. In this way, by using specialized prompts, the output of a general-purpose LLM can be adapted to specific marketing communication requirements, enabling the automatic generation of high-quality appeal content.

[0037] The user interface unit 54 displays the promotional content generated by the promotional content generation unit 53 so that the user can review and edit it. The user interface unit 54 extracts promotional content from the promotional content DB 76, transmits it to the user terminal 2 via the communication unit 19, and displays it on the screen of the user terminal 2. The user can review, edit, select, and instruct the displaying promotional content to regenerate it. The user's editing results and regeneration instructions are transmitted from the user terminal 2 to the server 1 via the communication unit 19 and reprocessed by the promotional content generation unit 53. This allows for fine-tuning that cannot be handled by fully automated systems, enabling the creation of promotional content that is more suitable for practical use.

[0038] The data storage unit 55 stores target information, selected appeal axes, and generated appeal content in a database, associating them with each other. The data storage unit 55 manages the information stored in the target information DB 71, target information DB 72, appeal axis DB 75, and appeal content DB 76, associating them with each other. This allows for the analysis of past appeal results, accelerating the process of hypothesis testing and improvement. Specifically, for example, it is possible to analyze which appeal axes were effective for which targets and use this information to select appeal axes for the next campaign.

[0039] Figure 5 shows an overview of the marketing communications field in the embodiments of Figures 1 to 4.

[0040] Figure 5 shows an overview of the marketing communications field to which the present invention applies. Elements such as marketing strategy, strategy formulation, positioning, and 3C organization are arranged, and the relationships between each element are shown. In particular, 3C organization involves organizing company information, customer information, and competitor information, and deriving RTB (Reason To Believe). Furthermore, differentiation points are clarified through PoD, PoP, and PoF organization. Figure 5 shows that the marketing communications automation system realized by Server 1 of this embodiment is built on such a comprehensive framework.

[0041] Figure 6 is a diagram showing the structure of the appeal axes for the embodiment shown in Figures 1 to 4.

[0042] Figure 6 shows a hierarchical structure illustrating an example of the appeal axes of the present invention. Starting from the top-level "Appeal Axis," the second level consists of nine types of appeal axes: functional feature appeal axis, merit appeal axis, benefit appeal axis, reliability appeal axis, emotional / psychological appeal axis, negative appeal axis, offer appeal axis, comparison appeal axis, and social contribution appeal axis. Below each appeal axis, more detailed appeal elements are arranged. For example, under the functional feature appeal axis, basic performance, operability, additional functions, quality emphasis, and innovation are arranged. Under the merit appeal axis, time benefits, economic benefits, performance benefits, and convenience are arranged. Under the benefit appeal axis, functional benefits, emotional benefits, self-actualization benefits, and future-oriented benefits are arranged. Under the reliability appeal axis, usage history, third-party evaluation, and guarantee / support are arranged. Under the emotional / psychological appeal axis, empathy for concerns, urgency, sense of exclusivity, and loss / risk are arranged. Under the negative appeal axis, economic risks, health risks, and wasted time are placed. Under the offer appeal axis, discounts, free shipping, perks, and free trials are placed. Under the comparison appeal axis, direct competitor comparisons and indirect competitor comparisons are placed. Under the social contribution appeal axis, environmental considerations, social contribution, and sustainability are placed. This system is stored in the appeal axis DB75, and the appeal axis selection unit 52 selects the most suitable appeal axis from this system.

[0043] Figure 7 shows the continuous improvement cycle of the marketing process according to the embodiments shown in Figures 1 to 4.

[0044] Figure 7 shows the SMART framework, with five processes—Scope, Mapping, Allocation, Rebuild, and Test—arranged in a circle. This represents a continuous improvement cycle for realizing the hypothesis testing process by the data storage unit 55. In Scope, for example, the project objectives are clarified and stakeholder agreement is secured. In Mapping, for example, current processes are analyzed and opportunities for AI integration are identified. In Allocation, for example, task assignments between AI and humans are optimized. In Rebuild, for example, business processes are restructured. In Test, the AI ​​solution is evaluated and continuous improvements are made. Through this cycle, the server 1 of this embodiment significantly improves the speed of marketing strategy verification.

[0045] Figure 8 shows the implementation configuration of the results-oriented marketing creative according to the embodiments of Figures 1 to 4.

[0046] Figure 8 shows the detailed development of steps S2 to S5 in Figure 1. As an example of external environment organization, PEST, SWOT, and 5 Forces analysis is performed, and as an organization of the company's services, the company is organized from a 4P perspective. For example, as USP organization, competitor research, USP extraction, and user research are performed. For example, as STP organization, targeting, positioning, and segmentation are performed. For example, as WHO / WHAT design, target persona design, empathy map, funnel, and attributes are set. For example, as HOW design, appeal axis, psychological techniques, creative (copy, composition, design, video, search ad TD), and media (selection of advertising distribution media and targeting) are determined. Finally, PDCA operation is performed. This series of flow examples is realized by each functional block of Server 1 (information acquisition unit 51, appeal axis selection unit 52, appeal content generation unit 53, user interface unit 54, data storage unit 55).

[0047] Figure 9 shows the detailed process of the economic environment analysis for the embodiments shown in Figures 1 to 4.

[0048] Figure 9 shows an example of market analysis data obtained from external database 3, specifically an analysis of the Economy domain. It includes information on declining purchasing power during recessions, price-focused messaging, and market damage factors. The information acquisition unit 51 obtains this kind of economic environment data from external database 3 and stores it in market analysis data DB 74. The appeal axis selection unit 52 selects appeal axes appropriate to the economic environment based on this data. For example, during a recession, it is determined that price appeals and economic benefit appeals are effective.

[0049] Figure 10 shows the detailed process of the technical environment analysis for the embodiments shown in Figures 1 to 4.

[0050] Figure 10 shows an analysis of the Technology domain. As an example, it describes the penetration of AI technologies such as chatGPT (registered trademark), changes in needs for smoother information gathering, and the impact of AI utilization. The information acquisition unit 51 acquires data on such technology trends from the external database 3 and stores it in the market analysis data DB 74. The appeal axis selection unit 52 selects appeal axes according to the technology trends based on this data. For example, with the penetration of AI technology, it is determined that appeals to innovation and appeals to functional features are effective. Figure 10 shows the analysis in the Politics and Society domains. The analysis of political and social factors complements the remaining elements of the PEST analysis. The information acquisition unit 51 acquires such data from the external database 3 and stores it in the market analysis data DB 74. The appeal axis selection unit 52 comprehensively analyzes this data to select appeal axes based on a comprehensive understanding of the market environment. Figure 10 shows the details of Price and Promotion. For example, the coordination of pricing strategy and promotion strategy constitutes part of the 4P analysis. The appeal axis selection unit 52 reflects these analysis results in the selection of appeal axes. For example, it selects price appeals and offer appeals based on the pricing strategy, and selects limited-time appeals and urgency appeals based on the promotion strategy.

[0051] Figure 11 shows the detailed process of USP (Unique Suggestion Program) preparation for the embodiments shown in Figures 1 to 4.

[0052] Figure 11 shows an example of the process for organizing a Unique Selling Proposition (USP), which represents the "strengths" of a company's services. The USP organization process consists of three steps. The first step is to conduct user research. This involves interviewing users to delve deeper into their needs and pain points. Specifically, the research is conducted with multiple segments, including users who are already using the company's service, users who are using competitors' services, and people who considered the service but did not end up using it. This helps to identify the user's decision-making criteria. The second step is to conduct a competitive analysis. This analysis clarifies the differences between your company and its competitors. Using the user decision-making criteria derived from user research, your company's service is compared to that of competitors. The third step is USP extraction. USP extraction involves extracting the service's strengths from user research and competitor research. This clarifies the uniqueness of the company's service. The appeal axis selection unit 52 selects appeal axes using the USP information obtained through this USP organization process. For example, if "ease of use for anyone" is extracted as the USP, then a functional feature appeal axis and a merit appeal axis are selected.

[0053] Figure 12 shows the detailed process of the user survey for the embodiments shown in Figures 1 to 4.

[0054] Figure 12 shows examples of specific questions used to delve deeper into needs and pain points and identify users' decision-making criteria. Users are classified into multiple segments, such as target group A, target group B, and target group C. For target group A, which consists of users already using the company's service, questions such as the following might be asked: "What do you find most satisfying about it?", "What was the deciding factor in your purchase?", "What points would you emphasize when recommending it to other companies?", "What effects have you seen since implementing the service?", "Are there any additional features you would like to see?", and "Are there any areas where you would like usability to be improved?" For target group B, which consists of users currently using a competitor's service, questions such as the following might be asked: "What do you find most satisfying about this service?", "What was the deciding factor in your purchase?", "What points would you emphasize when recommending this service to other companies?", "Do you have any criteria for switching services?", and "What is the most important factor when switching services?" For target group C, those who considered the service but ultimately didn't use it, questions such as the following might be asked: "What were your main reasons for not adopting the service?", "Would you consider the service again? If so, what points would you prioritize?", and "When you were considering adopting the service, what additional features or characteristics would have made you decide to use it?" The information acquisition unit 51 acquires information to be stored in the target information DB 72 through such detailed user research. Based on this information, the appeal axis selection unit 52 selects the appeal axis that best suits the target's needs.

[0055] Figure 13 shows the detailed process of the competitive analysis for the embodiments shown in Figures 1 to 4.

[0056] Figure 13 shows a concrete example of a competitive analysis that uses the user's judgment axis on the vertical axis to highlight the differences between one's own company and others. The comparison table lists four companies: the company itself, competitor A, competitor B, and competitor C. The comparison criteria include service name, URL, monthly price, template, presence or absence of AI functionality, support system, additional features, and other characteristics. For example, in the case of this company, the monthly price starts from 200,000 yen, there are 2,400 templates (carefully selected for their effectiveness), the AI ​​function is described as "creating target personas and copy," the support system is described as "a dedicated consultant will accompany you from planning to operation," the additional features are described as "a wealth of video courses summarizing know-how," and other features are described as "easy operation for anyone to use." For example, in the case of competitor A, the monthly price starts at 140,000 yen, the number of templates starts at 1,400, the presence or absence of AI functionality is "none", the support system is "a dedicated consultant will accompany you from planning to operation", the additional features are "unlimited use of many BGM and materials, a user community is prepared", and other features are "suggestion of simple text overlays". For example, in the case of competitor B, the monthly price starts at 180,000 yen, the number of templates starts at 6,600, the presence or absence of AI functionality is "suggests simple captions", the support system is "a dedicated person resolves any questions", the additional features are "a stamp function and a wealth of animations", and other features are "a UI that is easy to use for a wide range of purposes such as training, recruitment, and advertising". For example, in the case of competitor C, the monthly price starts at 10,000 yen, there are 100 templates, AI functionality is "none", support is "none", additional features are "none", and other features are listed as "easy to get started". The information acquisition unit 51 stores the results of such competitive analysis in the competitive information database 73. The appeal axis selection unit 52 identifies the company's differentiating points based on this comparison table and selects appeal axes that can highlight those points. For example, if the company's "AI function" is a differentiating point that competitors do not have, then a functional feature appeal axis or a merit appeal axis would be selected.

[0057] Figure 14 is a diagram showing the competitive selection method for the embodiments of Figures 1 to 4.

[0058] Figure 14 shows the criteria for selecting competitors. For example, competitors are classified into direct competitors (exactly the same type of business) and indirect competitors (different types of businesses but overlapping target markets). Target markets are also classified into existing and latent customers. The following three points are given as examples of criteria for selecting competitors. One criterion for judgment is the target market volume. When directly competing for market share with competitors, it is necessary to consider whether there is a sufficient target market. If the base number is small, it may be difficult to increase the number of acquired customers. In such cases, it is necessary to expand the target market to include potential customers who are also considering competitors in other industries. The second criterion for evaluation is current market share. This is a common criterion for services offered by large corporations. If a company has a high market share for its services, it's likely that most of the target audience considering only that type of service are already existing customers. In such cases, it becomes necessary to expand the target audience to include potential customers. The third criterion for judgment is whether to prioritize scale or acquisition efficiency. This is related to the company's management policy. The decision depends on factors such as whether the company wants to acquire new customers with a focus on cost-effectiveness (CPA), whether it wants to expand the business quickly (CV count focus), and how much fixed costs there are (low CV count will result in losses). If CPA is prioritized, it is necessary to consider only existing customers, i.e., only those in the exact same industry, as competitors. If CV count is prioritized, it is necessary to expand to include potential customers and consider different industries as competitors. The appeal axis selection unit 52 determines, based on this competitor selection approach, which range of competitors to consider when selecting appeal axes. For example, if the target is only the existing customer base, appeal axes that focus directly on differentiation from competitors are selected, while if the target is expanded to include the potential customer base, broader appeal axes are selected.

[0059] Figure 15 shows the detailed process of STP organization for the embodiments shown in Figures 1 to 4.

[0060] Figure 15 illustrates the process of organizing the market position of a company's services from an STP perspective. STP consists of three steps: Segmentation, Targeting, and Positioning. The first step is segmentation. Segmentation involves dividing the market into smaller segments. For example, the market is divided into multiple segments based on axes such as age, gender, income, lifestyle, and purchasing behavior. Figure 15, Part 1, illustrates how the market is segmented. The second step is targeting. In targeting, you decide which market to target within the segmented market. From among multiple segments, you select the segment in which your company's USP (Unique Selling Proposition) will be best utilized. Figure 15, second diagram, shows how a specific segment is selected as a target. The third step is positioning. Positioning clarifies the market positioning of the service. It defines the position the company occupies within the selected target segment compared to competitors. Figure 15, Part 3, shows how the company's position is clarified on the positioning map. The appeal axis selection unit 52 clarifies the target segment and positioning through this STP organization process and selects appeal axes based on them. For example, when targeting a high-price segment, appeals emphasizing quality or authority are selected, while when targeting a low-price segment, appeals emphasizing price or cost performance are selected.

[0061] Figure 16 shows the details of segmentation and targeting for the embodiments shown in Figures 1 to 4.

[0062] Figure 16 illustrates the process of segmenting the market based on user criteria and then identifying segments where a USP (Unique Selling Proposition) can be effectively utilized (targeting). Figure 16 illustrates a 2x2 matrix. The vertical axis represents price (high price / low price), and the horizontal axis represents application (specialized / general purpose). This matrix allows the market to be classified into four segments: Segment 1 is "specialized x high price", Segment 2 is "general purpose x high price", Segment 3 is "specialized x low price", and Segment 4 is "general purpose x low price". Figure 16 illustrates a similar 2x2 matrix, showing which segment the company's service falls into. For example, if the company's service is positioned in the "application-specific x high price" segment, the appeal axis selection unit 52 selects appeal axes that emphasize specialization and high quality. The appeal axis selection unit 52 selects the appeal axis that best suits the characteristics of the target segment based on the results of this segmentation and targeting.

[0063] Figure 17 is a positioning map for the embodiments shown in Figures 1 to 4.

[0064] Figure 17 illustrates a positioning map, including competitors, to visualize the service's market position. This positioning map helps identify competitors with similar market positions that require particular attention. Figure 17 shows a 2x2 matrix. The vertical axis represents price (high price / low price), and the horizontal axis represents application (general purpose / specialized application). Four companies—our company, competitor A, competitor B, and competitor C—are plotted on this matrix. For example, our company is located in the "specialized application x high price" quadrant, competitor A is located in the "specialized application x high price" quadrant, competitor B is located in the "versatile x high price" quadrant, and competitor C is located in the "versatile x low price" quadrant. Figure 17 illustrates POINT 1 and POINT 2 as examples of how to determine the axes. POINT 1 involves selecting two particularly important Key Buying Factors (KBFs) derived from user research—the factors that determine service adoption—and setting them as the vertical and horizontal axes. In most cases, the vertical axis will be price. POINT 2 involves choosing two independent axes with as little correlation as possible. For example, using "price" and "high / low specifications" as axes tends to result in a polarization between "services with high prices and strong specifications" and "services with low prices and low specifications." Analyze the positioning using multiple factors. The appeal axis selection unit 52 selects appeal axes that differentiate the company from competitors in a similar position (e.g., competitor B) based on this positioning map. It also selects appeal axes such as expertise appeals and quality emphasis appeals that are suitable for the company's position (specialized application × high price).

[0065] Figure 18 is a diagram showing the WHO's organizational flow for the embodiments of Figures 1 to 4.

[0066] Figure 18 illustrates the WHO's organizational process, which involves determining target attributes from USP positioning, organizing them by funnel, and then increasing the resolution from there. The WHO's organizational process consists of three steps. The first step is to organize the target audience. In this process, for example, the attributes of the target audience are determined from the USP and positioning, and then organized according to the funnel. The first diagram in Figure 18 shows how the target audience is organized according to the funnel (potential audience, semi-real audience, real audience). The second step is persona creation. For example, persona creation involves refining the target's profile. This involves setting detailed characteristics such as age, gender, occupation, lifestyle, and values. Figure 18, specifically the second diagram, illustrates the process of creating a specific persona. The third step involves creating an empathy map. For example, creating an empathy map increases the resolution of the target's psychology. It involves deeply understanding what the persona thinks, feels, sees, and hears. Figure 18, the third diagram, shows how an empathy map is created. The information acquisition unit 51 stores detailed target information in the target information DB 72 through this WHO organization process. The appeal axis selection unit 52 selects the appeal axis that best resonates with the target's needs and psychological state based on this detailed target information.

[0067] Figure 19 shows the details of the target organization for the embodiments shown in Figures 1 to 4.

[0068] Figure 19 shows a table illustrating an example of target organization, combining the WHO classification of funnels (potential customers, semi-conscious customers, and visible customers) with attributes (marketing managers at business companies, department heads at advertising agencies). For marketing managers at businesses, potential users might have a vague sense of the problem, such as, "We want to increase video advertising, but outsourcing it every time is costly and time-consuming." They constantly feel the effort and lack of resources required for video creative production, but haven't yet thought of a clear solution. Semi-conscious users might start searching for an easier way to create videos and learn about video production platform services. They become interested in success stories from other companies and the ability to streamline production, and their interest deepens, thinking, "Maybe this will make my work easier?" In the explicit user group, they seriously consider how much more efficient their work can be by using the service as a means of solving specific problems, confirm the effects through free trials and demos, and gather evidence to persuade their colleagues. In the case of a department head at an advertising agency, the potential customer might be struggling with issues like, "I want to improve the quality of my creative proposals to clients, but it's difficult with our current resources." They aren't considering introducing new tools yet, but they would appreciate a more efficient method. The semi-active customer might start researching, for example, "Are there any tools that can increase production speed and reduce costs?" and learn about the service. They see the potential to strengthen proposals to clients and improve operational efficiency, and become interested, for example, thinking, "With this, I think I can make proposals that are competitive." The active customer might consider the specific implementation of the service to enhance the value of proposals to clients, confirm its ease of use and effectiveness through a trial, secure a budget, and proceed with implementation. The appeal axis selection unit 52 selects the most suitable appeal axis for each target group based on this funnel-based and attribute-based target organization. For example, appeals that empathize with the customer's concerns are effective for potential customers, while appeals that focus on offers or evidence are effective for existing customers.

[0069] Figure 20 shows the details of the empathy map for the embodiment shown in Figures 1 to 4.

[0070] Figure 20 illustrates an empathy map that focuses on the persona's "emotions and circumstances" to help understand the target more deeply. The empathy map is created from the perspectives of multiple individuals. An empathy map, for example, places an illustration of a persona in the center, with six areas defined around it. These are: 1. "Thinking," 2. "Seeing," 3. "Hearing," 4. "Words and Actions," 5. "Pain and Stress," and 6. "What is Gained." For example, in the "Thinking about" section, the following are listed: pressure regarding advertising costs (high advertising production costs and concerns about declining cost-effectiveness; therefore, constantly seeking more efficient advertising production methods), passion for work (a strong sense of responsibility to contribute to the success of the company and team through their marketing activities), and anxiety about lack of time (feeling frustrated about not having enough time to create ads themselves and wanting to improve efficiency). For example, the "Things I Look At" section includes information I primarily look at (frequently browsing LinkedIn® and industry information sites to gather the latest industry trends, developments, and competitor information), my work environment (digital advertising and marketing dashboards, performance metrics, and advertising cost management sheets), and my personal perspective (getting creative inspiration from movies and books). For example, the "things I listen to" category includes topics from the workplace (discussions with superiors and team members about reducing advertising costs or effective marketing methods), feedback from colleagues and the industry (feedback and word-of-mouth about marketing methods and advertising tools used by other companies and competitors), and things I listen to in my private life (movie plots, music, relaxed conversations with friends). For example, the "Words and Actions" category includes words and actions (many of which relate to cost and time, such as "I want to improve cost performance," "I don't have enough time," and "I want to focus on more creative strategies") and actions (searching for new advertising services and tools on LinkedIn, checking reviews and testimonials; going to cafes and movie theaters to relax in private). For example, in the "pain and stress" category, the following are listed: rising advertising production costs (high costs for advertising production putting pressure on the budget, which is the biggest source of stress), time constraints (not being able to dedicate enough time to advertising production, which is affecting other tasks), and pressure to deliver results (the success of the advertising strategy directly impacts the company's revenue, so there is strong pressure to deliver results). For example, the "What you gain" section lists what you will gain (by utilizing automated ad generation services, you can improve cost-effectiveness and save time, allowing you to focus on other tasks) and what you want (you want to acquire more efficient and creative ad production methods to strengthen your overall marketing strategy, and you also want personal growth and career advancement through success at work). The information acquisition unit 51 understands the target's deep psychology through such a detailed empathy map and stores it in the target information DB 72. The appeal axis selection unit 52 selects appeal axes that empathize with the target's pain and stress (empathy appeal) and appeal axes that appeal with what the target can gain (benefit appeal) based on this empathy map.

[0071] Figure 21 is a diagram showing the details of the advantages presented in the embodiments of Figures 1 to 4.

[0072] Figure 21 illustrates the details of one of the appeal axes: appealing for benefits. Appealing for benefits emphasizes the advantages that the user can directly gain, such as time savings, cost savings, and convenience. Figure 21 shows an example of promotional content that uses a benefit-focused approach. It includes the phrases, "For those who don't have time to dedicate to creative production," and "Create highly accurate personas in just 5 minutes!" Figure 21 shows a table illustrating the breakdown of the benefits, including the breakdown of the benefits, explanations, and examples. For time-related benefits, the focus is on reduced work time and increased efficiency, with "50% faster operation" listed as an example. For economic benefits, the focus is on cost reduction and energy-saving design, with "reduced running costs" listed as an example. For performance benefits, the focus is on high-speed processing and energy-saving design, with "30% improvement in processing speed compared to conventional models" listed as an example. For convenience, the focus is on mechanisms that reduce user effort, with "one-touch operation" listed as an example. Figure 21 lists the following as a GOOD POINT: "It allows you to directly communicate what problems the service solves, and clearly highlight its differentiating factors." When a benefit appeal axis is selected by the appeal axis selection unit 52, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt. For example, it inputs a specialized prompt such as "Generate an appeal that highlights the time benefit. Specifically, emphasize that persona creation can be completed in 5 minutes" into the AI(LLM) 4 and generates appeal content.

[0073] Figure 22 is a diagram showing the details of the benefit appeals for the embodiments shown in Figures 1 to 4.

[0074] Figure 22 illustrates the details of benefit appeals, one of the appeal axes. Benefit appeals emphasize the emotional and psychological satisfaction and benefits that come from using a product or service. Figure 22 shows examples of appeal content using benefit appeals. Examples of appeal text include "A must-see for marketing professionals," "Anyone can easily create advertising videos and still images with abundant templates," and "Rapidly implement creative PDCA!!" Figure 22 shows a table illustrating the breakdown of benefit appeals, including the breakdown of appeals, explanations, and examples. Functional benefits appeal to improved safety and convenience, with "a system that protects the safety of the family" as an example. Emotional benefits appeal to a sense of security and happiness, with "a comforting taste" as an example. Self-actualization benefits appeal to improved status and a sense of accomplishment, with "social recognition through owning a luxury car" as an example. Future-oriented benefits appeal to long-term satisfaction and a positive vision of the future, with "maintaining healthy skin in 5 years" as an example. Figure 22 lists the following as a GOOD POINT: "It can help users imagine a better future when using the service. It can reach a wider target audience than simply appealing to benefits." When a benefit appeal axis is selected by the appeal axis selection unit 52, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt. For example, it inputs a specialized prompt such as "Generate an appeal that appeals to emotional benefits. Specifically, emphasize the sense of security that comes from rapidly implementing the creative PDCA cycle" into the AI(LLM) 4 and generates appeal content.

[0075] Figure 23 shows the details of the emotional and psychological appeals in the embodiments of Figures 1 to 4.

[0076] Figure 23 shows the details of emotional and psychological appeals, one of the appeal axes. Emotional and psychological appeals are appeals that encourage users' psychological and emotional empathy and actions. Figure 23 shows an example of appealing content that uses emotional and psychological appeals. It includes appeals such as "A must-see for advertising managers" and "You don't have time to think up effective ad copy." Figure 23 shows a table illustrating the breakdown of emotional and psychological appeals, including the breakdown of appeals, explanations, and examples. Empathy appeals to recognition of the problem and emotional empathy, with "For busy people" as an example. Urgency encourages immediate action, with "Don't miss this opportunity" as an example. Sense of exclusivity involves appealing to limited quantities or time periods, with "Limited-time campaign" as an example. Loss / risk presents risks and disadvantages, with "You'll lose out if you don't take action" as an example. Figure 23 lists the following as a GOOD POINT: "When users feel that their concerns are understood, their trust in the service increases. It also has the effect of making users aware of their latent concerns." When an emotional / psychological appeal axis is selected by the appeal axis selection unit 52, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt. For example, it inputs a specialized prompt such as "Generate an appeal that appeals to empathy for a problem. Specifically, empathize with the problem that ad operators don't have time to think up ad copy" into the AI(LLM) 4 and generates appeal content.

[0077] Figure 24 shows the details of the offer appeal for the embodiment shown in Figures 1 to 4.

[0078] Figure 24 shows the details of offer appeal, one of the appeal axes. Offer appeal is an appeal that stimulates purchasing intent through benefits, campaigns, etc. Figure 24 shows an example of promotional content using an offer appeal. It includes the appeal text: "Your personal marketing assistant AI" and "First month free campaign underway." Figure 24 shows a table illustrating the segmentation of offer appeals, including the segmentation, explanation, and examples. Discounts are promoted as initial discounts and subscription discounts, with "20% off for first-time customers" as an example. Free shipping is promoted as reducing shipping costs, with "conditional free shipping" as an example. Benefits are promoted as providing additional value at the time of purchase, with "gift campaigns and point rewards" as examples. Free trials are promoted as offering the opportunity to try products or services for free, with "one-week free trial and free sample provision" as examples. Figure 24 lists the following as a GOOD POINT: "By offering specific benefits and incentives that encourage purchases, it immediately increases purchasing intent. This is particularly effective for those who are already aware of the service and have some understanding of it." When an offer appeal axis is selected by the appeal axis selection unit 52, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt. For example, it inputs a specialized prompt such as "Generate an appeal text that promotes the first month free campaign" into the AI(LLM)4 and generates appeal content.

[0079] Figure 25 is a diagram showing details of other appealing aspects of the embodiments shown in Figures 1 to 4.

[0080] Figure 25 illustrates the details of appeals to functionality / features and appeals to reliability. Functionality appeals emphasize the specific features and performance of a product or service, aiming to build trust. Functionality appeals can be further subdivided into basic performance (essential core functions and performance, e.g., high durability, waterproofing, improved processing speed), usability (e.g., ease of use and intuitive design, simple UI, one-touch operation), additional functions (optional functions that complement or extend basic performance, e.g., smartphone connectivity, app compatibility), quality emphasis (high quality, attention to materials and manufacturing processes, e.g., craftsmanship, top-quality materials), and innovation (introduction of new technologies, unique features, e.g., world-first technology, industry-first AI integration). Reliability appeals are appeals that enhance trustworthiness through track record and third-party evaluations. Breakdowns of reliability appeals include usage history (quantitative evidence such as number of users, number of companies using the product, and market share ranking; e.g., "200 companies using it," "top market share in the industry"), third-party evaluations (qualitative evidence such as expert recommendations, customer satisfaction ratings, and certification labels; e.g., "XX certification," "98% user satisfaction"), and guarantees and support (after-sales support and money-back guarantees; e.g., 30-day money-back guarantee). When the appeal axis selection unit 52 selects a function / feature appeal axis or a reliability appeal axis, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt.

[0081] Figure 26 is a diagram showing the details of the negative and comparative appeals for the embodiments shown in Figures 1 to 4.

[0082] Figure 26 illustrates the details of negative and comparative appeals. Negative appeals are those that present risks or disadvantages to encourage action. Breakdowns of negative appeals include economic risks (fear of loss or increased costs, e.g., high repair costs due to neglect), wasted time (continuing inefficient work, e.g., repetitive manual work), and health risks (deterioration due to neglect, e.g., health problems due to insufficient maintenance). Comparative appeals emphasize superiority by comparing a product with competitors' products or alternative products. Subdivisions of comparative appeals include direct competitive comparisons (comparison with competitors' products in the same category, e.g., "20% lighter than competitors' smartphones") and indirect competitive comparisons (comparison with products in different categories or alternative options, e.g., "e-readers are more convenient than paper books"). If a negative appeal axis or a comparative appeal axis is selected by the appeal axis selection unit 52, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt.

[0083] Figure 27 shows the details of the social contribution appeals for the embodiments shown in Figures 1 to 4.

[0084] Figure 27 shows the details of the appeal for social contribution. The appeal for social contribution emphasizes the social significance of environmental considerations, social contribution, sustainability, etc. The breakdown of appeals for social contribution includes environmental considerations (eco-friendly products and recyclable materials, e.g., environmentally friendly products), social contribution (contributing to local communities or specific issues, e.g., donating a portion of sales), and sustainability (supporting a sustainable future, e.g., contributing to CO2 reduction). When the appeal axis selection unit 52 selects a social contribution appeal axis, the appeal content generation unit 53 obtains such detailed information from the appeal axis DB 75 and generates a specialized prompt.

[0085] Figure 28 shows the psychological techniques according to the embodiments of Figures 1 to 4.

[0086] Figure 28 shows that more effective creative content can be created by combining psychological techniques with the appeal axis. Psychological techniques are classified into cognitive psychology (the workings of the human mind) and behavioral psychology (observable human behavior). Cognitive psychology has shown several phenomena, including the cocktail party effect (the psychology of being drawn to a particular message because it seems relevant to oneself), the halo effect (the psychology of a particular impression influencing the overall evaluation), the obedience principle (the psychology of trusting the opinions of experts or high-ranking individuals regardless of their credibility), the Barnum effect (the psychology of trusting vague appeals that apply to many people because they feel they have hit the nail on the head), the bandwagon effect (the psychology of feeling a sense of security and trust in opinions and actions supported by many people), and the Windsor effect (the psychology of trusting information disseminated by a third party more than information disseminated by the person involved). Behavioral psychology has shown several phenomena, including cognitive dissonance theory (the psychological tendency to take action to resolve contradictions when one perceives a contradiction in certain information), the Sho-Chiku-Bai principle (the psychological tendency to choose the middle option when presented with three plans), prospect theory (the psychological tendency to prioritize actions that avoid losses over actions that gain benefits), the Caligula effect (the psychological tendency to want to perform an action when it is prohibited or restricted), the Zeigarnik effect (the psychological tendency to want to take action when information is incomplete and one becomes curious about what happens next), and the snob effect (the psychological tendency to want to buy things that are scarce). The appeal content generation unit 53 can generate more effective appeal content by generating specialized prompts that combine psychological techniques in addition to the appeal axis. For example, a specialized prompt such as "Generate an appeal that utilizes the bandwagon effect in addition to appealing for benefits. Specifically, emphasize the track record of numerous companies that have adopted it." is input to the AI(LLM)4.

[0087] Figure 29 is a diagram showing an example of a still image layout for the embodiment shown in Figures 1 to 4.

[0088] Figure 29 shows four examples of layouts for still images used as promotional content. These include: 1) an advertising banner type, 2) a vertical layout, 3) a horizontal layout, and 4) a diagonal layout. The banner ad format is designed to follow the "Z-shaped" pattern of human eye movement. It is easy to understand even with a large amount of information. However, because it is a common format, users are more likely to recognize it as an "ad" and ignore it. Examples of banner ad formats include content such as "A must-see for marketing professionals," "Anyone can easily create ad videos and still images with abundant templates," and "Rapidly implement creative PDCA!!" Vertical division is effective when you want to clearly show two elements. It also makes it easier to convey both when making comparisons. However, because the message is divided vertically, it may be difficult to grasp the overall content at a glance. Examples of vertical division include appealing content such as "For those who don't have time to spend on creative production," "Do you think the accuracy of ad copy generated by AI is questionable?" and "Create highly accurate personas in just 5 minutes!" Horizontal layouts offer high readability due to their horizontal text format. They are preferred even in text-heavy advertisements. They are also suitable for creating a brand image and showcasing a product's world through larger images. However, care must be taken to avoid imbalances in the left and right elements, as this can easily disrupt the overall balance. An example of a horizontal layout is shown in the promotional content: "AI Marketing Assistant: Highly Accurate Generative AI Usable at a Practical Level" and "Implemented by Over 2,000 Companies!" Diagonal layouts can create a sense of dynamism and a stylish impression. Even just slanting the text and background can be effective. It's more innovative than other layouts, emphasizing uniqueness and design. However, it can sometimes be difficult for users to read. Examples of diagonal layouts include promotional content such as "A must-see for marketing professionals" and "Do you know about AI tools that can generate a large amount of video creative?". The user interface unit 54 displays the appealing content in various layouts, allowing the user to select the most suitable layout.

[0089] Figure 30 shows the AIBAC framework for the embodiments shown in Figures 1 to 4.

[0090] Figure 30 shows the AIBAC framework. AIBAC consists of four phases: A (Attention), I (Interest), B (Benefit), and AC (Action). In section A (Attention), a list of usable elements is provided, including clearly stating the target audience (e.g., Calling all recent graduates!), asking provocative questions (e.g., Are you still outsourcing video ads?), emphasizing novelty (e.g., Newly released! First in Japan!), and attracting attention with a ranking format (e.g., Top 5 best-selling winter cosmetics). In the "Interest" (I) section, elements such as clearly stating the cause of the problem (e.g., "You're not losing weight because of your nighttime eating habits"), attracting interest with large numbers (e.g., "Over 1,000 companies listed!"), communicating functional features (e.g., "Just swipe, simple UI"), and using the second person (e.g., "What you want to do is here") are indicated. In the B (Benefit) section, elements such as explicitly stating the desire for money (e.g., 0 yen commission!), appealing to the benefit with a percentage (e.g., 95% job placement success rate), evoking the growth of the target (e.g., accelerate your business), and clearly stating the conditions (e.g., monthly salary of 300,000 yen, no overtime) are shown. AC (Action) includes elements such as encouraging searches (e.g., Search for Richika if you're interested!), using quantitative data (e.g., Easy download in 30 seconds!), emphasizing free content (e.g., Register for free here!), and highlighting price (e.g., First time only from 890 yen!). The appeal content generation unit 53 can optimize the structure of the appeal content based on this AIBAC framework. For example, a specialized prompt such as "Based on the AIBAC framework, generate an appeal that clearly identifies the target in A (attention), identifies the cause of the problem in I (interest), identifies the desire for money in B (benefit), and appeals for free in AC (call to action)" is input to the AI(LLM) 4.

[0091] Figure 31 is a diagram summarizing the typical selling points of the embodiments shown in Figures 1 to 4.

[0092] Figure 31 shows how representative appeal axes are selected from persona and empathy maps to find the ones that resonate with the target audience. The appeal axes shown are: functional appeals (basic functions, additional functions, ease of use), merit appeals (performance benefits, economic benefits, time benefits), benefit appeals (functional benefits, emotional benefits, self-actualization benefits), prestige appeals (track record / history, third-party evaluations, customer testimonials / case studies), offer appeals (discounts, special offers, free shipping), empathy appeals (awareness of challenges, empathy for past failures, emotional empathy), and negative appeals (risk of economic loss, health risk, risk of wasted time). The appeal axis selection unit 52 refers to the system of appeal axes stored in the appeal axis DB 75 and selects appeal axes that resonate with the target based on the persona and empathy map information stored in the target information DB 72.

[0093] Figure 32 shows details and examples of the appeal axis for the embodiments shown in Figures 1 to 4.

[0094] Figure 32 shows specific examples of offer appeals and empathy appeals. Examples of offer appeals include promotional content such as "Your Personal Marketing Assistant AI" and "First Month Free Campaign." For example, the explanation of offer appeals states, "Communicate the financial benefits such as 'discounts and campaigns.' By presenting specific benefits and incentives that encourage purchase, it immediately increases the desire to buy. It is particularly effective for those who are already aware of the service or who have some understanding of it. This includes discounts, benefits, free shipping, cashback, and campaign appeals." Examples of appeals that resonate with people's concerns include content with themes such as "A must-see for advertising managers" and "You don't have time to think up effective ad copy." For example, the explanation of appeals that resonate with people's concerns is given as follows: "Communicate the 'worries and anxieties' that the target audience is facing. When users feel that their problems are understood, their trust in the service increases. It also has the effect of making users aware of their latent concerns. Awareness of challenges: 'Are you so busy with work that you can't do housework?' Empathy for past failures: 'Have you failed at dieting many times?' Empathy for emotions: 'Why not treat yourself to a luxurious moment?'" The appeal content generation unit 53 generates appeal content based on the appeal axis, taking these specific examples as reference.

[0095] Although one embodiment of the present invention has been described above, the present invention is not limited to the embodiments described above, and any modifications, improvements, etc. that can achieve the objectives of the present invention are considered to be included in the present invention.

[0096] Furthermore, the system configuration shown in Figure 2 and the hardware configuration of Server 1 shown in Figure 3 are merely illustrative examples for achieving the objectives of the present invention and are not particularly limited.

[0097] Furthermore, the functional block diagram shown in Figure 4 is merely illustrative and not particularly limiting. In other words, it is sufficient that the information processing system in Figure 2 has the functionality to execute the various processes described above as a whole, and the functional blocks and databases used to realize this functionality are not particularly limited to the example in Figure 4.

[0098] Furthermore, the location of the functional blocks and database is not limited to Figure 4, but can be any location. For example, at least a portion of the functional blocks and database located on the server 1 side may be provided on the user terminal 2 side, the external database 3 side, or other information processing device (not shown). For example, in the embodiment described above, AI(LLM)4 was located outside the server 1, but it is not limited to this and may be located inside the server 1.

[0099] Furthermore, the series of processes described above can be executed by hardware or by software. Furthermore, a single functional block may consist of hardware alone, software alone, or a combination of both.

[0100] When a series of processes are executed by software, the programs that make up that software are installed on a computer or other device from a network or storage medium. The computer may be a computer that is built into dedicated hardware. Furthermore, a computer can be any computer capable of performing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0101] Such recording media containing programs may consist not only of removable media (not shown) distributed separately from the main unit of the device to provide the program to the user, but also of recording media provided to the user in a state where they are pre-installed in the main unit of the device.

[0102] In this specification, the step of describing a program to be recorded on a recording medium includes not only processes that are performed chronologically in that order, but also processes that are not necessarily performed chronologically, but are executed in parallel or individually.

[0103] In summary, the information processing device to which the present invention applies only needs to have the following configuration, and can take various forms. That is, the information processing device to which the present invention is applied (for example, Server 1 in Figures 2 to 4) is: An information acquisition means (for example, the information acquisition unit 51 in Figure 4) acquires information about a specified product or service that the target audience wants to appeal to as the target of the appeal (for example, product information for the lotion "Moist Care" in Figure 1, and the target of the appeal information DB71 in Figure 4), and acquires information about the target audience as target information (for example, information on women in their 30s who suffer from dry skin in Figure 1, and the target information DB72 in Figure 4), A means for selecting appeal axes (for example, the appeal axis selection unit 52 in Figure 4) that, based on the appeal target information and the target information, selects from among a plurality of appeal axes that are suitable for appealing to the target (for example, the benefit appeal axis, evidence appeal axis, authority appeal axis in Figure 1, and the appeal axis system in Figures 6 and 27), using axes to which predetermined appeal characteristics are assigned as appeal axes, and A means for generating appeal content (for example, the appeal text "For moist skin that never dries out..." in Figure 1) that generates content that includes content to appeal to the target audience with the appeal characteristics corresponding to the selected appeal axis, Having that will suffice.

[0104] In this way, a framework and workflow that systematizes multiple appeal axes makes it possible to reliably select the optimal appeal tailored to the product and target audience.

[0105] Furthermore, the aforementioned multiple appeal axes may include functional feature appeal axes (e.g., functional / feature appeals in Figure 6), benefit appeal axes (e.g., benefit appeals in Figure 6), price appeal axes (e.g., discounts and price-related appeals in offer appeals in Figure 6), authority appeal axes (e.g., third-party evaluations in reliability appeals in Figure 6), benefit appeal axes (e.g., benefit appeals in Figure 6), evidence appeal axes (e.g., usage history in reliability appeals in Figure 6), scarcity appeal axes (e.g., sense of exclusivity in emotional / psychological appeals in Figure 6), and social proof appeal axes (e.g., usage history and third-party evaluations in reliability appeals in Figure 6).

[0106] This allows for the systematic organization of multiple appeal axes, enabling the response to various appeal patterns and allowing for more effective appeals to a wider range of targets and products.

[0107] Furthermore, the appeal axis selection means can acquire information about competitors as competitive information (for example, information on competitor lotions A, B, and C in Figure 1, and the competitive information DB73 in Figure 4) in addition to the appeal target information and the target information, perform a positioning analysis (for example, the 3C analysis in step S3 of Figure 1, and the positioning in Figure 8) based on the competitive information, and select the appeal axis based on the results of the positioning analysis.

[0108] This allows for positioning analysis that incorporates competitive information, enabling the selection of appeal points that differentiate the product from competitors, and thus enabling more effective marketing.

[0109] Furthermore, the appeal content generation means can generate the appeal content by inputting a specialized prompt corresponding to the selected appeal axis (for example, "Generate an appeal text for lotion targeting women in their 30s with dry skin, focusing on benefits" in step S5 of Figure 1) into a large-scale language model (for example, AI(LLM)4 in Figure 2).

[0110] This allows for the automatic generation of high-quality, targeted persuasive content by controlling large-scale language models with specialized prompts, significantly reducing the amount of work required.

[0111] Furthermore, the system may further include a user interface means (for example, the user interface unit 54 in Figure 4, and the user interface screens in Figures 22 to 25) that displays the promotional content generated by the promotional content generation means in a way that allows the user to review and edit it.

[0112] This allows users to review and edit the generated promotional content, enabling fine-tuning that wouldn't be possible with full automation, and allowing for the creation of promotional content that is more practical and suitable for real-world use.

[0113] Furthermore, the appeal axis selection means can perform target analysis (for example, the target insight analysis in step S3 of Figure 1, and the target analysis process in Figures 18 to 21) based on the target information, and select the appeal axis based on the results of the target analysis.

[0114] This allows for target analysis, enabling the selection of appeals based on an understanding of the target audience's attributes and needs, resulting in more targeted and effective messaging.

[0115] Furthermore, the information acquisition means can acquire market analysis data from an external database (for example, external database 3 in Figure 2, market analysis data DB74 in Figure 4), and the appeal axis selection means can further use this market analysis data to select the appeal axis.

[0116] This makes it possible to acquire market analysis data from external databases and use it to select appeal points, thereby enabling appeals that reflect market trends and consumer behavior.

[0117] Furthermore, the system may further include data storage means (for example, data storage unit 55 in Figure 4) that associates the appeal target information, the target information, the selected appeal axis, and the generated appeal content and stores them in a database (for example, the appeal content DB 76 in Figure 4).

[0118] This allows for the analysis of past sales performance by linking and accumulating marketing data, thereby accelerating the hypothesis testing and improvement processes. [Explanation of Symbols]

[0119] 1...Server, 2...User terminal, 2-1...User terminal, 2-2...User terminal, 2-n...User terminal, 3...External database, 4...AI (LLM), 11...CPU, 12...ROM, 13...RAM, 14...Bus, 15...Input / Output interface, 16...Input unit, 17...Output unit, 18...Storage unit, 19...Communication unit, 20...Drive, 21...Removable media, 51...Information acquisition unit, 52...Appeal axis selection unit, 53...Appeal content generation unit 54...User Interface Section, 55...Data Storage Section, 71...Target Information DB, 72...Target Information DB, 73...Competitor Information DB, 74...Market Analysis Data DB, 75...Appeal Axis DB, 76...Appeal Content DB, N...Network, S1...Product Information Registration, S2...Information Acquisition and Analysis, S3...Target Analysis and Positioning Analysis, S4...Appeal Axis Selection, S5...Appeal Content Generation, S6...Data Storage, S7...Display and Editing in User Interface

Claims

1. An information acquisition means that acquires information about a specified product or service that the target audience wants to appeal to, as the target information, and acquires information about the target audience as the target information, A means for selecting an appeal axis from among a plurality of appeal axes, based on the appeal target information and the target information, using an axis to which a predetermined appeal characteristic is assigned as an appeal axis, the appeal axis being suitable for appealing to the target, and A means for generating appeal content that generates content to appeal to the target audience with the appeal characteristics corresponding to the selected appeal axis, An information processing device equipped with the following features.

2. The information processing apparatus according to claim 1, wherein the plurality of appeal axes include a functional feature appeal axis, a merit appeal axis, a price appeal axis, an authority appeal axis, a benefit appeal axis, an evidence appeal axis, a rarity appeal axis, and a social proof appeal axis.

3. The information processing device according to claim 1, wherein the appeal axis selection means acquires information about competitors as competitive information in addition to the appeal target information and the target information, performs a positioning analysis based on the competitive information, and selects the appeal axis based on the results of the positioning analysis.

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