The Evolution of Search: From SEO to GEO
TL;DR: Generative Engine Optimization (GEO) Explained
The rise of AI and Large Language Models (LLMs) is transforming search from a click-and-browse experience to a "zero-click" one. This means traditional SEO is evolving into Generative Engine Optimization (GEO). GEO isn't a replacement for SEO, but an enhancement, focusing on creating high-quality, trustworthy content that AI models can easily summarize and reference. To succeed, you need to be technically sound, produce fresh and long-form content, and ensure your digital footprint is visible across a variety of platforms.
Google Search or ChatGPT
The Evolution of Search: From SEO to GEO
For decades, the foundation of web search has been built on a simple premise: a user types a query, and a search engine directs them to a list of relevant websites. This predictable process gave rise to the entire industry of Search Engine Optimization (SEO), a powerful blend of technology and marketing that helped websites rank high in search results.
However, the rapid growth of artificial intelligence (AI), large language models (LLMs), and generative search is fundamentally changing this dynamic. Where search engines once funneled traffic to websites, AI-powered platforms now synthesize information from numerous sources to deliver a single, curated response. This creates a "zero-click" search experience, where users get their answers directly on the search page without needing to visit a single website. This shift from a destination-based search to a solution-based one is redefining online visibility.
This is the genesis of Generative Engine Optimization (GEO)—the practice of optimizing your content to be a trusted source for AI-driven search engines.
Why Generative Engine Optimization (GEO) Matters Now
As more and more users turn to AI assistants and generative search tools for quick answers, Generative Engine Optimization is becoming crucial for your website's discoverability. While SEO was about ranking your digital offering in search results, GEO is about becoming a reliable source that generative AI models will cite.
This doesn't mean traditional SEO is dead. On the contrary, GEO is best thought of as SEO with an enhanced focus on quality, clarity, and authority. In 2025, a strong traditional search ranking on Google and Bing is still the most effective way to be referenced by AI-powered search engines.
GEO focuses on LLMs and AI assistants that summarize, synthesize, and answer user questions without requiring external links. While the tech landscape is in constant flux, today's LLMs still use search APIs from major engines. They consistently favor highly-ranked content that features clear explanations and easy-to-understand formatting.
AI search results
How to Future Proof Your Website with GEO Best Practices
By combining the best of your existing SEO practices with new, AI-aware strategies, you can significantly increase the likelihood that your content will remain visible in the age of AI-powered search.
Be Visible Where AI Looks for Data
AI search engines act as content aggregators and pre-processors. Your content is unlikely to be cited if it only exists on a single niche blog. Expand your digital footprint across various platforms where AI tools gather data, such as reputable blogs, review sites, and online directories. Build brand citations by reaching out to journalists and authors and maintaining good digital marketing hygiene to maximize your overall visibility.
Ensure Content Is Server-Side Rendered
LLMs cannot render JavaScript. This means any core content that loads on the user's device (client-side rendering) is effectively invisible to AI crawlers. Sites built on frameworks like React or Next.js that rely on JavaScript for content are at a disadvantage. To ensure your information is detectable and readable by LLMs, make sure all your core content is either in static files or served with server-side rendering.
Keep Your Content Fresh and Timely
AI models are highly sensitive to content "freshness" or recency. To test this, we conducted a study across three major models—Perplexity, Gemini, and ChatGPT—using ten software-related search queries (e.g., "best project management software," "best antivirus software"). Our findings revealed a clear preference for recently published content:
- Perplexity: Cited sources with an average publication window of 2.4 months.
- ChatGPT: Cited sources with an average publication window of 5.4 months.
- Gemini: Cited sources with an average publication window of 6.2 months.
While our queries specifically sought current information, these results demonstrate that timeliness and recency are key criteria in the generative search experience. Regularly updating and publishing new content is vital for maintaining visibility.
Aim to Be Featured in Notable Roundups
A proven strategy in both brand marketing and SEO, getting your product or service featured in high-profile roundup lists is now considered a key GEO practice. Our research shows that cited sources from ChatGPT and Google Gemini often correlate with the top 10 search results on their respective search engines. This makes sense: the highest-ranking, most authoritative content is naturally the most trusted by AI models.
Focus on Long-Form, High-Value Content
Some website owners worry that Google's AI Overviews will reduce their click traffic. However, most of the lost clicks are for low-value queries that require quick, simple answers—something AI handles exceptionally well. Instead of competing on this front, shift your focus to publishing high-quality, long-form content. Enrich your articles with expert insights and unique perspectives that only you can provide. This "human-centered" content strategy prioritizes thoughtful, valuable information and is what will truly set your online offering apart from an AI-powered content aggregator.
Think in Terms of Passages, Not Just Keywords
The modern best practice for LLM-aware content is to break your writing into small, digestible segments that provide a complete answer to a specific query. This is also a core principle of creating meaningful and readable web content. As Google's own blog, The Keyword, notes: "By understanding passages in addition to the relevancy of the overall page, we can find that needle-in-a-haystack information you’re looking for." This semantic clarity makes your content easier for LLMs to understand, process, and cite.
Don't Block AI Crawlers
In the past, you may have been advised to block AI crawlers via your robots.txt file to prevent content scraping. However, we've reached a point of no return. Blocking AI crawlers today is counterproductive, as your content is likely already being used by AI models. To ensure you can benefit from this new normal, make sure your robots.txt file allows the following known bots:
User-agent: ClaudeBotUser-agent: Claude-WebUser-agent: anthropic-aiUser-agent: Google-ExtendedUser-agent: PerplexityBot
Keep an Eye on llm.txt, but Don't Rush to Adopt It
The llm.txt schema is an emerging solution for marketers and developers who want to control how LLMs interact with their content. However, adoption is currently low, and major LLMs like OpenAI do not consistently respect it. Our recommendation is to monitor its development but focus your efforts on more effective strategies for improving visibility, such as:
- Clean data structures
- Semantic clarity
- Server-side rendered content
- Publishing high-quality information
These practices are far more effective for enhancing your visibility across LLMs today.