Ryan Shelley
Key takeaways
- 0:00Traditional keyword analysis is insufficient; search engines now understand meaning through vector embeddings rather than exact text matches.
- 2:27Cosine similarity measures semantic relevance on a 0–1 scale, where 1 means identical meaning and 0 means no relationship.
- 3:11Vector-based content optimization reveals that pages with unrelated keywords (like 'reliable family vehicle' and 'dependable car for parents') address the same user intent.
- 9:26Screaming Frog's embedding feature with Gemini API enables internal linking discovery based on semantic relevance, not just anchor text or keywords.
- 14:35Vector embeddings are already core to Google's ranking and LLM-based search; the question is whether you optimize for how they work today.
In Ryan Shelley's words
“Search engines don't rank pages the way they used to. SEO has moved beyond exact keyword matching—today, vector embeddings, semantic search, and AI measure meaning and relevance.”
Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines0:00
“Traditional keyword analysis is becoming insufficient. When somebody searches 'best smartphone 2025,' they're not just looking for those exact words. They want a comprehensive comparison of things like battery life, camera quality, and price versus performance.”
Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines1:04
“Words with similar meaning are clustered together, while unrelated concepts sit further apart. For example, terms like king and queen would be positioned closer together because they're related, but apple and banana would be near to each other because they live in the fruit neighborhood.”
Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines2:08
“This isn't future technology. This is current reality. The question isn't whether search engines will use embeddings, but whether you'll be optimizing for how they already work today.”
Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines14:35