LLM optimization: how to get found by AI models

Large language models (or LLMs, from Large Language Models) are revolutionizing the way people search for and consume information.

Advanced platforms such as ChatGPT, Bard and Claude not only answer questions directly, but are able to generate detailed answers based on huge data sets and neural networks with billions of parameters.

In this context, LLMoptimization (or LLMO) has become critical for brands that want to be present within the answers provided by artificial intelligence models.

But it is not simply about traditional SEO: the LLMO requires a targeted strategy to understand the language of LLMs and adapt your content so that it is identified as a trusted source.

In this guide, we will explore the top six strategies for optimizing LLM, explaining how to make the most of this opportunity to stand out in an increasingly competitive landscape.

What is LLM Optimization?

LLM optimization is the set of techniques for increasing the visibility of your content within the responses generated by large language models such as ChatGPT, Claude and Bard.

Unlike traditional SEO, which seeks to rank content in search engines, LLMO focuses on getting your content cited and recommended by pre-trained AI models.

LLMs do not conduct real-time research; they rely on data sets they have been trained with. This means that your content must be clear, authoritative, and well-structured to be considered part of the responses they generate.

How does LLM optimization differ from traditional SEO optimization?

LLM optimi zation and traditional SEO optimization share the goal of making content more visible, but they target two completely different systems: search engines and large language models.

While traditional SEO focuses on ranking in SERPs (search engine results pages) by optimizing keywords, meta tags, and backlinks, LLMO aims to make content relevant to responses generated by artificial intelligence models such as ChatGPT, Bard, and Claude.

Perplexity’s results when asked what are the best shoes for running.

What does ChatGPT recommend for the same question.

The main differences include:

Focus on Content:
traditional SEO focuses on optimizing for specific keywords and traffic to the website. In contrast, LLM performance prioritizes authoritative, well-structured content that is easily understood by neural networks to be cited or used directly in AI results.
Data Structure:
in LLMO it is critical to use structured data, such as schema markup, to organize information so that pre-trained models can interpret and integrate it into their data sets. Traditional SEO, on the other hand, uses structured data primarily to enrich visual search results (such as rich snippets).
Conversational Queries:
LLMs excel atnatural language processing (NLP) and answer complex queries in a conversational manner. This means that LLMOs require content optimized for long-tail, natural language queries, while traditional SEO focuses on short, specific keywords.
Ultimate Goal:
traditional SEO aims to attract users to the website to generate traffic. LLM optimization, on the other hand, aims to provide content that LLMs can understand, extract, and integrate directly into their generated responses.

In summary, LLM optimization does not replace traditional SEO, but complements it, shifting the focus from mere visibility in search engines to presence in AI answers, which rely on billions of parameters to provide high-quality answers.

How to optimize LLM: key strategies

1. Create authoritative and reliable content

LLMs reward content that demonstrates experience, authority and trust. These qualities are essential because large language models seek information that is not only accurate but also reliable.

How to:

Demonstrate expertise: provide detailed and specific content based on up-to-date data. For example, if you write about technology, cite recent statistics or real case studies.
Use reliable sources: link your content to authoritative sites. For example, a medical article should cite peer-reviewed studies.
Update your content: LLMs prioritize recent information. Review and update your main articles frequently.
Involve experts: work with recognized professionals in your field to increase the credibility of your content.

In the image we can see how Perplexity considers these sites from which it takes its answers to be authoritative.

2. Use structured data and schema markup

Large language models are designed to analyze and understand well-organized content. The use of schema markup helps provide a clear structure to information, making it more easily interpretable by the neural networks that power LLMs.

How to:

FAQ outline: answer the most common questions clearly and concisely.
Schema HowTo: create step-by-step guides for complex processes.
Article Outline: use this outline for in-depth content such as blogs and white papers.
Product Outline: highlights important details such as prices and reviews.

Useful tools:

Plugins such as Yoast SEO or Rank Math for WordPress simplify the implementation of schemes.
Use the Google Structured Data Testing Tool to verify that the markup is correct.

Practical case:

A recipe site might use the HowTo diagram for a pasta recipe:

Ingredient list.
Clear numbered passages.
Total preparation and cooking time.
This structure helps LLMs generate accurate and detailed responses.

3. Optimize for conversational and long-tail queries.

LLMs excel atnatural language processing (NLP), which means they understand and respond to colloquially formulated queries. Optimizing your content for long-tail, natural language queries can increase your chances of being cited.

How to:

Study the language of the audience: analyze forums such as Reddit, Quora, and Google “People Also Ask” threads.
Frame subheadings as questions: for example, instead of “LLM strategies,” write “How to optimize content for LLM?”
Expand FAQs: answer the questions your audience frequently asks.

Practical case:

A technology article could answer questions such as:

“What are the best smartphones for taking pictures?”
“How does a neural network work in a pre-trained model?”
These NLP natural language queries are more easily recognized by LLMs.

4. Building topical authority with content clusters

Building authority on a specific topic is essential for LLMs, who favor sites that demonstrate expertise through in-depth, linked content. Content clusters are the ideal way to achieve this goal.

How to:

Create a pillar page: a comprehensive guide on a main topic, such as “LLM optimization.”
Link related articles: write sub-posts that elaborate on specific topics, such as “How to implement schema markup” or “Strategies for improving E-E-A-T.”
Use internal links: connect content together to create a logical network.

Practical case:

A fitness blog might have a pillar page on “HIIT training,” with related clusters on:

“The benefits of HIIT cardio.”
“How to start a HIIT program for beginners.”
“The best apps for tracking HIIT workouts.”

5. Earning Backlinks and Mentions

LLMs trust what is cited by reliable sources. For this reason, getting backlinks from authoritative sites is a crucial element of proper LLM performance.

How to:

Digital PR: pitch unique articles or research reports to the media.
Guest contributions: collaborate with industry blogs to get mentions and backlinks.
Original research: publishes white papers and surveys, which are naturally cited.

Practical case:

A technology company might publish a report on AI trends in 2025. This type of content is often cited by analysts and industry media.

6. Implement multi-format content

LLMs prefer clear, readable and well-organized content. Structuring your articles in different visual and textual formats can make a big difference.

How to:

Use bulleted lists for key processes.
Include tables for comparisons or data.
Add infographics with text descriptions to improve readability.

Practical case:

An e-commerce site might include a comparison table for products, accompanied by bulleted lists highlighting the main benefits of each item.

LLM optimization with Factory Communication

LLM optimization is not just a new trend, but an indispensable strategy for staying relevant in the age ofnatural language processing. Focus on high-quality, well-structured content that is optimized for the needs of large language models-only then can you ensure that your brand is included in the responses generated by models such as ChatGPT and Bard.

If you feel a little lost, don’t worry, we will help you through all these new processes that technology puts in front of us!