Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines скачать в хорошем качестве

Keywords Aren’t Enough. Start Using Vectors to Rank on Google and Other AI Engines

👉 Try SE Ranking free for 14 days https://seranking.com/sign-up.html?ut... 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. In this video, we break down how modern search engines actually understand content, why traditional keyword analysis is no longer enough, and how vector embeddings work — with real, hands-on demos. 🔑 What you’ll learn: Vector SEO 101 – why Google moved from “strings” → “things” → vectors Cosine similarity, explained simply – how a 0–1 score measures topical relevance Content gap discovery – export SERPs from SE Ranking, vectorise them with the Gemini API, and uncover hidden subtopics keyword tools miss Internal-link goldmines – use Screaming Frog’s new embedding feature to surface link opportunities based on meaning, not just anchor text Hands-on demo – a Python/LangChain mini-app (no coding required) that scores your page vs a competitor for “What is SEO” and pinpoints missing sections Action checklist – four practical takeaways to future-proof any site for AI-powered search If you work in SEO, content, or digital marketing, this will change how you think about optimization. 🛠 Tools & resources shown: SE Ranking – SERP & keyword exports with real-time competitor data Screaming Frog 20.0 – built-in Gemini embeddings & similarity reports Gemini / Hugging Face AI – free APIs for vectorising content chunks LangChain mini-app – open-source script to score pages and suggest missing sections 👍 Like the video if it helped 💬 Drop your questions or thoughts in the comments — we read them all 🔔 Subscribe for more insights 👉 Take the free “AI for SEO” course at SE Ranking Academy → https://seranking.com/academy/ai-for-... 👉 Connect with Ryan Shelley on LinkedIn:   / ryancshelley   Chapters: 00:00 – SEO changed: Why keywords aren’t enough anymore 01:17 – What are vector embeddings? 02:27 – Cosine similarity explained 02:57 – Content optimization with embeddings (real examples) 03:50 – Content gap analysis & topic clustering (SE Ranking demo setup) 06:15 – Live demo: Scoring “What Is SEO” with a competitor 08:11 – Internal linking with embeddings (Screaming Frog walkthrough) 13:55 – Multimodal embeddings & AI search 14:45 – 4 key takeaways to future-proof SEO #seo #aiseo #semanticsearch Stay connected: 🌐 SE Ranking: https://seranking.com/?utm_source=you... 🎓 SEO Academy: https://seranking.com/academy.html?ut... 💬 SE Ranking SEO Community   / 1916042605357814   🔹 Facebook:   / serankingcom   🔹 X (ex-Twitter):   / seranking   🔹 Instagram:   / se_ranking