Traditional SEO is evolving. With the rise of AI tools like ChatGPT, Google SGE (Search Generative Experience), Perplexity, and You.com, users are shifting from link-clicking to answer-seeking. This shift requires a fresh approach for digital marketers: Generative Engine Optimization (GEO) is optimizing content to be discoverable and useful to large language models (LLMs) and AI-driven search tools.
SEO vs GEO
Traditional SEO (Search Engine Optimization) focuses on helping web pages rank on search engine results pages like Google or Bing. It’s all about optimizing for algorithms that prioritize things like keywords, backlinks, page speed, and mobile friendliness. Users typically scan a list of links, click one, and then engage with the content.
In contrast, GEO (Generative Engine Optimization) is about optimizing content to show up in AI-generated answers. These platforms synthesize answers and often summarize the best information available without requiring a click. GEO focuses on creating clear, factual, conversational content that AI models can easily understand and cite. It also emphasizes building digital authority (such as consistent bios, structured content, and entity recognition) so your name, brand, or product is part of the language models’ knowledge base.
In a nutshell: SEO aims to rank your page. GEO aims to get you mentioned in the answer itself.
The Right Kinds of Content for AI
LLMs are trained on clear, fact-based, helpful, and human-sounding content. Now, it’s important to write for both people and machines.
Examples that work:
- Long-form content that answers specific questions clearly (like blog posts, FAQs, and pillar pages).
- Semantic keywords and natural language, such as "how to use a UGC creator" vs. “UGC service.”
- Content summaries — think bullet points, definitions, comparisons, and step-by-step guides.
The Sites That AI Pulls From
Different AI platforms rely on different sources. Some use Google-indexed pages, while others prioritize Reddit, YouTube, news articles, or high-authority forums.
Examples of high-ranking sites:
- Reddit (especially subreddits relevant to your niche)
- YouTube (captions and transcripts matter!)
Syndicate your own blog content or post summaries that link back to your owned channels.
Structured Data & Schema Markup
AI favors well-structured, machine-readable data. That includes schema markup that explains what your page is about.
Examples of Data:
- FAQ schema, How-To schema, and Article schema to key pages.
- Headings (H1, H2, H3) to break up content logically.
- Internal linking structures that show hierarchy and relevance.
Ensure your Identity is Clear Online
Generative AI often refers to entities: people, brands, products, or companies it recognizes. You want your name or brand to be understood as a known entity.
Examples:
- Use consistent bios, brand descriptions, and naming conventions across all platforms.
- Get listed in credible directories (Crunchbase, Product Hunt, G2, etc.) and reference your brand in multiple contexts.
Publish Fresh, Authoritative Content Regularly
AI favors content that’s current, trustworthy, and published by credible voices. "Digital authorship" is becoming the new ranking signal.
Examples:
- Maintain an active blog or thought leadership hub.
- Publish under a consistent author name with a bio attached.
- Repurpose TikToks, threads, or newsletters into blog posts to maintain freshness and depth.
- Social media helps you show up in AI search by building digital authority, influencing language models, and becoming part of the real-time web AI tools crawl and cite. Regularly posting content that is relevant to your brand, solves a problem your customer is having, and maintains consistency is key.
