
What Is LLM Optimization?
The primary goal of LLM optimization (LLMO) is to enhance the visibility and effectiveness of digital content, specifically for large language models (LLMs).
Unlike traditional Search Engine Optimization (SEO), which focuses on ranking in search engine results, LLMO aims to make content more accessible and comprehensible to AI language models, which increasingly mediate user interactions with online information.
This involves structuring content it maximize the likelihood of LLMs accurately interpreting, retrieving, and utilizing the information when responding to user queries.
The goal is twofold: first, to ensure your content is included in LLM training datasets by maintaining strong search engine visibility and clear content structure, and second, to format information in ways that align with how LLMs process and understand language.
Effective LLMO helps organizations ensure their content remains relevant and accessible in an AI-driven information landscape. This means not only being discoverable but also being represented accurately when LLMs generate responses about your topic, product, or service.
The end goal is to maintain digital presence and authority not just in direct search results, but also in the AI-mediated conversations and interactions that are becoming increasingly common in how people access and consume information online.
Why Is LLMO Vital For Your Future?
LLMO SEO is becoming crucial as AI language models increasingly shape how people discover and interact with online content.
By optimizing for both search engines and LLMs, businesses can ensure their digital presence remains strong not just in traditional search results, but also in AI-powered conversations and recommendations that are defining the future of information access.
LLM Growth & Shift In The Market
The growth of LLMs can’t be overlooked. In fact, In October 2024, Google’s market share dropped below 90% for the first time since March 2015 (source).
Furthermore, it’s predicted that 50% of search engine traffic will be displaced by 2028. This indicates a major shift in how people access information, with LLMs playing an increasingly prominent role
LLMs As Recommenders
Unlike traditional search engines that provide information, LLMs actively recommend brands, products, and services based on an individual’s query.
Similar to a sales assistant, LLMs can influence a person’s buying decisions, and this means that brands that are not visible in LLM output run the risk of losing on our highly qualified buyers and sales opportunities.
New Avenue For Brand Awareness
LLMs are an emerging technology that can provide new brand awareness apart from Google and other search engines.
They will become a go-to method for consumers looking to learn more about products and services, and since they are a new field, it’s important for SEOs and marketing professionals to learn how to gain a competitive advantage and secure visibility in LLM outputs.
Future-Proof Brand Visibility
As discussed, LLMs will play a significant role in how people search for brands, products, and services in the future. Investing in LLMO now will give your brand an advantage over your competitors as you take advantage of this new and important channel for brand awareness.
Supported By Your SEO Efforts
Since LLMs use data from third-parties, you can integrate LLMO strategies right into the SEO strategies that you are currently implementing.
For example, you can implement several tactics like long-tail keyword optimization, structured data markup, and LLM keyword research to create content that is great for today’s SEO efforts and tomorrow’s LLMO criteria.
How Do LLMs Process & Retrieve Information?
LLMs are highly advanced readers who extract massive amounts of information from online text, videos, and images to generate human-like responses. These responses are meant to be conversational and consultative, as LLMs aim to provide educated answers to specific questions.
LLMs rely on vast amounts of information from various third-party sources to understand the context and meaning of a question and its related answer.
Your website will not be included in the LLM’s training data if your product or services are not referenced in popular sources like Reddit, Wikipedia, and other online sources.
LLMs typically learn from data that’s easily accessible online, mainly through search engines. So if your website isn’t showing up in search results or is challenging to navigate, it’s less likely to be included in their training data. This means that good old-fashioned SEO practices aren’t just important for Google – they help your content get noticed by LLMs too.
What Is The Difference Between LLMO and SEO?
While LLMO and SEO differ in the types of search technologies used, they are related in the fact that both revolve around the processes to get information found based on a specific query.
Traditional SEO primarily uses backlinks based on authority, comprehensiveness, and relevance to deliver a list of relevant links to a query. LLMs utilize a similar set of data to generate responses, but they use information from a wider variety of sources, such as user-generated content, structured knowledge bases, and video content.
SEO strategies also differ from LLMO strategies in the way that search engines and LLMs look at content. Search engines tend to focus on keyword selections, the architecture of a website, and backlinks. LLMs use quotes, statistics, and citations to understand the relationship between entities and focus on entity research to build connections and associations between topics.
While SEO strategies are tied closely to LLMO strategies, it’s important to know how the two approaches to digital marketing differ so you can get the most visibility possible from LLM outputs.
How RAG LLMs Impact LLM Optimization
There are two main flavors of LLMs that you need to consider as you plan out your LLMO. First are self-contained LLMs that train on huge historical and fixed datasets. These LLMs are not connected to the internet, so they do not have access to current information and an example of this type of LLM is Claude.
The other type of LLM is a Retrieval-Augmented Generation (RAG) LLMs that retrieve live information from the internet in real time. Since RAG LLMs are connected to the internet they can provide updated, real-time information that pulls directly from the web. Examples of this type of LLM include Gemini, Perplexity, and ChatGPT.
RAG LLMs will play a big role in future LLMO strategies for several reasons:
Deliver Citations
Since RAG LLMs can access the internet in real-time, they are able to provide citations for their outputs. This is vital for LLMO since you want to maximize your brand’s visibility while also driving qualified traffic to your website. RAG LLMs, with proper LLM optimization, will get your brand in front of your audience across the greater online ecosystem.
Content Discovery
RAG LLMs will continue to lead the pack because their LLM training data is influenced by current information. Unlike self-contained models, RAG-based LLMs can give real-time information like weather reports, stock information, and even current events that can help you improve your brand’s positioning in relevant responses.
Improved Organic Visibility
Content that ranks well in traditional search engines is often the same content that is referenced by RAG LLMs. Keep this in mind as you optimize your SEO strategies, because your efforts with SEO and content marketing will play a vital role in your ability to improve your brand’s visibility in LLMs.
How To Optimize For LLMs
As Large Language Models reshape digital interaction, optimizing content for AI comprehension becomes essential.
Understanding how to structure and present information effectively ensures your content remains discoverable, accurately represented, and influential in an AI-driven information landscape.
1. Use Long-Tail Keywords
Similar to traditional SEO strategies, you should focus on long-tail questions that your products and services rank for. Instead of going after “short head” terms, you should focus on conversational phrases people would ask when interacting with Perplexity, ChatGPT, or Gemini.
2. Use Keyword Research In LLMs
It is a common practice in traditional SEO to use “People Also Ask” and the “Related” search terms in Google to come up with additional keywords to target. You can use a similar approach with Perplexity and other LLMs to see what other terms are related to the topic that you are trying to rank for in LLM output.
A great way to optimize your content in a conversational way that LLMs understand is by using the “Related” section in Perplexity. In this section you can see other ways Perplexity (and other LLMs) understand entities related to your search query.
You can use this information to expand your content whether it be a text document like a webpage or blog post, or a video script that you are building for a YouTube video.
3. Rich Snippets
Rich snippets are extra information that Google and other search engines show with details like ratings, images, and prices. You can feed this information to Google and LLMs through structured data markup to help your products and services stand out. This is extremely important for LLMO, especially if you are selling a product or good in ecommerce.
4. Schema Markup Data
While structured data markup will not directly help your visibility in LLM output, you should still use structured data to help LLMs (and search engines) understand your products and services better.
The idea here is to make your products stand out as much as possible for search engines. Since LLMs use search engines and scrape information from your website it makes sense to implement schema whenever possible to help LLMs understand your products and services better.
How-To Schema
Structured data that outlines step-by-step instructions, required materials, and completion time for tasks. Helps LLMs understand and present procedural content in a clear, actionable format.
Course Schema
Markup that defines educational content structure, including course name, provider, duration, and prerequisites. Enables LLMs to accurately represent and recommend educational opportunities.
Product Schema
Data structure that organizes product information including price, availability, reviews, and specifications. Helps LLMs provide accurate product details and comparisons in user queries.
Article Schema
Structured markup for news articles, blog posts, and other written content, including author, publication date, and topic. Helps LLMs understand content context and credibility.
Local Business Schema
Structured data format describing business details like location, hours, services, and contact information. Enables LLMs to provide accurate business information in location-based queries.
5. Invest In Backlinks and PR
Just like traditional SEO, you will need to continue to invest in link building and PR efforts to help associate your brand with specific terms. LLMs analyze the proximity of works and phrases to understand their meaning, and you can improve this relationship with backlinks and PR mentions.
Be sure to track web mentions and share of voice for specific terms in LLM outputs to understand what topics you are associated with and track what mentions have the most impact on your brand’s visibility.
6. Invest In Reddit Strategies
Getting your brand active in online communities can be a powerful way to increase visibility with LLMs.
By engaging authentically on platforms like Reddit through AMAs, working with influencers, and encouraging users to share their experiences with your brand, you create the kind of genuine community content that LLMs often reference and learn from.
7. Claim Your Wikipedia Listing
Getting your brand on Wikipedia can be a powerful way to boost your visibility with LLMs, since they often rely heavily on Wikipedia during their training.
The key is to approach it authentically. Your brand needs to be genuinely notable, with verifiable sources backing up your claims.
Before diving in, it’s smart to become an active Wikipedia contributor and understand their community guidelines. This way, when you work on your brand’s entry, you’ll be more likely to create content that meets Wikipedia’s standards for neutrality and reliability.
Final Thoughts
Let’s be honest about what we’re dealing with in the world of AI optimization – it’s a bit like trying to solve a puzzle with some missing pieces. While we can’t peek behind the curtain of how these AI models choose what content to highlight, that’s not stopping SEO experts from rolling up their sleeves and figuring it out through good old-fashioned testing and analysis.
Customer journeys were already complex, but AI has added a whole new layer of complexity. People are now interacting with brands through AI conversations, voice search, and all sorts of new channels we’re still trying to understand.
This means we need to think bigger about our brand presence. Since customers might discover you through an AI conversation rather than a traditional Google search, every touchpoint of your brand needs to be polished and consistent.
And when AI starts mentioning your brand more frequently, you’ll want your website ready to welcome and guide these visitors effectively.
Sure, optimizing for AI is a big undertaking, but if predictions about AI surpassing traditional search hold true, it’s an investment worth making. The key is building a strong, adaptable brand presence that works for both human visitors and AI systems.
Contact our team at StrategyBeam today if you are looking for a winning SEO and LLMO strategy for your business!