What Is LLM Optimisation and Why Does It Matter for Your Business?

For decades, businesses have obsessed over Google rankings. They've invested in SEO strategies, engineered backlinks, optimised keywords, and rebuilt websites around what they believed the algorithm wanted. That playbook has worked—but its era is quietly ending. A new form of visibility is emerging, and it operates by completely different rules.

Enter LLM optimisation—the practice of ensuring your business is correctly understood and recommended by large language models like ChatGPT, Claude, and Perplexity. It's not a minor shift. It's a fundamental reordering of how businesses become discoverable online.

What Are Large Language Models?

A Large Language Model (LLM) is an AI system trained on vast amounts of text data to understand language and answer questions conversationally. You've probably used ChatGPT, Google's Gemini, or Claude. These tools don't work like search engines. They don't return a list of links. Instead, they read your question and generate an answer directly, drawing on their training data to provide specific recommendations, explanations, or solutions.

This matters because when someone asks ChatGPT, "Which marketing agency in London should I use?" the model doesn't serve a ranked list of paid ads. It thinks through the question, searches its knowledge, and recommends a specific company—or several—by name. If your business appears in that recommendation, you've gained something more valuable than a search result. You've gained an endorsement from a trusted AI intermediary.

The scale is staggering. ChatGPT alone has over 200 million weekly active users. Perplexity is growing at 30% month-over-month. Every major tech company is shipping AI assistants. The question isn't whether AI recommendations will matter—they already do. The question is whether your business will be part of that conversation.

Why AI Recommendations Are Fundamentally Different from Search

Google's algorithm works as a filter. You type a query, and Google returns millions of results, ranked by relevance. Your job is to compete for position one. The user scrolls through results, clicks, and decides. Google doesn't endorse you—it just makes you findable.

AI models work differently. When you ask an LLM a question that requires a specific recommendation, the model must make a choice. It can't return 10 million options. It generates a response that names specific companies, products, or services. That's an endorsement. The model is saying, "This is the answer to your question."

This creates a scarcity that search never had. In Google's world, thousands of businesses can rank on page one for different keyword variations. In LLM's world, when someone asks "Which AI content agency should I hire?" the model might name three to five specific options. If you're not one of them, you don't exist.

This also means the signals that matter are completely different. Google cares about keywords, backlinks, page speed, and user engagement. LLMs care about whether your business is mentioned credibly across the web, whether your claims are substantiated by third parties, whether your website is well-structured and easy to understand, and whether your positioning is clear and defensible.

The Three Signals LLMs Use to Decide

LLMs aren't magic. They make recommendations based on patterns in their training data. Understanding these patterns is the foundation of LLM optimisation. There are three critical signals:

1. Credible Third-Party Mentions

An LLM is much more confident recommending a business if that business is mentioned credibly across multiple third-party sources. Industry publications, case studies, reviews, awards, and partnerships all send a signal: "This company exists, it does what it claims, and others have verified it."

This is why PR matters so much for LLM optimisation. A feature in a respected publication, a case study on a partner's website, or a testimonial from a known client all feed the LLM's confidence. When your business is discussed credibly elsewhere on the web, the model has corroborating evidence to justify recommending you.

2. Clear, Structured Information About Your Business

LLMs struggle with confusing websites. If your business description is vague, your service offerings are buried, or your expertise isn't clearly stated, the model can't confidently recommend you. Conversely, if your website clearly articulates what you do, who you serve, and why you're different, the model can extract and understand that information.

This is where technical structure comes in. Schema markup, proper heading hierarchy, clear CTAs, and logical information architecture all make it easier for LLMs to understand your business. You're not optimising for a keyword-scanning algorithm. You're optimising for reasoning. You want to make it obvious to an intelligent system why you're the right recommendation.

3. Evidence of Expertise and Authority

LLMs are trained to recognize authority. If you've published thought leadership content, created resources that help people solve problems, contributed to industry conversations, or built a genuine body of work, the model recognises this. Thin, generic content doesn't work. Deep, insightful, expert-level content does.

This means your content strategy changes. Instead of optimising for search intent and keyword density, you're creating content that demonstrates real expertise. You're answering hard questions, sharing genuine insights, and building a reputation as someone who knows their domain.

Why Every Business Needs an LLM Optimisation Strategy Now

You might assume this is still niche—that most businesses aren't using AI for recommendations. You'd be wrong. Professional services firms are using ChatGPT to shortlist agencies. Marketers are using Perplexity to research tools. Founders are asking Claude which platforms they should build on. The shift is already happening, and it's accelerating.

The businesses losing out are the ones who optimised purely for Google. They built SEO-first strategies with thin content, backlink farms, and keyword manipulation. When LLMs encounter these sites, they don't trust them. The model detects manipulation. It looks for businesses with genuine authority instead.

Starting an LLM optimisation strategy now gives you two advantages. First, you're building credibility across the web while most competitors are still siloed in Google. Second, you're getting ahead of the curve before AI recommendations become the dominant discovery mechanism.

Building an effective LLM optimisation strategy requires three things working together: a well-structured, informative website that clearly communicates your expertise; high-quality content that demonstrates thought leadership and authority; and strategic PR that creates credible third-party mentions across trusted publications and platforms.

That's exactly what we do at Fortitude Media. We build AI-optimised websites that are clear and structured for reasoning, we create expert content that establishes genuine authority, and we run PR programmes that put your business in front of the right audiences. The result: when AI models make recommendations in your category, your business is the obvious choice.

The Opportunity Ahead

The next three years will see a fundamental shift in how people discover and evaluate businesses. AI recommendations will become standard. Recommendations that come through ChatGPT, Perplexity, and Claude will outpace Google search as the trust signal that drives decisions.

The question for your business is simple: will you be part of that story? Will you be the business that AI recommends confidently? Or will you be overlooked because your website is confusing, your authority is unclear, and your third-party credibility is thin?

The time to act isn't when AI recommendations are dominant. It's now, while you can still build foundational authority and positioning. Start with an audit. Understand what AI currently says about your business. Then build a strategy to become the obvious recommendation in your category.