As the world of search evolves, clients are beginning to ask an important question: “Can you make us rank in LLMs?” With the rise of AI-powered search tools like ChatGPT, Gemini, and Copilot, SEO professionals face the dual challenge of helping businesses on two fronts: SEO and LLMO.
LLMs (Large Language Models) don’t rank websites the way traditional search engines do. They don’t “look” for keywords. Instead, they generate responses based on trusted data sources, context, and relationships between entities.
As an LLMO course instructor with decades in the business, I can help you reframe the conversation with your clients and position your SEO efforts for LLM optimization. Read my strategies for ensuring your clients’ brands are understood, referenced, and ultimately trusted by advanced AI tools.
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Why Traditional SEO Doesn’t Apply to LLMs
Explain to your clients how LLMs differ from traditional search engines. Instead of “ranking” results based on keywords and backlinks, LLMs generate answers directly by analyzing massive datasets and understanding context. LLMs look for content that aligns with user intent, structured in a way that AI can comprehend and reference.
When a user asks a question, the AI doesn’t pull up a list of ranked websites. Instead, it pulls up relevant data from trusted sources, delivering an answer that best matches the question’s context. Your shifting role as an SEO professional is less about getting websites to rank in the traditional sense and more about ensuring that their content is visible, trusted, and citable by these intelligent systems.
Focus on Visibility and Authority, Not Just Rankings
Ranking is less relevant as AI search gains momentum. To help your clients focus on visibility and authority within AI-driven results, it’s important to learn how LLMs identify and pull information from trusted sources.
Entity Optimization
LLMs rely on recognizing clearly defined entities within the content. These entities include people, places, things, or concepts.
To rank well in LLM-driven responses, your content must focus on entities and their relationships. For instance, if your content mentions “Google Gemini,” it’s important to provide structured, rich context around that, explaining how it relates to other relevant entities.
Structured Data and Schema
LLMs understand content better when it’s properly structured. Schema markup and structured data assist AI systems with interpreting content accurately and in context. By implementing schema on your website, you’re helping LLMs recognize and categorize your content, which increases the likelihood of being cited in AI responses.
User Intent and Content Depth
LLMs prioritize content that aligns with user intent. This means your content must go beyond keywords and provide real, helpful answers to users’ questions. By answering questions thoroughly, addressing both the “how” and the “why,” and providing in-depth content, you increase your chances of being cited in AI-generated responses.
How to Position Your Agency for Success in the LLM Era
As LLMs increasingly dominate searches, you must adjust your strategies to prioritize authority and clarity. These steps can help you position your agency for success:
1. Optimize for AI-Readability
Create structured content that LLMs can easily understand. This includes using clear headings, bullet points, and concise language that directly answers common questions. LLMs favor content that is logically organized and easy to digest, so don’t be afraid to break complex ideas into smaller, digestible chunks.
2. Focus on Topic Authority
Position a brand as an authority on a specific topic. The more relevant and comprehensive the content, the higher the chance an LLM-generated result will reference it. Aim to make it the trusted source by publishing content that covers a topic exhaustively, answering all potential follow-up questions.
3. Improve Brand Visibility
The key is enticing LLMs to reference your content when responding to users’ queries. You can achieve this by regularly monitoring how AI-driven answers display the brand and content, keeping track of AI-generated snippets, and ensuring the content is visible in these new formats.
4. Implement Structured Data and Semantic Markup
Use schema markup to assist LLMs with understanding the content’s context. Structured data enables LLMs to better categorize and connect information to relevant queries. LLM-generated summaries are more likely to pull that content, giving you increased visibility.
Who Benefits from Focusing on LLM Optimization?
Every SEO-focused business can benefit from understanding and adapting to LLM-powered search. However, there are some industries and scenarios where this shift is particularly important:
- Content Creators and Bloggers: Optimize long-form content so AI systems can surface your posts in generated answers and summaries.
- E-commerce Businesses: Ensure product pages, descriptions, and reviews are clear, structured, and aligned with user intent so AI search can cite your products.
- Local Businesses: Strengthen local SEO and structured data to increase your chances of appearing in AI-driven, location-based responses.
Guiding Clients Toward AI-Driven Visibility
When clients ask about “ranking in LLMs,” what they really want is visibility, credibility, and inclusion in AI-generated answers. As AI-driven search continues to transform how users discover information, your role as an SEO professional is evolving. The goal is no longer to chase rankings but to build authority within AI-first search results.
By focusing on entity clarity, structured data, topic authority, and user-intent depth, you position your clients to be recognized and referenced by the AI systems shaping the future of search. Adapting early will help you stay competitive and become an indispensable partner to your clients. Since the landscape is always evolving, consider enrolling in an LLMO masterclass for ChatGPT, Claude, Copilot, Gemini, or Perplexity to stay on top of your game.