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With the spread of generative AI and AI search, manufacturing industry websites are experiencing a phenomenon where "there is a lot of information, yet inquiries are decreasing." The main cause lies not in the quality of the content, but in the "structure that is not read or is misread by AI." This service disassembles your company's website with the premise that AI will reference, summarize, and compare it, visualizing where evaluations drop, where drop-offs occur, and why it does not lead to inquiries or appointments, prioritized for improvement. This is a diagnostic service aimed at companies that want to first confirm "whether a renewal is necessary" and "where to fix it for the quickest return." ▼ For concerns like these: - Even though we are doing SEO, inquiries are not increasing or are decreasing. - We have product pages, but we feel we are not being chosen in comparisons. - Information is misaligned in AI summaries, and strengths are not conveyed. - We cannot reach an agreement within the company on renovations and cannot decide what to fix first. - Sales materials, case studies, and strengths are not linked on the web. Would you like to first confirm "what to fix to get back on track"? If you share the current URL, we will quickly organize the "causes of drop-offs in AI search" specific to your company and guide you on how to proceed with the diagnosis.

The reason why the web for manufacturing does not "work despite being created" lies not in the amount of information but in its "structure." In the era of AI search and generative AI summarization, the way sites are read changes, and companies whose strengths are not accurately recognized will quietly be removed from consideration. This GEO diagnosis inspects your site on the premise that AI will evaluate, summarize, and compare it, visualizing the causes of any losses with prioritized insights. ■ Provided Content (3 points) - Structural check of AI evaluation criteria (definitions, headings, information layout, FAQs, internal navigation) - Extraction of improvement points by important pages (top, products, case studies, document downloads, etc.) - Improvement priorities arranged by impact and effort (Quick Wins / Medium-term design) Deliverables: GEO diagnosis report (list of issues, priorities, improvement instructions) + next action proposals Scope / Premise: The target URL is generally limited to "up to 10 main pages" (exceeding this can be accommodated with an extension). *Please send us the URL first. We will provide an initial assessment (where the issues lie) and the scope of the diagnosis.

"Even though there is a website, inquiries are not increasing" — the cause is not the amount of information but rather "insufficient structural design." With the spread of generative AI and AI search, users narrow down their options based on AI summaries and comparison results without loading pages. Websites with weak structures quietly fall out of consideration, even if they have good technology. This service redesigns the web structure to communicate effectively to both AI and humans, taking into account your company's sales realities, product characteristics, and decision-making processes, and helps determine "which pages to present, in what order, and what to say to win." ■ Provided Content (3 Points) - Organization of business, products, and customers (winning strategies/selection criteria/objection handling points) - Redesign of information structure and navigation (sitemap/page roles/user flow/CTA) - Creation of outlines for key pages (heading structure/persuasive axes/FAQ/case study placement) Deliverables: Redesign report (To-Be structure) + sitemap + key page outlines + improvement roadmap Scope/Assumptions: Design centered around key pages (home + product groups + case studies + document downloads, etc.) (actual production is separate) *Please first share the current URL and product. We will organize the current "structural defects" and provide guidance on the redesign.

The reason for the lack of inquiries is not the quality of the website, but rather that "sales and the web are treated as separate entities." In the era of generative AI and AI search, users compare options "before reading" and narrow down their choices before meeting with sales. Nevertheless, companies that do not reflect the winning strategies (effective explanations, selection criteria, and handling objections) from the sales field on their websites are less likely to convey their strengths and may be excluded from consideration. In this service, we will break down your sales process and structure "who is confused by what and how they decide." We will redesign the web as the "pre-sales process" and design "definitions, comparison axes, and pathways" that align even with AI summaries. ■ Service Offerings (3 points) - Structuring sales interviews (winning strategies, reasons for lost sales, handling objections, selection criteria) - Redefining the role of the web (entry → deep dive → comparison → consultation) and designing pathways - Designing "decision-making components" for product pages, case studies, downloadable materials, and FAQs Deliverables: Integrated design document for sales and web (pathways, page roles, comparison axes, content design) Scope/Assumptions: Sales interviews (60–90 minutes × 1–2 sessions) + design of key pages (production is separate) *Please first share the current URL along with the product and target audience. We will organize the bottlenecks in the sales pathway and the missing components on the web to provide our proposal.

The reason is simple: both decision-makers (humans) and generative AI judge companies based on "structure." This service will inventory your company's business, products, customers, strengths, and sales processes, and distill **"who," "what," and "why your company can win"** into a single structural diagram. This will align the standards for communication and pathways across web, sales, materials, and recruitment, creating a foundation for a company that "remains" in comparative evaluations. ■ Provided Content (3 points) 1. Organization of business, products, and customers (value offered / usage / selection criteria / winning strategies) 2. Visualization of the sales structure (leads → initial contact → comparison → approval process → decision-making bottlenecks) 3. Integration of communication structure (role design for web / proposal materials / case studies / FAQs) Deliverables: Corporate Structure Map (Business × Sales) + Message Outline + Prioritized Improvement Roadmap Scope/Assumptions: Organizing based on 60-90 minute interviews × 1-2 times + existing materials (website/sales materials/proposals, etc.) *Please share the current URL and products. We will organize the structural misalignments (causes of miscommunication) and the axes that need to be aligned.

The reason why B2B web and sales efforts are ineffective is that "customer understanding design" is missing before implementing measures. Decision-makers are not just one person; they compare based on different axes such as technology, purchasing, on-site operations, and management. If you create pages or materials without capturing this, even if the amount of information increases, it won't resonate, and you will quietly continue to lose in the comparison process. This service is designed to establish a "foundation" for improving the accuracy of subsequent web design, proposal materials, and content production, based on the target customers' consideration process (DMU) and purchasing journey, specifically focusing on **"what to verify, with whom, and in what order."** ■ Provided Content (3 points) - Hypothesis organization (target/issue/selection criteria/competitive comparison axes) - Research design (research items, methods, samples, question design) - Connection design to measures (translation of messages, content, and pathways) Deliverables: B2B customer understanding research design document (hypotheses, design, questionnaire/guide, analysis framework) Scope/Assumptions: Primarily "up to design" (actual research = conducting interviews/surveys/log analysis is a separate option) *Please share the current URL, product, and assumed target. We will start organizing from the "hypotheses to be verified" as soon as possible.*

B2B lost opportunities occur not due to product strength, but because of a "lack of comparison pathways." Once customers enter the comparison stage, they begin to look for "reasons not to buy" rather than "reasons to buy." Nevertheless, many sites stop at product introductions and lack the necessary information for approvals and decision-making (such as handling objections, reassurance materials, selection criteria, and implementation conditions). As a result, potential candidates are eliminated with the thought, "I understand the benefits, but..." In this service, we design information architecture and pathways (what to show next and what to resolve) to win in comparisons, based on your products and the customer's decision-making process, creating a "structure of decisive factors" that leads to inquiries and business discussions. ■ Provided Content (3 points) Identification of bottlenecks in comparison (reasons for lost opportunities / anxiety factors / barriers to approval) Design of decision-making components (selection criteria, FAQs, case studies, materials, guarantees/support) Pathway design (designing the flow from product → comparison → reassurance → approval → consultation) Deliverable: Decision-making pathway design document (pathway diagram, page roles, content list, priorities) Scope/Assumptions: Focused on designing the main pathways (product page group + case studies + FAQs + material downloads + inquiries) (production is separate) *Please share the current URL and product. We will organize the "causes of lost opportunities in comparisons" and the missing decision-making components and provide suggestions.

In the era of AI search and generative AI summarization, the success of a website is determined not by individual pages but by the "sitemap (overall structure)." Users are no longer browsing, and AI attempts to understand the entire site as a "structure." Despite this, outdated websites have a mix of "business, products, case studies, and materials," leading to an ambiguous role for pages as they proliferate. As a result, strengths are overlooked, making it easier for candidates to be eliminated during comparisons. Our service will redesign the overall structure of your site (page roles, hierarchy, navigation, naming) based on your business, products, and sales pathways, creating a foundation for a "chosen structure" in the shortest time possible. ■ Service Offerings (3 points) 1. Current sitemap diagnosis (overlapping, missing, and confusing page roles) 2. To-Be sitemap design (hierarchy, naming, navigation, and CTA design) 3. Implementation roadmap (prioritization of where to start for effective changes) Deliverables: To-Be sitemap (design version) + page role definitions + improvement roadmap Scope/Assumptions: Primarily up to design (actual production and CMS implementation are separate) / includes major pathways (products, case studies, materials, inquiries) in the design *Please share the current URL. We will organize and guide you on the structural defects and the most effective order for redesign.

Even if people come through search, they often leave without exploring further—this is the biggest loss for manufacturing websites. In the era of generative AI and AI search, users skim through pages and will quickly leave if they cannot find the next piece of information to read. Many sites end up with their search entry pages being "just explanations" and fail to guide users to the in-depth information necessary for comparison (such as applications, selection criteria, case studies, FAQs, and materials). This service is designed with the assumption of user behavior after search entry, intentionally creating "the next page to show" and establishing a navigation flow from entry to in-depth exploration, comparison, and consultation. ■ Provided Content (3 Points) 1. Clarification of the role of the search entry page (questions to resolve at the entry point / design of the next questions) 2. Design of the in-depth exploration flow (connections to related pages, comparison axes, and decision-making components) 3. Template for navigation rules (a model that can be horizontally expanded across product page groups) Deliverables: Navigation design document (flowchart, related link design, template) + priority list Scope/Assumptions: Design from major entry pages (approximately the top 10 pages) (scope can be expanded) / Implementation will be handled separately. *Please share the current URL. We will organize the "reasons for drop-off" on the entry page and identify the potential for the in-depth exploration flow.

The shortest route to stabilize B2B inquiries is to increase the number of branded searches (being searched by company name or service name). When branded searches increase, it becomes less likely to get caught up in price competition, and it gains an advantage in comparison considerations. However, many manufacturing sites have strong technology but fail to leave a lasting impression on "what their strengths are and what problems they solve for whom," resulting in a lack of reasons for revisits. This service is designed with the premise of the customer's comparison process, creating a foundation that leads to branded searches, revisits, and inquiries through the structure of **"memorable definitions" and "desirable pathways for revisits."** ■ Provided Content (3 Points) 1. Identification of the causes for the lack of branding (insufficient definitions/differentiation unclear/lack of memory hooks) 2. Design of a memorable structure (core messages, comparison axes, naming, page roles) 3. Design of revisit pathways (designing "return points" to case studies, FAQs, materials, and comparison pages) Deliverables: Structural design document for increasing branded searches (definition statements, comparison axes, pathways, page design) Scope/Assumptions: Up to design (production is separate)/Focus on top + main pathways (products, case studies, materials, inquiries) *Please share the current URL and products. We will organize the "causes of being unmemorable" and the structure that generates branding.

The reason for losing in competitive comparisons is not the performance difference, but rather that "the structure of the appeal does not withstand comparison." B2B purchasing involves multiple people (technical, field, purchasing, management) comparing on different axes, and ultimately, the decision is made based on whether "it can be approved without concern." Nevertheless, many sites simply list specifications and strengths, lacking the axes for comparison (selection criteria) and rebuttal handling (addressing concerns). In this service, we will translate the winning strategies of your products into "comparison axes" and design an appealing structure (order of presentation, evidence, wording) that highlights strengths even when placed alongside competitors. ■ Provided Content (3 points) - Identification of losing patterns in competitive comparisons (reasons for lost orders/comparison axes/misunderstanding points) - Structuring of winning strategies (differentiation axes, evidence, rebuttal handling, materials for approval) - Design of appeal templates (product pages/case studies/FAQs/document formats) Deliverables: Appeal structure design document (comparison axes, messages, evidence design, page outline) Scope/Assumptions: Design centered on 1-2 main products (expandable)/Production and implementation are separate. *Please share the current URL and competitors (as far as you know). We will organize the reasons for losing in comparisons and identify "winning appeal axes."

In the era of generative AI and AI search, the evaluation and understanding of text depend not on the quality of the writing but on the "structure of information." AI does not read the entire text carefully; instead, it summarizes based on clues such as headings, definitions, relationships, and comparison axes, presenting candidates. Texts with ambiguous structures may lose their strengths or be summarized on par with competitors, putting them at a disadvantage in comparisons. This service involves "structural rewriting," which reorganizes existing pages into a form that is "not misread by AI and can be communicated instantly to people," including the design of headings, definitions, comparison axes, and the order of evidence. ■ Provided Content (3 Points) - Identification of causes for discrepancies in summaries (insufficient definitions/unclear relationships/insufficient evidence/inappropriate order) - Structural rewriting (redesign of headings, key points, comparison axes, FAQs, and case study pathways) - Template creation for horizontal deployment (creating a format that can be applied to similar pages) Deliverables: Rewritten manuscript with structural headings + list of improvement points + applicable template Scope/Assumptions: Initially targeting 3 to 5 main pages (expandable) / Implementation (CMS reflection) is separate or handled by your company. *Please share the target URL. We will identify the "areas where you are losing out" in AI summaries and propose the most effective rewriting scope.

B2B inquiries often increase from "problem pages (entry points based on issues)" rather than product pages. Customers do not start by searching for product names. They gather information using problem-related keywords such as "defect rate," "delivery delays," "cost," "inspection," and "quality assurance," and then enter the comparison phase. In the era of AI search, these entry pages become subjects for summarization and comparison, and if their structure is weak, they will be excluded from the candidates. Our service designs landing pages (problem-specific LPs) centered around customer issues, including definitions, comparison axes, and evidence that will not be misinterpreted by AI, creating a pathway from entry to deep exploration, comparison, and consultation. ■ Provided Content (3 points) 1. Problem theme design (hypothesis design for targeted issues, search intent, and comparison axes) 2. LP structure design (situation → disadvantages → solutions → evidence → decision-making → CTA) 3. Existing asset connection (shortest pathway to products, case studies, FAQs, and document downloads) Deliverables: Problem-specific LP design document (structure, headings, appeals, pathways, CTA) + draft outline Scope/Assumptions: Design starting from one theme (one LP) (expandable) / Production and implementation are separate *Please share the product and the issues (or problems) you want to target. We will organize from the "most impactful entry theme" as quickly as possible.

The web for BtoB manufacturing often fails to prompt "action" even when the information is correct. The reason is that there is no necessary psychological support designed to address the anxieties (failure, approval processes, responsibility, internal coordination) that users face during comparison and consideration. Our service will improve your copy to ensure that "readers can take the next step," based on your products, customers, and sales processes, from the perspective of behavioral economics and marketing psychology. This is not just a simple rephrasing of text; it includes the design of headlines, order, rationale, and CTAs, transforming it into a format that generates inquiries. ■ Service Contents (3 points) 1. Identify issues with the current copy (anxiety factors, points of misunderstanding, lack of decisive factors) 2. Design psychological triggers (phrasing and order that advance comparison and consideration) 3. Improve CTAs (design to elicit consultation permissions and next actions) Deliverables: Improved copy proposals (headlines, body text, CTAs) + list of applicable triggers + horizontal expansion rules Scope/Assumptions: Initially focusing on the main 1-3 pages (top, product, document download, etc.) with potential for expansion. *Please share the target URL. We will quickly assess "what to change and how to prompt action" and provide our suggestions.

In the era of generative AI and AI search, FAQs will become the foundation of AI responses (primary source) rather than just "frequently asked questions." AI will refer to the FAQs and definitions on corporate websites to answer users' inquiries and assist in comparing options. Companies with weak FAQs are likely to have answers sourced from other sites, leading to their strengths and conditions not being accurately conveyed, resulting in them being eliminated from consideration. This service will focus on the common concerns that arise in B2B manufacturing comparisons (quality, delivery time, structure, costs, implementation conditions) and will design an FAQ structure that can be clearly understood by both AI and humans, providing reassurance that leads to inquiries and business negotiations. ■ Provided Content (3 points) 1. Question Design (extracting concerns related to comparisons = points for counter-argument processing) 2. Answer Design (structuring the order of definitions, conditions, exceptions, and evidence) 3. Flow Design (designing the "next action" that connects to product pages/case studies/document downloads) Deliverables: FAQ design document + structured FAQ draft + page connection diagram (indicating where to reference) Scope/Assumptions: Initially recommend 20 to 40 questions (expandable) / Implementation (CMS reflection, schema support, etc.) will be handled separately. *Please share the target URL and products. We will organize the necessary FAQs starting from the "questions" that stop at comparisons.

The more product items there are, the results on the web are determined by "database design." In the era of generative AI and AI search, AI does not read product pages individually; instead, it references product information as a "data structure" for comparison, summarization, and recommendations. However, many manufacturing websites have inconsistent item names, variations in notation, missing usage or selection criteria, and non-uniform specification granularity, making it difficult for both AI and humans to compare. As a result, strengths are overlooked, and products are eliminated from consideration. This service will redesign product information with the premise of being "searched, compared, and summarized," creating a product database that is strong in AI reference (item design, granularity unification, naming rules, associations). ■ Provided content (3 points) 1. Current database inventory (identifying missing items, notation variations, and granularity inconsistencies) 2. Information design (designing essential items, selection criteria, usage, and comparison axes) 3. Operational rule design (standardizing input conventions, naming, categories, and association rules) Scope/Assumptions: From design to operational rules (implementation/CMS modifications and migration work are separate) / The number of target products will be adjusted according to scale. *Please share the current product list (CSV/Excel acceptable) or URL. We will organize the defects and improvements as a database.

In the B2B manufacturing industry, the success of business negotiations is determined more by the "way of conveying reproducibility" than by the number of cases. In situations of comparison and consideration, what customers want to know is not "impressive achievements," but whether it will truly work under conditions similar to their own. However, many case study pages merely list company names and results, lacking details on conditions, reasoning, and implementation processes. As a result, they do not provide reassurance and cannot be used in decision-making processes. Our service will design a case study page format that structures industry × scale × challenges × conditions × measures × results, while maintaining confidentiality, to ensure that potential clients think, "This company can also succeed." ■ Provided Content (3 points) 1. Design of case study "conditions" (which conditions to present to convey reproducibility) 2. Structure design of case study pages (effective order, headings, and placement of evidence for comparison) 3. Template creation for mass production (creating a format that maintains quality even as the number of case studies increases) Deliverables: Case study page template (structure, headings, input items) + case study draft template + flow design Scope/Assumptions: Initially, template design + creation of 1 to 3 representative case study templates (expandable) / implementation to be handled separately *Please share the current URL (if there are case studies) and the products. We will organize based on the "missing elements" of effective comparison case studies.

GEO (Structural Optimization for AI Reference) will fail if started haphazardly. The reason is that initiatives tend to be scattered, and if you miss the "critical points of structure" that are effective in AI summarization and comparison, you won't achieve results even if you invest effort. This service is specifically tailored for B2B in the manufacturing industry, providing starter support to streamline the shortest route for GEO from "diagnosis → prioritization → initial implementation" all at once. First, we will establish a foundation that leads to inquiries by preparing a definition (company/product/application) that won't be misinterpreted by AI and the necessary decision-making materials (selection criteria, FAQs, case study pathways) in a minimal configuration. ■ Provided Content (3 Points) GEO Quick Diagnosis (Identification of structural defects and "areas of loss") Initial Design (Definition statements, comparison axes, pathways, priority roadmap) Initial Implementation Support (Structural rewriting of key pages/Minimum maintenance of FAQs and pathways) Deliverables: GEO Starter Pack (Diagnosis report + Initial design document + Key page improvement proposals) Scope/Assumptions: Initially, we standardize around "approximately 5 key pages + 20 FAQs" (adjusted based on scale) *Please share the URL. We will present the current "GEO hindering factors" and the initial scope that will be most effective in the shortest time.

The main reason why content strategies do not last is not "the act of writing," but rather the lack of a "management framework." In B2B manufacturing, as the number of products increases and more information such as applications, case studies, FAQs, and documents accumulate, inconsistencies in terminology, varying levels of detail, and broken navigation occur. In the era of AI search, this directly leads to a "decrease in reference quality," putting you at a disadvantage in summarization and comparison. This service is designed to manage content not by creating it "point by point," but by establishing a structure (templates, input guidelines, tags, approval flows) that allows for consistent quality even when mass-produced. ■ Provided Content (3 points) 1. Content system design (organizing what types of content should be held) 2. Template and input guideline design (standardizing detail levels, preventing terminology inconsistencies, defining mandatory items) 3. Operational flow design (role division and rules for creation → review → publication → improvement) Deliverables: Structured content management design document (system, templates, guidelines, flow) + complete checklist Scope/Assumptions: Up to the design phase (actual operational support is a separate option) / Optimized to fit existing CMS and organizational structure *Please share the current URL and your internal update structure (number of responsible personnel and frequency). I will promptly identify the "causes of collapse" and propose a management framework.

GEO (Structure Optimization Referenced by AI) is not a one-time task that is completed once it is set up. The search intent, competition, AI reference trends, and internal product information are constantly changing. If you cannot keep up with these changes, the structure you thought was organized will quickly collapse, and the issue of candidates falling out during comparisons will reoccur. This service provides ongoing support tailored to the practical needs of B2B manufacturing, cycling through "Prioritization → Improvement → Verification" every month to continuously update the structure that leads to inquiries and business negotiations. It increases the "frequency of improvements," which tends to stagnate within the company, and maintains a state where results are achieved. ■ Provided Content (3 Points) Monthly Priority Design (Determining what needs to be done this month based on Impact × Workload) Improvement Execution Support (Structure rewriting / FAQ expansion / Pathway and CTA improvements / Case study development) Verification and Next Steps (Observing responses and connecting to next month's improvement themes) Deliverables: Monthly Improvement Report (Implementation details, effects, next month's plan) + Improvement drafts/instructions Scope/Assumptions: Monthly regular meetings (60–90 minutes) + improvement tasks (scope adjusted based on the plan) *Please share the current URL and issues (such as reduced inquiries, losing comparisons, etc.). We will design the "most effective order of improvements" in the first month.

Many websites are created from "means" rather than "purpose." As a result, they end up being sites that serve no one. At And One, unlike the typical approach where "creating" becomes the goal, we consistently structure a "process for achieving results." That is the "And One Method." *For more details, please download the PDF or feel free to contact us.*

This document is a white paper aimed at organizing the structural reasons behind "what is valued in the AI era and why many web initiatives have ceased to function." It provides a detailed explanation of the evaluation (points) of the past and the evaluation (structure) in the AI era, as well as the structural consistency of the entire company as seen by AI, and the true web redesign process. AndOne is not a company that "creates" websites. We are a partner that organizes the structures of sales, business, and information, and designs the web by working backward from results. [Contents (partial)] ■ Introduction | Why have improvements to the web stopped yielding results? ■ The real changes occurring in the AI era ■ AI evaluates "companies" rather than "content" ■ Failures of companies where the sales structure and web are disconnected ■ Why have "correct web initiatives" stopped producing results? *For more details, please download the PDF or feel free to contact us.

This document provides a detailed explanation of the new fundamentals of customer acquisition that small and medium-sized enterprises should know now. We also introduce the benefits that GEO brings to companies, such as being "chosen even without being searched," the knowledge of all employees being turned into assets, and long-term evaluations that do not decline. AI tools like ChatGPT, Gemini, and Copilot are looking for "reliable sources of information to generate answers." As a result, the need for GEO (Generative Engine Optimization) has arisen. GEO is a mechanism that allows companies to gain trust by being cited by AI. 【Contents (partial)】 ■ Introduction | The End of the SEO Era and the Emergence of "GEO" ■ Vol.1 From "Discovery" to "Trust" in the AI Era ■ Vol.2 The Shift in Search from "Human → AI" ■ Vol.3 The Core of GEO is Creating "Reasons to be Cited" ■ Vol.4 Fighting in a "Forest of Context" Rather than a Sea of Information *For more details, please download the PDF or feel free to contact us.

Many companies consider the web to be a "repository of information." If you line up the necessary information such as company overview, service introduction, product list, and recruitment information, it will be conveyed. Most websites are built on this premise. However, this way of thinking is the biggest reason for the lack of results. In this white paper, we carefully dismantle the "illusions" that companies are prone to fall into and clarify the underlying laws of success. [Contents] ■ Why 99% of companies are mistaken ■ Analysis of types of illusions ■ The tragedies brought about by illusions ■ The laws of reality ■ The "thinking patterns" of successful companies ■ And One's approach (philosophical perspective) *For more details, please download the PDF or feel free to contact us.

This book is not a book that provides answers. It is a "diagnostic report" to calmly verify whether your company is an explainable entity for AI. It clearly explains the reasons why, even with technology, AI may not favor you, and the logic behind why AI includes certain candidates in its "recommendations." If you find yourself feeling uncomfortable while reading or become anxious about your company's website, that is not a problem. The fact that you have realized this is already a significant step. 【Contents】 ■ How does ChatGPT perceive "companies"? ■ Seven common structures of "companies not evaluated" by ChatGPT ■ The moment ChatGPT determines "this company is trustworthy" ■ What manufacturing websites are fundamentally getting wrong right now ■ So, how can you become a "company not disliked by AI"? ■ Why AndOne can write on this topic *For more details, please download the PDF or feel free to contact us.

Due to the spread of generative AI and AI search, a phenomenon is occurring in the textile industry where "catalog information is available, yet direct searches and sample requests are declining." The main reason for this is that the uniqueness of craftsmanship and fabrics is structured in a way that "cannot be read by AI or is summarized as generalities." This service thoroughly analyzes your company's website based on the logic of "AI comparing and recommending materials." It visualizes where strengths are being diminished and why recommendations are being taken away by competitors, along with specific improvement measures. ▼ For concerns like these: - When searching for "material name + function," recommendations are for other companies or summary sites instead of your own. - The unique texture and processing techniques are summarized by AI as "general characteristics." - While there is a specification sheet (mixing ratio, weight, etc.), AI does not recognize it as a "strength." - Information on sustainability and certifications (like GRS) is missing from AI search comparisons. - Although there are inquiries at exhibitions, there are no sample requests or new inquiries coming through the web. This is a diagnostic package that determines whether to "renew" or "how to rewrite existing specification sheets" from the perspective of data in the AI era, based on design principles.

Designers and purchasing agents are now narrowing down their inquiry candidates by looking at the "comparison tables" generated by AI searches. However, many semiconductor-related sites are experiencing significant missed opportunities because, despite having excellent specifications, they have a structure that "AI cannot extract data from," preventing them from even entering the arena for comparison. Our service analyzes your site based on the "algorithm that AI uses for device selection." We will quickly present why your technology is not being recommended and what changes need to be made to connect to targeted searches. ▼ Are you facing these issues? - When searching for "specific technology + material," only competitors are recommended. - Technical documents are locked in PDFs, preventing AI from reading their content. - AI incorrectly determines that your company's capabilities are "not possible." - Although SEO measures have been taken, other companies are cited in AI overviews. Would you like to optimize for the "spec sheets of the AI era"? If you share your current URL, we will quickly organize the "opportunity loss points in AI searches" for your site and guide you on how to proceed with the diagnosis.

Due to the proliferation of generative AI and AI search, the food industry is experiencing a phenomenon where "product information is comprehensive, yet inquiries and consideration for adoption are decreasing." Much of the cause lies in the structure where the depth of flavor and quality commitment are "not readable by AI or are processed as the same general statements as those of competitors." This service analyzes your company's website using a "logic that allows AI to compare and recommend ingredients and suppliers." It visualizes where differentiation elements disappear and why competitors are proposed first, along with improvement priorities. ▼ For concerns like these: - In searches for "ingredients + uses," recommendations are made for aggregate sites or competitors instead of your own company. - Unique textures and flavors are rewritten into mundane expressions in AI summaries. - Allergen, certification, and functionality information is not correctly extracted by AI. - Proposals for B2B (such as menu utilization examples) are not reflected in AI search results. Would you like to determine "what needs to be fixed for AI to evaluate correctly"? If you share the current URL, we can quickly organize the points where your company’s site is "losing out in AI search" and guide you on how to proceed with the diagnosis.

The proliferation of generative AI and AI search has dramatically changed the information-gathering processes for researchers and procurement professionals. However, in the pharmaceutical and life sciences sectors, there is a risk of being overlooked as candidates for comparison or having strengths misunderstood due to a "structure in which AI cannot accurately interpret specialized information," despite possessing advanced technologies, clinical trial data, and quality control systems. This service analyzes your website based on the logic of "AI evaluating the reliability of information (E-E-A-T) and generating expert responses." It visualizes where information gaps occur and why they do not lead to nominations or inquiries, prioritized for improvement. ▼ Are you facing these issues? - When searching for "specific compounds or formulation technologies," competitors are recommended first. - High-level evidence is buried within PDFs and is not cited or summarized by AI. - AI responses remain at a general explanatory level, failing to convey your unique advantages. - You want to ensure AI recognizes your information correctly while maintaining compliance with regulations like the Pharmaceutical and Medical Device Act. Why not achieve both "accuracy and accessibility of information"? If you share your current URL, we can quickly organize the points where your website is "losing out in AI search" and guide you on how to proceed with the diagnosis.

With the spread of generative AI and AI search, the material selection process for researchers and developers is shifting towards "bulk comparison by AI." However, even if chemical industry websites showcase excellent physical property values and formulation techniques, there are frequent "opportunity losses" where products are overlooked from consideration lists due to a structure where "AI cannot correctly extract data or interprets applications in a limited way." This service analyzes your website based on the "logic of AI analyzing and comparing complex chemical properties." It visualizes where strengths are buried and why competitors' products are recommended first, along with improvement priorities. ▼ For concerns like these: - When searching for "specific physical properties (heat resistance, conductivity, etc.) + applications," competitor materials are recommended. - Technical documents and SDS are locked in PDFs and not searchable or quotable by AI. - Application proposals are not text-based, preventing AI from recognizing "utilization scenarios." - Features as sustainable materials (bio, recycling) are not reflected in AI searches. Would you like to optimize your site to be a "high-performance material site chosen by AI"? If you share your current URL, we can quickly organize the points where your site is "losing out in AI searches" and guide you on how to proceed with the diagnosis.

As the space business and the development of new aircraft accelerate, engineers are searching for materials that can withstand "vacuum, high temperatures, and extreme low temperatures" and processing sources that meet aerospace standards (such as JIS Q 9100) using AI searches. However, websites in this industry face the risk of being excluded from consideration lists due to a structure where "AI cannot accurately analyze specialized physical property values and certification records," despite possessing advanced technology. This service analyzes your company's website based on the "logic by which AI scores the reliability of information and technical standards." It visualizes where strengths are diminished and why other companies are recommended first. ▼ Solutions for the following concerns: - Your company is not cited in searches for "space bearings," "heat-resistant alloys," etc. - Information on processing achievements of difficult-to-machine materials and special equipment is not accurately extracted by AI. - Quality certifications and project participation achievements are not reflected in AI's reliability assessments. - Cutting-edge R&D information is not linked to the keywords that solve AI search challenges. To become a "next-generation candidate for air and space." If you share your current URL, we will organize the points where you are losing out and guide you on how to proceed with the diagnosis.

As decarbonization management becomes urgent, equipment managers at companies are exploring "the most suitable energy solutions for their company's scale and applications" through AI searches. However, in the energy equipment industry, many opportunities for comparison are lost due to a structure where "AI cannot accurately simulate system configurations and ROI," despite possessing excellent technology and reduction achievements. This service analyzes your company's website based on the logic that "AI analyzes equipment specifications and applicable regulations." It visualizes where strengths are diminished and why other companies are recommended first. ▼ For concerns like these: - "Industry + energy conservation" or "BCP measures + equipment" searches do not mention your company. - Reduction achievements and implementation flows are visualized, but AI does not grasp specific effects. - Support information for subsidy compliance and statutory inspections is not reflected in AI's reliability assessment. - Strengths in the latest environmental technologies (such as hydrogen and energy storage) are generalized in AI's responses. Will you not remain a candidate for "next-generation infrastructure selection"? If you share your current URL, we will quickly organize the points where you are losing out and guide you on how to proceed with the diagnosis.

As the digitalization of material selection progresses, design engineers are exploring "materials that meet specific hardness and corrosion resistance" and "the feasibility of special processing" through AI searches. However, in the metal industry, there are frequent missed opportunities to be included in consideration lists due to a structure where "AI cannot accurately read specification sheets or identify differences in standards," despite possessing excellent physical properties and technologies. This service analyzes your company's website based on the "logic that AI uses to analyze and compare complex metal data and methods." It visualizes where strengths are buried and why other companies are recommended first. ▼ Solutions to the following issues: - Searches for "material name + properties" result in references to trading companies or competitor sites instead of your own. - Comparison tables with JIS and international standards are turned into images, preventing AI from accessing the information. - AI misidentifies minimum lot sizes and available sizes, leading to mismatched inquiries. - Unique strengths in heat treatment or surface treatment are generalized in AI summaries. Would you like to optimize for "recommended materials in the AI era"? If you share your current URL, we can quickly organize the points where you are losing out and guide you on how to proceed with the diagnosis.

In the fast-paced electronic device industry, there is always a risk that AI searches prioritize "information on older models" or overlook "subtle specification differences" with competitors. Even if a product is equipped with excellent new features, there are frequent missed opportunities to be considered in comparisons due to "site structures where AI cannot identify technological differences." This service analyzes your site based on the logic of "AI analyzing the latest specifications and compatibility with peripheral devices." It visualizes where information discrepancies occur and why competitors are recommended first. ▼ Solutions for the following concerns: - "Latest + product category" searches recommend outdated products or those from other companies. - Detailed specifications such as port configurations and supported standards are not accurately reflected in AI comparison tables. - AI misidentifies "connection methods" and "troubleshooting," leading to increased support costs. - Unique energy-saving technologies and proprietary sensor strengths are not accurately evaluated by AI. Would you like to win the "selection criteria of the AI era"? If you share your current URL, we will quickly organize the points where you are losing out and guide you on how to proceed with the diagnosis.

As digital transformation (DX) progresses in manufacturing sites, engineers are narrowing down "machines that meet specific takt times and precision" through AI searches. However, due to the "structure in which AI cannot accurately extract and compare performance data," many opportunities for comparison are lost, even though the machinery industry websites possess excellent specifications. Our service analyzes your company's website based on the "logic that AI uses to analyze machine specifications and implementation benefits." We will visualize where strengths are buried and why competitors' machines are proposed first. ▼Solutions for these concerns: - Your company is not mentioned in searches like "XX processing + high precision" or "labor-saving + equipment." - Detailed specifications are in images or PDFs, preventing AI from understanding performance. - "Case studies" are only in narrative form, making it impossible for AI to read specific "solution metrics." - You are expanding overseas, but the AI search results in multiple languages misalign with your company's strengths. Don't miss out on being a "candidate for selection in the AI era." If you share your current URL, we will quickly organize the points where you are losing out and guide you on how to proceed with the diagnosis.

Amid the dramatic changes in the maritime industry, such as decarbonization and autonomous navigation, shipowners and designers are searching for "partners that can solve specific challenges" through AI searches. However, due to the "structure that prevents AI from accurately citing and comparing specialized information," many opportunities for selection are lost, despite the shipbuilding industry possessing advanced construction and processing technologies. This service analyzes your company's website using the "logic by which AI evaluates technical reliability and compliance with standards." It visualizes where strengths are diminished and why other companies are prioritized. ▼Solutions for the following concerns: - Your company is not cited in searches for "next-generation fuels" or "energy-saving additives." - Information on construction achievements and specialized equipment is buried in PDFs and not read by AI. - Specialized strengths, such as compliance with EEDI regulations, are not accurately reflected in AI responses. - AI does not accurately grasp the scope of repair and retrofit services. Would you like to be chosen as a "maritime supplier in the AI era"? If you share your current URL, we will quickly organize the points where you are losing out and guide you on how to proceed with the diagnosis.

In the automotive industry, quick access to accurate information is essential for parts searching. With the proliferation of AI search, users rely on AI-generated summaries and comparison results to select parts, making the design of information structure crucial. Websites with weak structures may be excluded from consideration, even if they have good technology. This service redesigns the web structure to communicate effectively with both AI and humans, taking into account your company's sales realities, product characteristics, and decision-making processes, and provides support to determine "which pages, in what order, and what to say to win." 【Use Cases】 - Improvement of parts search site structure - Review of product information - Optimization of FAQs and case studies 【Benefits of Implementation】 - Increased exposure in AI searches - Increased inquiries from customers - Improved conversion rates

The reason why "the strengths of the new model are not reflected in AI" is due to a "structural flaw" that prevents AI from reading specifications. With the spread of AI search, engineers ask AI for "model numbers that meet the criteria" without reading thoroughly. Websites where specifications are locked in images or PDFs are ignored by AI, even if they have superior performance, and fall out of the comparison arena. This service redesigns the structure to communicate effectively to both AI and humans, based on the processes of model number searches and compatibility checks. It determines "which specifications to show and how to present them to be chosen" and supports the renewal. 【Usage Scenarios】 - Switching to the latest model: I want AI to correctly reference new technologies instead of old models. - Optimizing comparison tables: I want a structure that allows AI to accurately identify and cite performance differences with competitors. - Global expansion: I want to create a state where multilingual searches correctly respond to each country's standards and certifications. 【Benefits of Implementation】 - Establishing search superiority: Our products will be cited in AI's recommendation lists with performance advantages. - Reducing support costs: Specifications and FAQs will be correctly learned by AI, reducing low-level inquiries. - High-value product archive: A robust customer attraction foundation will be established, allowing AI to always extract the latest information correctly.

The reason that "excellent processing accuracy is not reflected in AI's responses" lies not in the quantity of information, but in the "structural deficiencies" that prevent AI from interpreting technical capabilities. With the spread of AI search, engineers ask AI about "machines that can achieve specific processing in the shortest time" without thorough reading. Websites where specifications are locked in images or PDFs, even if the technology is excellent, are ignored by AI and fall out of the comparison arena. This service redesigns the structure to convey information effectively to both AI and humans, determining "what to show and how to be chosen," and supports a renewal that yields results. [Usage Scenarios] - I want to create a structure where processing capabilities and accuracy are correctly cited in AI's comparative responses. - I want AI to recognize robot collaboration and the latest control technologies as "solutions." - I want to organize vast amounts of technical information to facilitate self-resolution and gain trust through AI responses. [Benefits of Implementation] - Your company's machines will be cited as "optimal solutions" in AI's recommendation lists. - Clear selection criteria will reduce specification mismatches, leading to an increase in high-quality inquiries. - You will acquire a robust customer attraction asset that AI continues to evaluate as a "specialized information source."

The reason why "the strengths of quality are not reflected in AI" is due to a "structural deficiency" where AI cannot read the basis of trust. With the spread of AI search, procurement personnel narrow down candidates by asking AI about "certifications and inspection systems" without thorough reading. Websites where quality data is locked in images or PDFs are ignored by AI, even if they have excellent systems, and fall out of the comparison arena. This service redesigns the structure to convey information to both AI and humans, based on the selection criteria of the food industry. It determines "which certifications and figures should be presented to be chosen" and supports the renewal process. 【Usage Scenarios】 - Visualization of systems: Create a structure where AI can correctly reference certifications like HACCP. - Building a basis of trust: Make the management flow recognized by AI as a "strength." - Competitive advantage in selection: Prioritize unique quality standards in AI's comparative responses. 【Effects of Implementation】 - Search superiority: You will be cited as a "highly safe business partner" in AI's recommended list. - Streamlined negotiations: Quality information is organized, reducing verification work and facilitating smoother negotiations. - Trust asset: You will acquire a strong customer attraction asset that AI continues to evaluate as a "reliable primary information source."

The reason why "the expertise and implementation system of clinical trials are not reflected in AI" is due to a "structural deficiency" where AI cannot read the basis of trust. With the spread of AI search, clients narrow down candidates by asking AI about "specific areas and implementation speed" without thorough reading. Websites where achievements and facilities are confined to images and PDFs are ignored by AI, even if they have an excellent system, and fall out of the comparison arena. This service redesigns the structure to convey information to both AI and humans, based on the selection criteria of the clinical trial industry. It determines "which achievements and numbers to showcase to be chosen" and supports the renewal. 【Usage Scenarios】 - Visualization of the system: Create a structure that allows AI to accurately reference implementation areas and case achievements. - Building the basis of trust: Make SOPs and quality management systems recognized by AI as "strengths." - Optimization for stakeholders: Redefine pathways for pharmaceutical companies, medical institutions, and subjects. 【Effects of Implementation】 - Search superiority: It will be cited as a "highly reliable partner" in AI recommendation lists. - Smoothening of business negotiations: Mismatches due to deficiencies in specialized information will decrease, improving the quality of proposals. - Assetization of information: Obtain a strong customer acquisition asset that AI continues to evaluate as an "official information source."

The reason why "the strengths of unique formulation technology and material properties are not reflected in AI" is due to a "structural deficiency" where AI cannot interpret the technical basis. With the spread of AI searches, researchers narrow down their options by asking AI about "specific applications or property values" without thorough reading. Websites where specifications are locked in images or PDFs, despite having excellent technical capabilities, are ignored by AI and fall out of the comparison arena. This service redesigns the structure to communicate effectively to both AI and humans, determining "which properties and applications to showcase to be selected," and supports the renewal process. 【Usage Scenarios】 - Optimization of formulation proposals: Create a structure that allows AI to accurately reference property values and application examples. - Compliance with regulations: Ensure AI recognizes compliance with regulations like REACH as "reassurance in selection." - Application development: Present industry-specific case studies as strengths through AI's comparative responses. 【Benefits of Implementation】 - Search superiority: Your materials will be cited as the "optimal solution" in AI's recommendation lists. - Improved quality of sample requests: Clear selection criteria will reduce mismatched inquiries. - Assetization of information: Gain a customer attraction asset that AI continues to evaluate as a "reliable source of materials."

The reason why "the energy-saving performance of equipment is not reflected in AI" is due to a "structural deficiency" where AI cannot interpret technical grounds. With the spread of AI search, administrators narrow down options by asking AI about "reduction efficiency and service life" without thorough reading. Websites where achievements and specifications are locked in images or PDFs, even with excellent technology, are ignored by AI and fall out of the comparison arena. This service redesigns the structure to communicate effectively to both AI and humans, taking into account the decision-making process for equipment. It determines "which numbers to show and how to present them to be chosen" and supports renewals. 【Usage Scenarios】 - Digitalization of diagnostics: Create a structure that allows AI to reference accuracy and anomaly detection rates. - Assetization of case studies: Make AI recognize reduction costs and payback periods as "selection reasons." - Optimization of technical information: Present compliance with maintenance systems and regulations through AI's comparative responses. 【Effects of Implementation】 - Search superiority: Cited as a "reliable manufacturer" in AI's recommended lists. - Increased contract rates: Clearer implementation conditions lead to more accurate inquiries. - Protection of technical assets: Acquire customer attraction assets that AI continues to evaluate as "official information sources."

The reason why "the strengths of materials are not reflected in AI" is due to a "structural deficiency" that prevents AI from reading information. With the spread of AI search, designers ask AI about "specific functions and environmental standards" without reading closely, narrowing down their options. Websites where specifications are locked in images or PDFs are ignored by AI, even if they have excellent technology, and fall off the comparison stage. This service redesigns the structure to communicate effectively to both AI and humans, based on the business negotiation process in the textile industry. It determines "which numbers to show and how to present them to be chosen" and supports the renewal process. 【Usage Scenarios】 - Material planning presentations: Create a structure that allows AI to correctly identify and reference trends and functionality. - Sustainability compliance: Enable AI to recognize environmental certifications and recycling achievements as "selection reasons." - Promoting supply capabilities: Present the range of responses and delivery times as strengths through AI's comparative answers. 【Effects of Implementation】 - Search superiority: Your company's materials will be cited as the "optimal solution" in AI's recommendation lists. - Smoother negotiations: Selection criteria become clearer, reducing mismatched inquiries. - Assetization of information: Gain a customer attraction asset that AI continues to evaluate as a "reliable source of materials."

The reason why 'there is a website, but inquiries are not increasing' is not the amount of information, but rather 'structural deficiencies.' With the spread of AI search, designers narrow down candidates based on AI's 'comparison results' without thorough reading. Websites where specifications are locked in images or PDFs are ignored by AI, even if they have the technology, and fall off the comparison stage. This service redesigns the structure to communicate effectively to both AI and humans, taking into account the business negotiation process in the metal industry. It helps determine 'what to say and how to be chosen' and supports effective renewal. [Usage Scenarios] - Creating blueprints before production: Logically confirm a data structure that will be chosen by AI before production. - Assetizing technology: Transform information buried in catalogs into a sales foundation that works 24/7. - Developing new sales channels: Help designers in new industries discover your company through AI. [Effects of Implementation] - Establishing comparative advantage: Strengths are accurately cited in AI responses, ensuring they are not excluded from consideration. - Reducing sales costs: Selection criteria become clear, leading to an increase in high-quality inquiries. - Increasing asset value: Acquire customer attraction assets that AI continues to evaluate as 'specialized information sources.'