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1. Causes of AI Search Failures: Analysis Service (for Manufacturing Industry)

Even when summarized by AI, we will identify the "structural flaws" that allow it to remain a candidate for comparison.

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.

  • others
  • Analysis of the causes of falling

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Analysis service for causes of drop in AI search for pharmaceuticals.

"Safety" and "evidence" do not reach AI. A technical assessment for pharmaceutical-related sites to be correctly cited in AI searches.

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.

  • Other Signs
  • Analysis of the causes of falling

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【自動車品質管理向け】AI検索で落ちる原因 分析サービス

「Tier1・2への提案力」をAIが正しく要約。自動車部品サイトがAI検索で推奨されるための技術診断。

CASE対応やEVシフトが加速する中、設計担当者はAI検索で「特定の課題を解決できるサプライヤー」を探しています。しかし多くの部品メーカーサイトは、優れた技術を保有しながら“AIが課題解決力として抽出できない構造”のせいで、土俵にすら上がれない機会損失が多発しています。本サービスでは、貴社サイトを「AIが技術力や信頼性を評価するロジック」で分析。なぜ競合が先に推奨されるのかを可視化します。 ▼こんなお悩み解決に ・「軽量化」「放熱」等の課題検索で、自社が引用されない ・試作実績や設備情報が構造化されず、AIが対応不可と判断している ・品質認証やBCP体制が、AIの信頼性評価に反映されない ・EV等の新領域技術が、AI検索のキーワードと紐付いていない 「次世代モビリティの選定候補」に残りませんか。現状URLを共有いただければ、損をしているポイントを短時間で整理し、診断の進め方をご案内します。

  • Automotive Connectors
  • Analysis of the causes of falling

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Aerospace AI Search Failure Analysis Service

"Extreme performance" and "quality certification" are beyond the reach of AI. A technical diagnosis for aerospace sites to be recommended through AI search.

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.

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  • Sterilizer
  • Analysis of the causes of falling

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Analysis service for causes of drop in AI search for energy equipment.

"Energy-saving effects" and "implementation results" are not being accurately conveyed to AI. A diagnosis for energy equipment sites to be selected in AI searches.

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.

  • Industrial Furnace
  • Analysis of the causes of falling

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Analysis service for causes of drop-offs in AI search for electronic device manufacturers.

"Latest specifications" and "compatibility" are not reflected in AI. A technical diagnosis for electronic device sites to be recommended in AI searches.

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.

  • Electron tube
  • Analysis of the causes of falling

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Analysis service for causes of drop in AI search for shipbuilding.

"Construction achievements" and "technical standards" are not correctly conveyed to AI. A technical assessment for shipbuilding industry sites to be recommended in AI searches.

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.

  • Ultrasonic Oscillator
  • Analysis of the causes of falling

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Analysis service for causes of drop-offs in AI search for the textile industry.

The "texture" and "commitment" do not get conveyed to AI. There are reasons why websites in the textile and apparel industry are "not chosen" in AI searches.

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.

  • fiber
  • Analysis of the causes of falling

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Analysis service for causes of drops in AI search for semiconductors.

Are you missing out on the spec comparison? A technical diagnostic service for semiconductor sites to be "correctly cited" through AI search.

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.

  • others
  • Analysis of the causes of falling

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Analysis service for causes of drop-offs in AI search for the food industry.

"Deliciousness" and "safety" do not get conveyed to AI. There are reasons why food industry websites are "not chosen" in AI searches.

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.

  • Other DNA/RNA
  • Analysis of the causes of falling

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Analysis Service for Causes of Drop in AI Search for the Chemical Industry

Are "physical properties" and "applications" being misread by AI? A technical diagnosis for chemical industry sites to be recommended in AI searches.

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.

  • Chemicals
  • Analysis of the causes of falling

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Analysis Service for Causes of Drop in AI Search for the Metal Industry

Are the "material properties" and "processing limits" being misread by AI? A diagnosis for metal industry websites to be recommended in AI searches.

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.

  • alloy
  • Analysis of the causes of falling

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Analysis service for causes of failures in AI search for machines.

"Performance metrics" and "strengths of automation" are not conveyed to AI. A technical diagnosis for machine industry websites to be recommended in AI searches.

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.

  • Processing Contract
  • Analysis of the causes of falling

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