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  "headline": "Experiment with Google Vertex AI Ranking API: Here's What I Found (Free Script)",
  "description": "Experiment with Google Vertex AI Ranking API: Here's What I Found (Free Script)",
  "datePublished": "2025-06-17T00:00:00.000Z",
  "dateModified": "2025-11-02T00:00:00.000Z",
  "url": "https://metehan.ai/blog/google-vertex-ai-ranking-api/",
  "category": "experiment",
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  "image": "/wp-content/uploads/2025/06/vertex-ap-ranking-api.png",
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  "articleBody": "For years, we’ve optimized for SERP positions. But what if we could look  *deeper*  — to see  **how semantically relevant**  a piece of content is according to Google’s own AI models?\n\nI built a custom workflow using:\n\n- `DataForSEO`  for SERP + content crawling\n- Google’s  **Vertex AI Ranking API**  to score semantic relevance\n- My own interpretation layer to map ranking position vs. AI understanding\n\nThe result? A practical way to audit  *what’s ranking*,  *why it’s ranking*, and  *what’s missing*.\n\nRead Google’s official blog post here:  [https://cloud.google.com/blog/products/ai-machine-learning/launching-our-new-state-of-the-art-vertex-ai-ranking-api](https://cloud.google.com/blog/products/ai-machine-learning/launching-our-new-state-of-the-art-vertex-ai-ranking-api)\n\n![google vertex ai ranking api](/wp-content/uploads/2025/06/google-vertex-ai-ranking-api-scaled.png)\n\n## Case Study: The Query “What is SEO”\n\nHere’s what I found when analyzing that query:\n\n### **SERP #2 → AI Score: 0.996**\n\n> Google’s own SEO Starter Guide\n\n- Comprehensive\n- Authoritative\n- Aligned with user intent\n\nNo surprise — it scored nearly perfect.\n\n### **SERP #5 → AI Score: 0.992**\n\n> A deeply technical guide buried on page one\n\n- High semantic match\n- Clean formatting\n- Clear, focused answers\n\nThis content deserves to rank higher — the AI knows it, even if the algorithm hasn’t caught up.\n\n### **SERP #6 → AI Score: 0.145**\n\n> A top-ranking page with  **shocking**  low relevance\n\n- Weak content\n- Likely ranking due to domain authority\n- Backed by site structure and aggressive internal linking\n\nIt ranks high — but  **not because of content quality**. This is where the opportunity lies.\n\n## What I Learned from Running 100+ Pages Through AI Scoring\n\nInstead of building “yet another SEO tool,” I used the API to reverse-engineer  **why bad content sometimes wins**, and why great content gets buried.\n\nThese were the  **3 most important takeaways**  from my analysis:\n\n### 1. Weak Content Can Still Rank — If Structure Carries It\n\nI found a page ranking  **#3 with only 300 words**  of fluff.\n\nWhy did it rank?\n\n- **47 internal links from the homepage**\n- Clean URL structure\n- Smart breadcrumbing\n\n**Site architecture**  was doing all the heavy lifting.\n\n### 2. Google Ranks  *Passages*, Not Pages\n\nWhen I isolated high-scoring pages, they didn’t rely on length, they relied on  **precision**.\n\nPages with just  **2–3 clear passages**  (scoring >0.900) consistently outperformed keyword-stuffed, bloated 2,000-word pieces.\n\n> “Answer first. Expand second.”\n\n>   That’s the pattern the AI favors.\n\n### 3. Internal Linking Drives Semantic Comprehension\n\nInternal linking wasn’t just a crawl signal — it shaped how the AI  **understood the topic**.\n\nWhat worked:\n\n- Contextual links to  **related**  content\n- Descriptive anchor text (not exact-match spam)\n- Logical topic clusters\n\nWhat didn’t:\n\n- Footer spam\n- Disconnected silos\n- Overused keyword anchors\n\nInternal linking =  **semantic scaffolding**.\n\n## The Process I Use\n\nHere’s my exact 5-step approach:\n\n1. **Run the analysis**  — Get Vertex AI scores for top 20 results\n2. **Find mismatches**  — High rank / low score =  *ranking without merit*\n3. **Deep dive winners**  — What makes 0.900+ pages special?\n4. **Audit the weak winners**  — Low-score pages ranking high? Follow the link trails\n5. **Execute precisely**  — Blend quality content with structural SEO\n\n## Download the Full Study + Scoring Script\n\nIf you’re curious about scoring your own pages or reverse-engineering competitors:\n\n    (function(w,d,e,u,f,l,n){w[f]=w[f]||function(){(w[f].q=w[f].q||[])\n    .push(arguments);},l=d.createElement(e),l.async=1,l.src=u,\n    n=d.getElementsByTagName(e)[0],n.parentNode.insertBefore(l,n);})\n    (window,document,'script','https://assets.mailerlite.com/js/universal.js','ml');\n    ml('account', '1481491');\n\n## Connect With Me\n\n- I share practical SEO experiments — not recycled advice.\n- ️I publish SEO tools, breakdowns, and findings in public. (Check my [GitHub](https://github.com/metehan777))\n- I test what others assume.\n\nFollow or connect if you’re into technical SEO backed by data:\n\n- [@metehan777 on X](https://x.com/metehan777)\n- [LinkedIn](https://www.linkedin.com/in/metehanyesilyurt)\n- [Substack](https://metehanai.substack.com/)\n- [YouTube](https://www.youtube.com/@metehanyesilyurtseo)",
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    "name": "Metehan Yesilyurt",
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