SEO Vector Gap Analyser - Semantic Content Gap Analysis Tool

Compare your page against top-ranking competitors using sentence embeddings and vector space analysis. Identify the exact semantic topics your page is missing and get AI-written content recommendations.

How It Works

  1. Enter your target keyword and URLs for up to 5 competitor pages plus your own page.
  2. We crawl and extract the main content from each URL, stripping navigation, ads, and sidebars.
  3. Sentence embeddings are generated using the all-MiniLM-L6-v2 model, converting every sentence into a 384-dimensional vector representing its semantic meaning.
  4. UMAP projects all vectors into 2D space for visualisation as an interactive scatter plot.
  5. K-means clustering groups competitor sentences into topic clusters. Each cluster is checked against your page to identify gaps, shallow coverage, and well-covered areas.
  6. Claude AI generates specific recommendations including suggested headings, content points, and ranking rationale for each gap.

What Is Semantic Gap Analysis?

Traditional keyword gap analysis compares keyword lists between pages. Semantic gap analysis goes deeper: it uses natural language processing to understand what topics and concepts are covered, regardless of exact wording. If your competitors all discuss a concept using different phrasings, traditional tools miss it. Vector gap analysis catches it because meaning is captured in the embedding space.