Entity & Topical Authority Mapper for Local Business — AI Citation Score
Extract entities, score topical authority across 6 GEO factors, and find the gaps holding you back from AI citations.
How to use this tool
- 1Enter your main topic
Type the keyword or topic your content is targeting - e.g. "content marketing" or "technical SEO auditing". This calibrates the topic density scoring.
- 2Paste your content
Paste the full text of your article, landing page, or blog post. Include headings, body paragraphs, FAQ sections, and any statistical claims for the most accurate score.
- 3View entities and score
The tool extracts and classifies all entities, displays a topical authority score across 6 GEO factors, and shows you which to fix first for the biggest authority lift.
How this tool helps for Local Business sites
Topical authority for for local business sites depends on how well search engines understand the entities and relationships your content covers. This mapper visualises your entity network, identifies authority gaps, and shows for local business sites exactly which topics to cover next to strengthen their semantic footprint.
Local businesses compete primarily in Google's Local Pack and Maps results, where proximity, relevance, and prominence determine visibility. Unlike national SEO, local ranking depends heavily on Google Business Profile optimisation, consistent NAP citations, and local review signals. Businesses serving specific service areas must also balance location page creation with avoiding thin content penalties.
for Local Business SEO tips
- Optimise your Google Business Profile with complete categories, weekly posts, and Q&A responses since the local pack drives most local clicks.
- Build individual service-area pages with unique content about each neighbourhood or town rather than just swapping city names in templates.
- Actively request reviews mentioning specific services because review content and keywords directly influence local pack ranking positions.
The 6 topical authority factors explained
Content depth (800+ words)
Comprehensive content is the first signal AI systems use to assess authority. Pages under 500 words rarely achieve strong topical authority. The threshold is 800+ words for most topics, 1200+ for competitive ones.
Topic & entity coverage
Entity density and diversity tell AI systems whether a page covers a topic broadly enough to be trustworthy. Aim for 8+ distinct entities related to your main topic, across at least 3 entity types.
Content structure
Structured content (headings + clear paragraphs) is easier for AI extraction algorithms to parse. Well-structured pages are cited 4× more often than unformatted text dumps.
Definitions & explanations
AI systems favour definitional sentences ("X is a...", "X refers to..."). These are the most commonly extracted passage types for knowledge-panel and citation answers.
Data & statistics
Pages that include verifiable statistics and research citations are perceived as more authoritative. Even rough benchmarks ("studies show X%...") improve citation rate.
FAQ & question signals
Pages with embedded questions and direct answers win disproportionate PAA, featured snippet, and AI cite slots. Two or more questions significantly improve the GEO score.
Why entity optimisation matters for AI search
Google runs on entities, not keywords
Google's Knowledge Graph stores billions of entities and relationships. When your content covers the right entities, Google can confidently associate your page with a topic - leading to higher rankings independently of exact keyword density.
AI models cite entity-rich content
ChatGPT, Perplexity, and Google AI Overviews preferentially cite pages that clearly define concepts, reference specific organisations and products, and connect entities with verified relationships. Thin content with limited entity coverage is consistently ignored.
Entity diversity beats repetition
A page mentioning five different entity types (concept + product + organisation + person + event) signals broader expertise than 50 mentions of a single keyword. The scoring system rewards entity type diversity explicitly.
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