If you haven’t started thinking about your LLM SEO strategy, the gap between you and competitors who have is already widening. Large language models, the technology powering tools like ChatGPT, Google’s AI Overviews, and Microsoft Copilot, are changing how people find information online. Not in a theoretical, future-tense way. Right now, today, a growing share of your potential customers are getting answers from AI rather than clicking through ten blue links. That changes what good SEO looks like, and it changes what you need to do about it.
What is an LLM and why does it matter for your SEO?
A large language model is a type of AI trained on vast amounts of text data to understand and generate human language. When someone asks ChatGPT a question, or when Google serves an AI Overview at the top of a search result, the answer is being generated or curated by an LLM. The model has, in effect, already done the searching for the user. It has read, synthesised, and summarised. The user may never visit your website at all.
This is not a reason to panic. It is a reason to adapt. Businesses that treat this as a threat tend to freeze. Businesses that treat it as a shift in the rules tend to move faster. An effective LLM SEO strategy is not about abandoning what worked before. It is about understanding which parts of traditional SEO still hold and which parts need rethinking.
How do LLMs decide which content to reference or recommend?
This is the question every business owner should be asking, because it is the one that actually determines whether your content gets surfaced or ignored. LLMs do not rank pages the way a traditional search algorithm does. They do not hand out position one and position two. Instead, they draw on content that demonstrates clear expertise, answers questions directly, and is structured in a way that makes it easy to parse and quote.
That last point matters more than most people realise. If your content is vague, padded, or written primarily to hit a word count, an LLM will either skip it or dilute it into nothing. If your content is precise, well-structured, and genuinely useful, there is a much stronger chance it becomes part of what the model draws on when constructing an answer. A solid LLM SEO strategy starts with writing content that actually answers the question being asked, not content that dances around it.
What does “demonstrating expertise” actually mean in practice?
It means specificity. Not “we help businesses grow their marketing” but “here is how a mid-sized B2B manufacturer restructured their lead generation and cut cost per acquisition by 40 percent.” It means naming things, explaining mechanisms, and not hiding behind generalities. LLMs are trained to recognise authoritative sources, and authority online still correlates strongly with the things it always has: depth of coverage, clarity of explanation, and consistency over time. If you want your content to feature in AI-generated answers, write like someone who actually knows the subject rather than someone who has read about it once.
This is also why experience matters. I have been doing this work since long before most agencies had heard of content marketing, let alone AI. The fundamentals of communicating expertise clearly have not changed. What has changed is how that communication gets evaluated and surfaced.
What should an LLM SEO strategy actually include?
A practical LLM SEO strategy is not a single tactic. It is a set of decisions about how you create, structure, and distribute content. The businesses that will do well here are the ones treating this as a content quality problem, not a technical SEO trick. Here is what that looks like in practice:
- Answer questions in full, within the content itself. Do not make readers scroll to find the answer. State it clearly, then expand. LLMs favour content that resolves the query without ambiguity.
- Use clear structure with descriptive subheadings. Heading tags still matter, but now they serve a dual purpose: helping search engines understand your content and making it easy for LLMs to extract specific sections as answers.
- Build topical depth, not just keyword breadth. A single well-researched article that covers a subject thoroughly will outperform ten shallow posts that each target a different keyword variation. Depth signals genuine understanding.
- Make your authorship and credentials visible. Who wrote this, why should anyone trust them, and what real-world experience backs it up. If that information is not on the page, you are asking both humans and AI to take your authority on faith.
- Maintain consistency across your content output. An LLM SEO strategy built on one strong article will not hold. The models that surface content tend to favour sources that have demonstrated expertise across multiple pieces on a topic.
If you want a broader look at how AI tools fit into your marketing workflow more generally, this piece on AI marketing tools worth your time covers the practical side without the hype.
Does traditional SEO still matter alongside an LLM SEO strategy?
Yes. The fundamentals have not been thrown out. Technical SEO, page speed, mobile performance, backlink quality, and well-structured metadata still matter because search engines still exist and still drive significant traffic. The shift to AI-generated answers does not mean Google has stopped indexing pages. It means there is now an additional layer, the AI Overview or the chat interface, sitting above the traditional results for many queries.
Your LLM SEO strategy and your traditional SEO work should reinforce each other. Content written to demonstrate genuine expertise will rank well in conventional search and be more likely to be referenced in AI-generated answers. These are not competing priorities. A B2B content marketing strategy that focuses on quality, clarity, and depth serves both ends simultaneously.
Where businesses go wrong is treating LLM optimisation as a separate project, layering it on top of weak foundations. If your existing content is thin, generic, or not performing, the right starting point is a proper marketing audit to understand what you actually have before adding more to the pile.
How do you measure whether your LLM SEO strategy is working?
Honestly, measurement here is still developing. Traditional ranking positions do not tell the whole story when a meaningful share of searches now end without a click. You will want to track direct traffic, branded search volume, and whether your content is being cited when you or your team test queries in ChatGPT, Perplexity, or Google’s AI Overviews directly. Prompt the tools with questions your customers would ask. See whose content comes up. If it is yours, something is working. If it is always a competitor’s, that is useful information too.
Beyond that, the same content metrics that have always mattered still matter. Time on page, return visits, and whether your content is generating enquiries or conversions. A strong LLM SEO strategy should ultimately drive business outcomes, not just AI citations for their own sake.
The businesses that will struggle most with this shift are those that have been producing content for volume rather than value, chasing keywords without saying anything worth reading. That model was already under pressure. LLMs have accelerated its decline considerably. The businesses that will benefit are those willing to invest in content that reflects real expertise and communicates it clearly, which has always been the right approach, and now carries even more weight.
If you want to talk through what a practical LLM SEO strategy looks like for your specific business, get in touch. I work with a limited number of clients at any one time, so if this sounds like the right conversation, it is worth having sooner rather than later.