As artificial intelligence continues to transform search experiences, the introduction of large language models (LLMs) like ChatGPT, Claude, and Perplexity has shifted how people find information online. These tools offer synthesized answers rather than traditional lists of blue links, leaving SEO professionals wondering how they can adapt their strategies to ensure their content shows up in these results.
In a recent discussion with SEO expert David Quaid, a wealth of insights were shared about how LLMs retrieve and rank content differently from traditional search engines like Google. This guide breaks down the conversation into actionable advice for improving your visibility within LLM environments.
Understanding LLMs: Not Your Traditional Search Engine
First, it’s essential to grasp the fundamental difference between LLMs and search engines like Google. While Google uses PageRank and crawls the web continuously to organize search rankings, LLMs use real-time queries to fetch data and synthesize responses. Here are the critical distinctions:
- LLMs are not static repositories of the web: Unlike Google, which maintains vast caches of indexed pages, LLMs fetch results in real-time and do not store massive quantities of web data.
- Query Fanouts: LLMs often break down a user’s prompt into multiple smaller queries, fetching relevant data from Google or other search engines (like Brave Search in the case of Claude). This is known as the "query fanout." Understanding how query fanouts work is crucial for optimizing LLM performance.
- Drift: Over time, the phrasing of queries made by LLMs changes dynamically. If your content aligns with these changing keyword patterns, you’re more likely to get picked up in LLM results.
How to Optimize for LLM Visibility
1. Start with Traditional SEO
LLMs rely heavily on search engines to find content. Therefore, if you’re not ranking in Google or Bing, you won’t show up in LLM results either. Create high-quality, well-optimized content with a focus on:
- Topical authority: Cover related topics comprehensively to demonstrate expertise.
- Keyword variety: Use a mix of long-tail and targeted keywords.
As Quaid puts it, "Ranking in LLMs starts with ranking in Google."
2. Track Query Fanouts and Adjust Content
To uncover the specific phrases LLMs use to fetch data, you can reverse-engineer their methods:
- Use tools like Perplexity or ChatGPT with live browsing enabled to test various search prompts related to your target keywords.
- Monitor Google Search Console to see which queries are bringing impressions but not clicks. These deep, long-tail queries often suggest what LLMs are fetching.
- Check query drift by testing how LLM results evolve over time. If a query includes dynamic modifiers like "2025", consider adding these elements to your content.
3. Leverage Search Console for Insights
Google Search Console provides invaluable data about your rankings and impressions. Quaid highlighted the importance of analyzing long-tail queries, particularly those where you rank on page 8 or lower but still see impressions. These queries often indicate high search volume and untapped potential.
- Action Item: Identify these queries and either expand your existing content to rank better or create new pages specifically targeting them.
4. Test and Iterate Quickly
One of the biggest advantages of LLMs is their real-time indexing. Unlike traditional organic SEO, where results can take weeks or months to appear, content changes can impact LLM rankings almost instantly. Quaid demonstrated this with a live example where he updated a blog post, re-indexed it in Google Search Console, and saw the changes reflected in LLMs within minutes.
- Action Item: Experiment frequently. Publish content targeting specific query patterns, test its performance in LLMs, and refine it as needed.
5. Forget Schema Hype
A common myth in SEO is that schema markup is essential for ranking in LLMs. According to Quaid, schema can be valuable in niche cases like flight schedules or review data but has little impact on regular blog content. Instead of overcomplicating your pages with unnecessary schemas, focus on creating high-quality, user-first content.
6. Monitor Referral Traffic from LLMs
Google Analytics and Looker Studio can help you track traffic originating from specific LLMs like ChatGPT, Perplexity, or Claude. Analyze this data to:
- Identify which pages are being referenced.
- Determine the specific keywords or phrases used to find your content.
- Track conversions or engagement metrics tied to LLM traffic.
7. Use Generative AI for Research, but Verify Data
Generative AI tools like ChatGPT can help uncover FAQs or popular topics your target audience is discussing, especially on platforms like Reddit. For example, by asking ChatGPT to summarize questions people are asking about a niche topic, you can quickly identify gaps or opportunities for content creation.
However, always verify the information before using it. Generative AI is prone to hallucinating facts, so cross-check everything against reputable sources.
Key Takeaways
- LLMs rely on traditional SEO foundations: If you’re visible on Google, you’re more likely to appear in LLM outputs.
- Understand and track query fanouts: LLMs break down prompts into multiple smaller searches. Use tools like Perplexity or ChatGPT to uncover these patterns.
- Analyze query drift: LLM queries evolve over time (e.g., adding dynamic elements like "2025"). Monitor and adapt your content accordingly.
- Schema is not a priority for most content: Focus on topical relevance rather than unnecessary technical implementations.
- Track referral traffic: Use Looker Studio or Google Analytics to monitor clicks from LLMs and optimize based on performance data.
- Experiment frequently: Update content and test how quickly it impacts LLM results. Use real-time indexing to your advantage.
- Leverage AI for research cautiously: Use AI to generate ideas but verify all data for accuracy.
Conclusion
As LLMs continue to reshape the search landscape, SEO professionals must adjust their strategies to stay ahead of the curve. By understanding how LLMs retrieve and process content, you can position your website for maximum visibility in this new era of search. Prioritize traditional SEO best practices, track query patterns, and experiment with real-time updates to ensure your content is optimized for future search trends.
LLMs may represent a shift in how users find information, but the core principles of SEO - creating relevant, high-quality content - remain unchanged. By combining these fundamentals with an understanding of how LLMs operate, you’ll be well-positioned to thrive in AI-powered search environments.
Source: "AI & LLM Visibility: A Practical Guide for Ranking in AI Results" - Edward Sturm, YouTube, Nov 10, 2025 - https://www.youtube.com/watch?v=ZXR1HvUU1kI
