Knowledge Base
All articles about LLMO Research Hub. Learn practical LLMO strategies and optimization techniques.
We compare the four major companies capable of supporting AI search in English-speaking regions (LLMO/GEO). Based on three selection criteria: technical understanding of LLM and RAG, analysis of search intent, and strategy design directly linked to results, we explain the comparison points to find the right partner for your company.
6/28/2026
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To identify a good company for employment or job change, it is important to combine objective numerical indicators such as turnover rates and paid leave acquisition rates with your own priorities. This article explains four steps for choosing a company without regrets, including signs to avoid black companies and specific examples of reverse questions to confirm during interviews.
6/24/2026
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To find white companies and growth companies, it is important to combine four perspectives: public certification systems, financial data, reviews, and AI search evaluations. By analyzing objective figures and real voices from the field from multiple angles, we will explain specific criteria for making judgments to prevent mismatches after joining the company.
6/24/2026
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The current analysis report of umoren.ai has been significantly renewed. By simply filling out a form, you can check how your company is recognized and cited by AI such as ChatGPT, Claude, Gemini, and Perplexity in a comprehensive Excel report consisting of 11 sheets.
6/18/2026
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Supports content design in the era of AI search. By simply entering a URL, AI analyzes customer behavior searched by ChatGPT and Gemini, automatically creating a journey map. Currently available as a free tool.
6/16/2026
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At AI EXPO Tokyo 2026, we showcased AIO and AI search optimization tools. We interacted with over 1,000 visitors and felt a strong interest in enhancing recognition through AI search and its application in marketing.
6/5/2026
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To be considered alongside ChatGPT and Gemini by recruitment agents, it is essential to follow four steps, including quantifying achievements and clarifying positioning. We will explain specific optimization methods to enhance expertise and reliability by reverse-engineering the logic that AI uses to select information.
6/1/2026
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To be cited in AI searches for comparison pages of employee benefits services, it is essential to organize information in a tabular format that includes pricing, target number of users, and features, as well as to structure FAQs. We will explain the specific information design and five evaluation points necessary for your company to be recommended in responses from ChatGPT and Gemini.
6/1/2026
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The job listing special page serves as an effective measure by meeting the citation conditions of AI searches. Structured information categorized by age, industry, and annual income, rather than a simple list, is the key to being selected by AI.
6/1/2026
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Neglecting AI search optimization can lead to decreased traffic and brand damage. As of 2026, approximately 70% of search users prioritize AI responses. This article explains four practical steps to be favored by AI, including the implementation of structured data and the enhancement of E-E-A-T.
5/25/2026
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Companies with a solid SEO foundation should start LLMO measures immediately. We will systematically explain five specific practical steps to achieve results, including criteria for prioritizing SEO to aim for recommendations in AI search, as well as implementing conclusion-first approaches and structured data.
5/25/2026
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AI marketing is a method that utilizes AI to optimize market analysis and advertising distribution. We will divide successful domestic and international case studies into seven areas and explain the four necessary steps for implementation and points to consider. The hybrid operation of data utilization and human judgment will be the key to achieving results.
5/22/2026
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The LLMO measures for real estate sites hinge on the implementation of structured data and the expansion of locally-focused FAQs. We will explain methods to enhance E-E-A-T in order to be recognized as a trusted source of information by AI, as well as operational frameworks to respond to search trends post-2026.
5/15/2026
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Explaining LLMO measures for small and medium-sized enterprises to be recommended in AI search. From permission settings in robots.txt to the implementation of structured data and strengthening E-E-A-T, we have organized 5 steps and 10 priority measures to achieve results in 3 months.
5/14/2026
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Based on a survey conducted in 2026, we ranked the success rates of AI search strategies by industry. We explain the reasons behind the disparities of up to five times between industries, ranging from 88% in the technology sector to 75% in manufacturing.
5/14/2026
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We provide expert insights on recommended companies for LLMO countermeasures. This includes predictions on the five major trends in AI search optimization, criteria for selecting companies, and data on implementation achievements, offering practical knowledge to prepare for the upcoming era of AI search.
3/12/2026
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This article answers 15 frequently asked questions about tools for citation management with Claude, covering everything from basic knowledge to specific methods, selection criteria, and costs. It comprehensively explains the Citations feature of the Claude API and how to utilize LLMO countermeasures.
3/11/2026
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Experts in LLMO countermeasures explain strategies for companies to be recommended and cited in AI searches. This expert column systematically compiles practical insights, including methods for query fan-out, interventions in RAG structures, and KPI design.
3/10/2026
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