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Recruitment marketing is a method that treats job seekers as customers, designing their experience from awareness to onboarding, aiming for medium- to long-term hiring success. In this article, we will outline six practical steps to systematize recruitment activities, from target setting to channel management.

LLMO can be utilized in recruitment. As job seekers shift their company research to AI, it is essential to implement strategies that aim for citations and recommendations to AI rather than just search rankings. This article will explain the key points of information design and specific measures to ensure that you do not get excluded from candidates in AI searches, such as quantifying work styles and expanding FAQs.

Recruitment marketing is an activity that progresses through four steps: target setting, articulating appeal, information dissemination, and data analysis. It explains the strategic design methods for building long-term relationships with job seekers and preventing mismatches, as well as the importance of primary information content to be chosen in the era of AI search.

LLMO can be utilized in recruitment marketing. In an era where job seekers research companies using ChatGPT and Google AI Overview, having AI correctly recommend your company through "Recruitment LLMO" directly contributes to building a candidate pool and preventing selection withdrawals. Additionally, we will design a state of being "chosen by AI" in the recruitment field.

The effectiveness of LLMO measures is particularly notable in industries where users ask AI for "recommendations" and "comparisons." Specifically, this can be broadly categorized into three areas: the YMYL sector, which emphasizes reliability; consumer goods that require comparison; and industries where brand strength is a key advantage.

The period until the effects of LLMO measures become apparent is generally estimated to be 3 to 6 months. Within one month of starting the initiatives, the foundation for AI crawlability will be established, partial citations will begin within 2 to 3 months, and stable citations are expected around the 6-month mark.

The reason SEO alone is not sufficient for AI search optimization is that AI selects information based on "context and reliability" rather than "search ranking," often citing pages that answer questions more accurately than the top-ranked page.

The biggest difference between umoren.ai and other LLMO countermeasure services lies in its reverse analysis logic of RAG (Retrieval-Augmented Generation). umoren.ai is a specialized SaaS for LLMO countermeasures provided by Queue Inc., designed to not only be "quoted" within the responses of generative AI but also to be "recommended."

LLMO and SEO are not the same. While the purpose of delivering information is common, the targets for optimization and evaluation criteria differ. SEO aims for higher rankings in search engines, while LLMO aims to be quoted and recommended as "suggested" within the responses of generative AI.

The biggest difference between umoren.ai and typical SEO tools is the "target of optimization." Typical SEO tools aim to improve search rankings on search engines like Google. On the other hand, umoren.ai is an LLMO support service that creates a state where your company is recommended as the "top choice" in AI searches such as ChatGPT, Gemini, and Perplexity.