entity-audit

Entity Audit — Phase 9

Executive Summary

Entity optimization is the bridge between traditional SEO and AI search visibility. Google's Knowledge Graph powers both the traditional Knowledge Panel and AI Overviews — businesses with strong entity signals get cited in AIO at higher rates than those without. In 2025, the minimum viable entity footprint is: GBP verified + 7+ sameAs connections + consistent NAP across all platforms + Wikidata entity. ChatGPT and Perplexity reference businesses with complete Wikidata entries 3× more than businesses without. The 30-minute fix with the highest impact: add sameAs properties to LocalBusiness schema (links to GBP, Facebook, LinkedIn, Yelp, BBB, Instagram, Wikidata) — this single action strengthens entity consolidation significantly.

2025 entity benchmarks:

• sameAs count for Knowledge Panel eligibility: 7+ authoritative sources (Google's Knowledge Vault threshold)
• sameAs 0–3: weak entity — Knowledge Panel very unlikely; 7–9: competitive; 10+: strong
• E-E-A-T entity signal: named author/owner with Person schema = measurable trust increase for YMYL and local service categories
• AI recognition rate: businesses with Wikidata entry cited 3× more by ChatGPT/Perplexity
• knowsAbout schema property: signals topical expertise domain directly to Google NLP
• Most specific @type matters: PlumbingContractor not LocalBusiness — specificity = entity clarity

Numbered Action Plan:

Immediate (30-Minute Wins)

1. Add sameAs links to LocalBusiness schema — Add "sameAs": [...] array with GBP URL, Facebook, LinkedIn, Yelp, BBB, Instagram, Twitter/X, Wikidata (if exists). Each is a separate entity consolidation signal. Effort: 30 min. Priority: 25 (5×5).
2. Change @type to most specific type — If currently "@type": "LocalBusiness", change to specific type (e.g., PlumbingContractor, Dentist, Attorney). Effort: 5 min. Priority: 15.
3. Add knowsAbout to Organization schema — Add the 5–7 core service entities the business is authoritative on. This directly signals topical expertise to Google's NLP and AI systems. Example: "knowsAbout": ["Drain Cleaning", "Water Heater Installation", "Emergency Plumbing", "Sewer Line Repair", "Tankless Water Heaters"]. Also add knowsAbout to Person schema for the owner/key staff. Effort: 15 min. Priority: 20.

Short-Term (Week 1–2)

1. Create Wikidata entity — If business has significant web presence (news mentions, 3+ external references): create Wikidata entry with name, type, location, website, founding date, sameAs links. Effort: 2–4 hrs. Priority: 16.
2. Add Person schema for owner — Create author page for business owner with Person schema: name, jobTitle (specific), credentials, worksFor → business entity, sameAs → LinkedIn. Effort: 1–2 hrs. Priority: 16.
3. Fix entity attribute inconsistencies — Audit: business name format, address format, phone format across website/GBP/Yelp/BBB/Facebook. Any variation = entity fragmentation. Fix the ≤3 platforms causing inconsistency. Effort: 1–2 hrs. Priority: 20.
4. Validate all schema — Run Rich Results Test (search.google.com/test/rich-results) + Schema Markup Validator (validator.schema.org) on homepage and top service pages. Fix any errors (invalid @type, missing required properties). Effort: 1–2 hrs. Priority: 20.

Medium-Term (Month 1–2)

1. Build topical entity associations — Publish 25+ articles on primary service cluster (entity co-occurrence accumulates). Get cited alongside industry terms in local publications. Add about + mentions schema to key pages. Effort: Ongoing.
2. Create team author pages — For each key team member: create /team/[name]/ page with Person schema, headshot, credentials, linked blog posts. Strengthens E-E-A-T author entity signals. Effort: 2–4 hrs/person.
3. Earn entity mentions — Pitch local news, industry publications, community platforms. Each mention = entity co-citation = strengthened Knowledge Graph. Effort: 4–8 hrs/mention.

Why Entities Matter in 2025–2026

Google's search engine is fundamentally entity-based. Rankings are increasingly driven by whether Google understands:

1. What your business IS — entity type, attributes, relationships
2. What topics you're authoritative on — topical entity associations
3. Where you exist — local entity with verified location signals
4. Who you're connected to — entity relationships: people, orgs, places

Strong entity presence = trust = better rankings AND AI visibility. In 2025:

• AI Overviews pull entity-structured data as primary citation sources
• ChatGPT/Perplexity reference businesses with complete Wikidata entries 3× more
• Google's Knowledge Vault — entities with sameAs coverage from 7+ authoritative sources achieve Knowledge Panel significantly faster

Step 1: Read Project Context

Read {AUDIT_DIR}/intake-data.md — business name, URL, location, services. Read {AUDIT_DIR}/competitor-profiles.md — competitor entity signals. Read {AUDIT_DIR}/local-findings.md — GBP completeness (feeds entity graph).

Tools for this phase: | Tool | Purpose | Cost | |------|---------|------| | Google Cloud NLP API | Entity extraction from page content (salience + type + sentiment) | Free ($0/1K calls) | | InLinks | NLP entity analysis, topic wheel, entity-based internal linking | Paid | | Kalicube Pro | Brand SERP entity completeness, entity clarity score, Knowledge Panel tracker | Paid | | Wikidata (wikidata.org) | Direct entity creation/editing — #1 Knowledge Panel trigger | Free | | Google Rich Results Test | Schema entity validation | Free | | Schema Markup Validator (validator.schema.org) | Entity schema syntax check | Free | | Otterly.ai | Monitor AI mention frequency (entity recognition across AI assistants) | Paid |

2025 Entity Context: Google's "Entity Home" concept means each business should have one authoritative page consolidating all entity attributes. An incomplete entity = fragmented Knowledge Graph = weaker rankings. Wikidata entry + GBP + 7+ sameAs connections = minimum viable entity footprint for Knowledge Panel eligibility.

Step 2: Business Entity Recognition Tests

Test 1: Knowledge Panel Check

Search Google for each:

| Query | Knowledge Panel? | Type | Completeness | |-------|----------------|------|-------------| | [Business Name] | Yes/No/Partial | Local/Brand | [X attributes showing] | | [Business Name] [City] | Yes/No/Partial | | | | [Business Name] [primary service] | Yes/No/Partial | | |

Status categories:

• ✅ Full Knowledge Panel — entity well recognized
• ⚠️ Partial — GBP card shows but no full panel (entity weak)
• ❌ No panel — entity not in Knowledge Graph

Test 2: AI Assistant Entity Recognition

| Query | Platform | Business Mentioned? | Accuracy? | Source Cited? | |-------|---------|--------------------|---------|--------------:| | "Tell me about [Business Name]" | ChatGPT | Yes/No | Yes/No | | | "What is [Business Name] in [City]?" | Perplexity | Yes/No | Yes/No | | | "[Best service] in [city]" | Google AIO | Yes/No | Yes/No | |

Test 3: Wikidata Check

Visit wikidata.org → search business name:

• Wikidata entity exists? Q-number: [Q_______]
• If exists: attribute completeness (names, location, website, founded, industry, sameAs links)?
• If not: does business qualify? (Must have coverage in reliable external sources, not just website)

Step 3: Entity Attribute Consistency

For a local business entity, Google expects these attributes consistently across ALL web properties:

| Attribute | Website | GBP | Schema | Wikidata | Consistent? | Action | |-----------|---------|-----|--------|----------|------------|--------| | Legal business name | | | | | ✅/❌ | | | Brand/trade name | | | | | ✅/❌ | | | Business @type (e.g., PlumbingContractor) | | | | | ✅/❌ | | | Street address (exact format) | | | | | ✅/❌ | | | City, State, ZIP | | | | | ✅/❌ | |