Content and Semantic SEO Audit

SearchMinistry Media's content and semantic audit maps pages against the full entity space of each topic, measures topical authority against ranking competitors, and identifies the specific content gaps, thin pages, and intent mismatches preventing better rankings. We apply LLM retrieval science: semantic chunking analysis, entity coverage mapping, and information gain scoring across the entire content inventory.

Why Thin Content and Entity Gaps Suppress Rankings

Google's Helpful Content system evaluates whether a page demonstrates genuine expertise about its subject matter. Pages that describe a topic without naming the relevant entities, citing authoritative sources, or explaining cause-and-effect relationships rank below pages that do. For AI systems including Google AI Overviews and ChatGPT Search, pages with repeated keywords across H2 headings produce embedding vectors too similar to retrieve independently, reducing the number of queries the page can answer.

How the Semantic Audit Evaluates Content

  • Entity Coverage Mapping: Primary entity identification per page, related entity gap analysis against ranking pages, authority source citation audit, entity chain consistency across sections.
  • Topical Authority Assessment: Topic cluster completeness mapping, competing page entity comparison, missing subtopic identification, internal link architecture for topical signalling.
  • Content Quality Scoring: Thin content identification, duplicate and near-duplicate content detection, search intent alignment per page type, information gain scoring vs top 5 ranking pages.
  • AI Retrieval Readiness: Semantic chunking quality at H2 boundaries, answer-first formatting compliance, FAQ schema and structured data presence, LLM citation probability scoring per section.