LLM Optimization – Optimizing for Claude, ChatGPT, Gemini

Most SEOs spend their entire careers chasing a single algorithm. Google updates roll out, they scramble, they adapt, and they go back to building links. That model worked for twenty years. It is still working today. But quietly, a second front has opened. Millions of people now start their search journey not with Google, but with ChatGPT, Claude, or Perplexity. They ask a question in natural language and get a generated answer that names specific products, tools, and brands. If your brand is not being named in those answers, you are losing visibility on a surface that no rank tracker can measure. I started paying serious attention to this shift in early 2025 when I noticed referral traffic appearing in my analytics from sources like "chat.openai.com" and "perplexity.ai." Small numbers at first, but growing fast. That is when I realized that we had entered a new era. The old game was about getting Google to rank you. The new game is about getting AI models to know you exist and cite you as an authority. This discipline is called llm optimization, and it is the next evolution of SEO. This guide will explain exactly what llm seo means, how ChatGPT, Claude, and Gemini decide which brands to mention, and the practical steps you need to take to make your brand the answer these models default to. I will also tell you, without hype, where good old-fashioned backlinks still fit into this picture. Because they do.

What Is LLM Optimization?

LLM optimization is the practice of shaping your online presence so that large language models, the AI systems that power ChatGPT, Claude, Google Gemini, Perplexity, and others, recognize your brand as a trustworthy source on specific topics. When a user asks ChatGPT "what is the best CRM for small business," the model generates a response based on everything it learned during training and, if the model has access, from real-time web searches. LLM optimization aims to make your brand the one that gets named in that answer. It is not about tricking the AI. It is about building the kind of authority, through content, citations, and entity signals, that makes the AI view you as the obvious choice.

This is different from traditional SEO in one crucial way. Google ranks pages. LLMs recommend entities. Google sees a collection of URLs with links pointing to them. An LLM sees a map of concepts and brands, connected by mentions, citations, and context. A link from a high-authority page helps a traditional ranking directly. An unlinked brand mention in a respected publication does almost nothing for a blue-link ranking but can significantly influence an LLM's perception of your brand. I explored this shift in detail in my guides on AI visibility and brand mentions and generative engine optimization. The core insight is that you now need to optimize for both signals: links for traditional ranking engines, mentions and entity authority for generative models.

How ChatGPT, Claude, and Gemini Choose Their Sources

Before you can optimize for these models, you need to understand what makes them tick. I have spent the last year testing, reading research, and talking to engineers. Here is the simple version.

ChatGPT (with search) and Perplexity are retrieval-augmented models. When you ask them a question, they do not just rely on their training data. They perform a live web search, pull in relevant pages, and synthesize an answer from those sources. This means they are heavily influenced by the pages that rank well in traditional search engines, because that is often where they get their information. A page that ranks in the top three for "best CRM for small business" is highly likely to be used as a source by ChatGPT when answering that question. This is why link building still matters enormously for LLM visibility. I proved this connection in my experiment on PBN links and AI Overviews. Building clean PBN links that push a page into the top five will indirectly boost its visibility in retrieval-based AI answers.

Google Gemini is deeply integrated with Google's Knowledge Graph and the core search index. When Gemini answers a question, it pulls from the same entity database that powers Knowledge Panels and featured snippets. If your brand is a well-defined entity in Google's Knowledge Graph, with consistent structured data, a Wikipedia or Wikidata entry, and frequent citations across the web, Gemini is much more likely to mention you. I covered the entity building process in my entity SEO guide. Gemini also relies on the web results for real-time information, so traditional ranking strength is a factor here too.

Claude from Anthropic operates differently. It does not have live web access by default (though some features are rolling out). Its knowledge comes entirely from its training data, a massive corpus of web pages, books, and articles. Claude knows about brands that were frequently discussed in that training data. It has a strong preference for sources that appear authoritative, are cited often, and are associated with clear expertise. To be visible in Claude, you need to be mentioned widely across the web in high-quality contexts. Guest posts, media mentions, forum discussions, and academic citations all feed Claude's training data. This makes brand mentions and digital PR even more important for Claude than for the other models. I wrote about how to get mentioned in ChatGPT and Perplexity, and the same principles apply to Claude.

The common thread across all three is that they trust entities that are frequently cited, clearly defined, and associated with high-authority sources. The specific mechanisms differ, but the underlying strategy is the same: become a known, trusted entity in your niche, and the AI models will follow.

The Practical LLM Optimization Playbook

I have been refining these tactics for the past two years across my own brands and for clients. This is the playbook I use.

1. Build Your Entity Foundation
This is step one. If Google's Knowledge Graph does not know who you are, the AI models will not either. I deploy comprehensive schema markup on every site, specifically Organization and Person schema, with sameAs links pointing to all social profiles, Wikipedia, and Wikidata. I make sure the brand's name, address, and phone number are identical across every platform. I claim and optimize every relevant profile: Google Business Profile, LinkedIn, Twitter, Crunchbase. I create a Wikidata entry for the brand, with proper references. This work is tedious, but it is the foundation that all other optimization rests on. My entity SEO guide walks through each step in detail.

2. Earn Brand Mentions on Authoritative Sites
An AI model's training data is full of text. If your brand name appears frequently in respected publications, the model will learn to associate your brand with those topics. I pursue brand mentions through digital PR. I use Featured.com ($19.99/mo for 15 pitches) and Qwoted ($79/mo for unlimited pitches) to connect with journalists. I provide expert commentary, and when they quote me, my brand name appears in the article, often without a link. That unlinked mention is invisible to a traditional backlink checker but feeds directly into the AI's training data. I detailed this in my HARO alternatives guide. I also publish original data studies. A survey of 200 customers with published results generates citations that compound for years.

3. Create Content That Is Structured for AI Extraction
LLMs process text in chunks. They prefer content that is well-organized, with clear headings, concise answers, and structured data. I format key pages with question-and-answer structures, using H2 and H3 headings for the questions and a short, direct paragraph as the answer. I use lists and tables where appropriate. I include schema markup for FAQs and HowTos. This makes it easy for retrieval models to pull my content into their answers. This is the on-page side of GEO that I described in my generative engine optimization guide.

4. Build a Network of Quality Backlinks
Links still matter. They may not be counted directly by all LLMs, but they power the traditional search rankings that many models rely on for real-time retrieval. A PBN link from a clean, niche-relevant domain pushes your page up the rankings. That higher ranking makes the page more likely to be cited by ChatGPT, Perplexity, and Google Gemini. I continue to build PBN links and place niche edits using the same rigorous standards I have always used: TF 10+, TF/CF ratio above 0.8, clean history, diverse hosting, safe anchors. My complete how to build a PBN guide and 18-point domain evaluation framework cover the process. At BuyPBNLinks, every link we sell is built to be a permanent authority asset that works for both traditional SEO and LLM visibility.

5. Be Active on Platforms That Feed AI Training
Reddit, Quora, and Wikipedia are heavily used in AI training data. An active, respected presence on these platforms gets your brand name into the training corpus. I do not spam. I participate genuinely in relevant subreddits, answer questions on Quora, and contribute to Wikipedia where appropriate. I discussed this in my guide on why Reddit and Quora dominate Google. These mentions build the kind of real-world association that LLMs are trained to recognize.

6. Monitor Your LLM Visibility
You cannot improve what you do not measure. I manually test my target queries in ChatGPT, Perplexity, Claude, and Google Gemini weekly. I track the results in a spreadsheet. I also use Brand24 ($149/mo Team plan) for automated AI Overview alerts. I dedicated an entire guide to how to track AI mentions. This monitoring tells me whether my optimization efforts are working and reveals which competitors are gaining ground.

The Role of PBN Links in LLM Optimization

I know what you are thinking. "Sheikh, you sell PBN links. Of course you are going to say they matter." I am not going to pretend otherwise. But I will give you the honest breakdown. PBN links do not directly influence an LLM's training data. ChatGPT does not crawl your backlink profile in real time and count your referring domains. But PBN links push your pages into the top five traditional rankings, and those top-ranking pages are the primary sources that retrieval models pull from. A clean PBN link is an indirect but highly effective LLM optimization tactic because it improves the ranking signal that many AI models rely on. Additionally, a well-built PBN domain that is itself a strong entity, with consistent branding, real content, and its own backlinks, passes both link equity and entity authority. This is why I build every PBN domain as a real publication. It strengthens the entire ecosystem.

The March Spam Update, which I analyzed in detail, did not change this. It penalized cheap, footprint-heavy networks. The clean, well-maintained PBNs survived and continue to support both traditional and AI visibility. At BuyPBNLinks, our links are built to this standard. We provide the foundational authority that makes all your other LLM optimization efforts more effective.

LLM Optimization Mistakes

• Mistake 1: Thinking LLM optimization replaces link building. It does not. It adds a layer on top. Without links, your traditional rankings suffer, and retrieval models will not find you.
• Mistake 2: Chasing AI mentions with spam. Posting "my brand is the best" in a hundred Reddit threads will get you banned and poison your brand. Authenticity is the only strategy that works with AI models.
• Mistake 3: Ignoring the entity layer. If your brand is not a coherent entity in Google's Knowledge Graph, the AI models have no consistent record of who you are. Fix the schema and the NAP data before anything else.
• Mistake 4: Treating all LLMs the same. ChatGPT relies on real-time search. Claude relies on training data. Gemini relies on the Knowledge Graph. Tailor your approach accordingly, but the common thread is entity authority and brand mentions.
• Mistake 5: Neglecting manual testing. The tools for tracking LLM mentions are immature. You must manually verify your visibility. A spreadsheet and thirty minutes a week is the minimum.

Frequently Asked Questions