What is LLMO (large language model optimization) and why is it important in 2025?
According to recent research by Ahrefs, traditional organic web clicks from search engines have decreased by approximately 34%, primarily due to AI-generated snippets directly answering user queries on platforms like Google. This dramatic shift underscores why optimizing your content for AI-driven search—known as large language model optimization (LLMO)—is rapidly becoming essential for online visibility in 2025.
What exactly is LLMO?
LLMO, or large language model optimization, is the practice of optimizing your content so that it's easily discoverable and cited by AI-powered tools like ChatGPT, Bard, Bing Chat, and other conversational AI assistants. Unlike traditional SEO, which primarily aims to rank high in search engine results pages (SERPs), LLMO focuses on being selected as the authoritative source in AI-generated responses.
Think of it this way: traditional SEO helps your content appear when users browse Google, while LLMO ensures your content is the one AI selects when directly answering user queries.
Why is LLMO crucial in 2025?
Here are three additional reasons why LLMO matters now more than ever:
1. The shift in user behavior
People are increasingly asking questions directly to AI assistants instead of browsing through traditional search results. By optimizing your content for these AI-driven interactions, you position your brand to capture this new, rapidly-growing traffic source.
2. Visibility and authority
AI-driven search is reshaping how authority is established online. When a large language model cites your content, it positions you as a trusted expert. This kind of credibility can significantly amplify your brand's visibility and trustworthiness.
3. Competitive advantage
Early adoption of LLMO strategies gives your brand a significant advantage over competitors who are slow to adapt. With AI-driven searches increasing exponentially, businesses that invest in LLMO now are setting themselves up for sustained success.
How do you implement LLMO?
Optimizing for large language models involves several key strategies:.
Clear, structured, and concise content
LLMs prioritize content that answers user queries directly and without fluff. Use clear headings, short paragraphs, and plain language. For instance, instead of saying “We provide scalable design systems for SaaS companies,” try “We help SaaS companies launch faster by building scalable design systems.”
Example: On your blog post titled "How much does a Webflow website cost in 2025?", include a sentence like: “A typical Webflow website for a SaaS company costs between €5,000 and €12,000 depending on design and CMS complexity.” This type of answer is perfect for an LLM to quote directly.
Semantic SEO and natural language variations
Use synonyms and contextually related terms to help LLMs understand your content. Don’t just target the phrase “Webflow SEO” — include related terms like “Webflow performance tips,” “technical SEO,” or “structured data in Webflow.”
Example: If your pillar page is “Webflow SEO Guide,” supporting articles might use variations like “optimize Webflow site speed,” “clean code in Webflow,” or “schema in Webflow CMS.”
Comprehensive FAQ pages
FAQs are easy for LLMs to parse and cite. Structure your FAQ sections clearly and use FAQ schema to increase their visibility.
Example: Add a question like “Is Webflow good for SEO?” and answer with: “Yes, Webflow gives full control over technical SEO, including meta tags, structured data, and fast page speed.” This can easily be pulled into Google’s AI Overview or tools like Perplexity.
Structured data and schema markup
Use schema types like FAQPage, Article, BlogPosting, WebPage, or HowTo to give LLMs structured insight into your content.
Example: For a “How to add schema to Webflow” article, use HowTo schema to mark up each step. This not only benefits Google snippets but makes it easier for LLMs to extract and cite how-to answers.
Topic clustering and internal linking
Group your content into thematic clusters around a pillar page. This builds topical authority, which search engines and LLMs interpret as expertise.
Example: A pillar page on “Webflow SEO” should link to detailed guides like “How to set up redirects in Webflow,” “Webflow vs WordPress for SEO,” and “Using structured data in Webflow.” Use internal links that clearly show relationships between content.
Content summaries and TL;DR sections
LLMs often cite short, summarized answers. Summaries at the top (or end) of a blog post help AI tools quickly grasp your message.
Example: At the start of your blog post, summarize key insights: “This guide covers key SEO tactics for Webflow, including meta tag optimization, site speed improvements, and internal linking strategies.” Add a TL;DR at the end for AI scanning.
Regular content updates
LLMs reward fresh content. Outdated stats, broken links, or old examples reduce your chances of being cited.
Example: Revisit your blog posts every few months. If Google releases a new Core Web Vitals update, revise your Webflow performance article to reflect this and add the updated date.
High-authority backlinks
LLMs are more likely to trust and cite content that’s been referenced elsewhere. Focus on guest posts, podcasts, or being cited on authoritative sites.
Example: Reach out to Webflow-focused blogs or digital marketing publications and contribute guest content. A backlink from a DR 70+ site not only boosts traditional SEO but also signals credibility to LLMs.
Final thoughts
In 2025, as the landscape of digital discovery evolves, integrating LLMO alongside traditional SEO isn't just wise—it's essential. By preparing your content strategy today for AI-driven discovery, you're ensuring your brand remains relevant, authoritative, and prominently positioned in the AI-driven future.
