We’ve been noticing something interesting lately. More and more people are finding Collective42 not just from traditional Google searches but from AI-generated responses, like those provided by ChatGPT. It’s not just us either. Clients and colleagues across the industry are seeing the same trend. So what’s behind this shift, and how do we adjust our approach?
How LLMs Recommend Results
When you ask ChatGPT a question, it follows a detailed process:
- Deep Intent Analysis: First, it carefully analyzes your question to understand your real goal, not just the keywords.
- Internal Knowledge Check: It checks its extensive internal knowledge from training data covering billions of documents.
- Real-Time Web Search (when needed): If more recent information is necessary, the AI performs a quick live search, crafting precise queries for relevant, updated data.
- Cross-Checking and Filtering: It carefully evaluates results for reliability, freshness, and relevance.
- Final Recommendation: Finally, it synthesizes everything into clear, concise recommendations tailored to your request.
This process differs from traditional SEO, which typically targets Google’s ranking algorithms and search results.
Traditional SEO vs. AI-Driven Discovery (and GEO)
SEO has historically been about optimizing websites for Google’s search rankings, focusing on keyword targeting, technical SEO (site speed, mobile optimization, structured data), quality content, and authoritative backlinks.
But a new era is emerging. AI-driven discovery, or what’s starting to be referred to in some circles as GEO (Generative Engine Optimization), introducing a different set of signals and criteria. GEO as a term might not stick (we’re not huge fans of the name), but the idea behind it reflects a real shift in how people are discovering information.
Instead of relying solely on Google’s traditional rankings, AI and generative engines evaluate websites based on:
- Content Clarity and Structure: AI favors clearly structured content that directly answers user questions.
- Domain Authority and Trust Signals: AI continues to value domain authority but also assesses credibility and content quality.
- Semantic and Intent Matching: Rather than just keyword matching, AI deeply analyzes semantic relationships and user intent.
What This Means for Marketers
Adapting to this shift means:
- Clear, Structured Content: Ensure your content is easy to read, structured logically, and provides concise answers to common questions. For example: clearly defined FAQs or bulleted key points.
- Authority and Freshness: Regularly update your site with current, reliable content. For instance: consistently refreshed blog posts, updated case studies, or accurate pricing pages.
- Real Answers, Not Fluff: Create content genuinely helpful to readers that directly addresses common queries or problems. For example: step-by-step guides, straightforward solutions, or actionable insights.
SEO and AI Optimization: The Road Ahead
We envision traditional SEO and AI optimization blending together. While core SEO principles like clarity, relevance, and authority remain important, specific tactics will evolve:
- AI-Friendly Schema and Structured Data: Clearly structured data and schema markup become crucial to help AI accurately understand and share your content.
- Cross-Platform Consistency: Consistent, accurate, and structured content across all channels enhances AI visibility.
What’s Next?
This is just an initial look at what we see changing. There’s a lot more depth to this topic, and we’ve been actively testing, talking, and learning alongside our clients and industry friends.
If you’re seeing these shifts too, or just curious about how this evolving space might impact your digital strategy, we’d love to talk more. Just reach out.