E-E-A-T & Information Gain

1. The Four E-E-A-T Signals

Experience is the newest addition to the E-E-A-T framework. It requires evidence of first-hand interaction with the subject matter — not just theoretical knowledge, but demonstrated practical engagement. For a web infrastructure company, Experience is evidenced by: case studies with measurable outcomes, before/after performance data, client testimonials with verifiable identities, and dated project records.

Expertise is the depth of knowledge demonstrated in the content. It is evidenced by: technical accuracy, use of domain-specific terminology, citation of primary sources (patent databases, academic papers, official documentation), and content that goes beyond surface-level summaries to provide actionable, specific guidance.

Authoritativeness is the recognition of expertise by third parties. It is evidenced by: inbound links from authoritative domains, citations in industry publications, mentions in AI Answer Engine responses, and a verified presence in the Google Knowledge Graph.

Trustworthiness is the reliability and transparency of the entity. It is evidenced by: a consistent identity across all platforms, transparent authorship attribution, accurate and up-to-date information, and a clear privacy policy and terms of service.

2. Information Gain Audit Protocol

Information Gain is the measure of how much new, useful knowledge a page adds relative to the existing corpus of content on the same topic. A page with low Information Gain — one that merely restates what is already widely known — is assigned lower ranking weight under Patent US125362233B1.

The Information Gain audit protocol has four stages:

Stage 1 — Corpus analysis: Identify the top 10 ranking pages for the target keyword. Extract the key claims, statistics, and frameworks they present.

Stage 2 — Gap identification: Identify what is missing from the existing corpus. What questions do users ask that are not answered? What data points are cited without primary sources? What frameworks are described without implementation detail?

Stage 3 — Unique value injection: For each identified gap, inject a unique value element: an original statistic, a proprietary framework, a first-hand case study, or a primary source citation that competitors have not used.

Stage 4 — Validation: After publication, verify that the page is cited by AI Answer Engines (Perplexity, Google AI Overviews) for the target query. AI citation is the strongest signal that the Information Gain threshold has been met.

3. Author Entity Schema

The Author Entity schema is the technical implementation of the E-E-A-T framework. It tethers the content to a verified human identity — a Person with credentials, affiliations, and a presence in the global Knowledge Graph.

Required Person schema properties for E-E-A-T compliance:

legalName: The author's full legal name (no abbreviations, no nicknames). jobTitle: A specific, descriptive title that signals expertise (e.g., "Industrial Infrastructure Architect" rather than "Web Developer"). worksFor: An Organisation schema block with the brand's full legal name, URL, and logo. sameAs: An array of URLs that cross-reference the author's identity across platforms — LinkedIn, Wikipedia (if applicable), Wikidata (if applicable), and any industry directories or professional registries. image: A high-resolution author photograph with appropriate EXIF metadata (GPS coordinates of the primary business location, IPTC copyright fields, alt text mapped to the Knowledge Graph entity). knowsAbout: An array of topics the author is an expert in, expressed as Wikidata entity IDs where possible (e.g., "Q180711" for Search Engine Optimisation).

The Author Entity schema must appear on every page of the site — not just the homepage or about page. This ensures that every page is tethered to a verified human identity, regardless of which page a crawler or AI model encounters first.

4. Knowledge Graph Tethering

The Knowledge Graph is Google's database of entities and their relationships. A site that is tethered to the Knowledge Graph — through sameAs cross-references, Wikidata IDs, and consistent identity signals — is treated as a known, verified entity rather than an anonymous source.

The Knowledge Graph tethering protocol:

Step 1 — Entity identification: Identify the Wikidata ID for every main entity on the site (the brand, the primary author, the service category, the target industry). If no Wikidata entry exists, create one.

Step 2 — sameAs injection: Add the Wikidata URL to the sameAs array of the corresponding schema block. Also add: the entity's Wikipedia URL (if applicable), the entity's LinkedIn URL, the entity's Google Business Profile URL, and any industry registry URLs.

Step 3 — Consistency audit: Verify that the entity's name, description, and identity signals are consistent across all sameAs URLs. Inconsistencies (different job titles, different company names, different profile photos) create disambiguation failures that reduce Knowledge Graph confidence.

Step 4 — Citation monitoring: Monitor AI Answer Engine responses for citations of the entity. Each citation is evidence that the Knowledge Graph tether is functioning correctly.

5. EXIF & Image Metadata Compliance

Patent US125362233B1 extends E-E-A-T signals to image metadata. Every image on a compliant site must carry a complete metadata manifest:

GPS Coordinates: Geo-tag images with the GPS coordinates of the primary business location. This creates a geographic identity signal that reinforces the LocalBusiness schema and supports local ranking.

IPTC Copyright: Set the IPTC Copyright Notice field to the brand's full legal name and the year of creation. Set the IPTC Creator field to the primary author's full legal name.

Alt Text: Write alt text that maps to the Knowledge Graph entity, not just a description of the image. For example: "Anthony James Peacock — Industrial Infrastructure Architect, LinkDaddy Build" rather than "man at computer".

ImageObject Schema: Every significant image must have a corresponding ImageObject JSON-LD block with: contentUrl, name, description (mapped to Knowledge Graph), author (linking to the Person schema), copyrightHolder, and geo (latitude/longitude of the primary business location).