What is E-E-A-T in SEO?

E-E-A-T stands for Experience, Expertise, Authoritativeness, Trustworthiness. These are the criteria Google uses to evaluate the quality and credibility of content and its authors.

What is the link between E-E-A-T and GEO?

Generative AI search engines use E-E-A-T signals to select the sources they cite in their responses. Content with strong E-E-A-T signals is significantly more likely to be retained as a source by Google AI Overviews, ChatGPT and Perplexity.

How to strengthen E-E-A-T signals?

Create detailed author pages with Person Schema.org markup, publish expert sourced and factual content, obtain editorial backlinks, keep content up to date, and strengthen your Organization Schema with sameAs links to verified profiles.

E-E-A-T and GEO: How Expertise Boosts Visibility in Generative AI

In brief:

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is the primary filter used by generative AIs to select their sources

E-E-A-T-optimized content sees its AI visibility increase by 30 to 40% according to a Princeton study

99% of Google’s AI Overviews cite pages from the organic top 10

Brands cited in AI Overviews receive 35% more organic clicks

Only 2 to 7 domains are cited on average per AI response, compared to 10 traditional blue links

Reading time: 9 minutes

Understanding E-E-A-T in the Context of GEO
The Four Pillars of E-E-A-T Applied to GEO
Why E-E-A-T Dominates AI Source Selection
Concrete Strategies to Strengthen Your E-E-A-T for GEO
E-E-A-T and Structured Data: The Technical Lever
Measuring and Auditing Your E-E-A-T for GEO

Understanding E-E-A-T in the Context of GEO

Definition of E-E-A-T

E-E-A-T stands for Experience, Expertise, Authoritativeness, Trustworthiness. This evaluation framework, defined by Google in its Search Quality Rater Guidelines, serves as the reference for assessing the quality of content and the credibility of its source.

Originally designed for traditional SEO, E-E-A-T takes on a new dimension with the rise of GEO (Generative Engine Optimization). To understand the fundamentals of GEO, it is useful to consult our comprehensive guide on what GEO is.

From SEO to GEO: A Paradigm Shift

The transition from SEO to GEO radically changes how content is selected and presented. In traditional SEO, the goal is to appear in Google’s 10 blue links. In GEO, the challenge is to be directly cited in responses generated by AIs like ChatGPT, Perplexity, or Google AI Overviews.

In this context, LLMs only cite an average of 2 to 7 domains per response, far fewer than the 10 results on a traditional search page. The competition to be selected as a reliable source is therefore significantly more intense — and E-E-A-T becomes the decisive criterion.

The Four Pillars of E-E-A-T Applied to GEO

Experience

Generative AI values content that demonstrates concrete, verifiable experience with the subject matter. Simply rephrasing existing information is no longer enough. Experience signals include:

Case studies drawn from real-world situations
Field-based feedback with proprietary data
Practical examples that are documented and dated
Direct observations supported by measurable results

Content that states “based on an analysis of 200 campaigns conducted in 2025” will systematically carry more weight than a purely theoretical article in the eyes of a language model.

Expertise

Expertise manifests through technical depth and factual accuracy of the content. Generative AIs favor sources that demonstrate genuine mastery of the subject:

Correct use of domain-specific technical vocabulary
Ability to present nuances and subtleties in the analysis
Quantified data and verifiable statistics
Knowledge of the latest developments in the field

According to a BrightEdge study, pages written by identified experts with detailed biographies and verifiable qualifications achieve significantly higher AI citation rates.

Authoritativeness

Authority is built through external recognition and consistency of editorial presence. In GEO, brand search volume has become the strongest predictor of AI citation, with a correlation of 0.334 — even ahead of traditional backlinks.

Authority Signal	Impact on AI Citation
Brand search volume	Strongest correlation (0.334)
Citations by third-party sources	Strengthens perceived credibility by LLMs
Consistent presence on the topic	Favors selection as a reference source
Author profiles with qualifications	Trust signal for RAG systems

Trustworthiness

Trustworthiness is considered the central pillar of E-E-A-T, the one that encompasses all others. It relies on the transparency and verifiability of information:

Cited sources that are traceable
Publication and update dates clearly visible
Factual information that is accurate and up-to-date
Transparency about the identity of the author and the organization

“RAG systems retrieve sources, synthesize them, and sometimes cite them. The competition is no longer about who ranks, but about who becomes the source. Without reliability, no retrieval. Without clarity, no usage. Without accuracy, no citation.” — The Digital Bloom, 2025 AI Visibility Report

Why E-E-A-T Dominates AI Source Selection

Key AI Visibility Figures

The importance of E-E-A-T in GEO is confirmed by recent data. In 2025, more than 50% of Google searches display an AI Overview, and 1.5 billion monthly users interact with these enriched results. Meanwhile, AI-referred sessions surged by 527% between January and May 2025.

This transformation creates a new reality: 60% of searches now end without a click (zero-click), and the click-through rate in position 1 with an AI Overview is only 2.6%. To explore the impact of these changes across different AI platforms, it is worth consulting the comparison between Perplexity, ChatGPT, and Google SGE.

The E-E-A-T Filter of Language Models

Language models do not treat all sources equally. 99% of AI Overviews cite pages from the organic top 10, and 87% of ChatGPT citations correspond to the top Bing results. E-E-A-T acts as a selection filter: among well-positioned pages, only those that demonstrate high expertise and reliability are actually cited.

Princeton research on GEO confirms that optimization methods related to E-E-A-T — citing sources, integrating statistics, including expert quotes — can improve AI visibility by 30 to 40% compared to non-optimized content.

Divergence Between AI Platforms

A critical point to understand: each AI platform has its own source selection criteria. Only 11% of domains are cited by both ChatGPT and Perplexity.

Platform	Preferred Sources	Dominant Criterion
Google AI Overviews	Diversified cross-platform presence	Domain authority and trustworthiness
ChatGPT	Wikipedia, parametric knowledge	Expertise and brand awareness
Perplexity	Reddit content, real-time sources	User experience and freshness

For specific techniques on appearing in ChatGPT, you can refer to our guide on techniques to appear on ChatGPT.

Concrete Strategies to Strengthen Your E-E-A-T for GEO

Detailed and Marked-Up Author Profiles

Each piece of content must be attributed to a clearly identified author. Organizations that associated each response with a named expert and added detailed biographies saw an increase of 12 to 15% in session duration according to Deloitte Insights. The essential elements:

Full name, role, and professional qualifications
Biography detailing experience in the field
Verifiable links to professional profiles (LinkedIn, publications)
Schema.org markup of type Person or Organization

Regular Publishing and Content Updates

Generative AI favors sources that publish regularly within their area of expertise. A consistent editorial calendar and systematic updating of existing content strengthen the perception of reliability. It is recommended to:

Maintain a stable publishing frequency
Update existing articles with the latest data
Clearly indicate update dates via the dateModified property
Build comprehensive topical coverage around your domain

Optimizing Content for AI Extraction

Content structured to facilitate extraction by LLMs achieves better results. Techniques for optimizing content for generative AI include the use of lists, tables, and clear summaries.

According to available data, tactical changes such as adding precise statistics and structured answers can impact visibility in as little as 30 to 45 days.

E-E-A-T and Structured Data: The Technical Lever

The Role of Schema.org in E-E-A-T

Structured data constitutes the technical bridge between E-E-A-T and GEO. Pages implementing complete Schema.org markup have approximately a one-third greater chance of being cited in AI responses. In 2025, 85% of businesses plan to increase their investment in structured data to improve their AI visibility.

The most impactful markup types for E-E-A-T are:

Article with author, datePublished, dateModified
Person for author profiles with sameAs and jobTitle
Organization with foundingDate, areaServed, knowsAbout
FAQPage for structured frequently asked questions
BreadcrumbList for contextual navigation

For a detailed guide on technical implementation, it is recommended to consult our comprehensive guide on Schema.org structured data.

Implementing E-E-A-T Signals in Schema.org

The goal is to make machine-readable the E-E-A-T signals that are visible to users. Each article should include JSON-LD markup incorporating:

The author’s identity with their qualifications
The publication date and last modification date
The publishing organization and its area of expertise
Cited sources when relevant

Content detected as “GEO-ready” thanks to this markup is discovered up to 10 times faster by generative engines compared to organic SEO alone.

Measuring and Auditing Your E-E-A-T for GEO

E-E-A-T Performance Indicators

There is no official E-E-A-T score provided by Google or AI platforms. However, several indicators allow you to indirectly evaluate the quality of your E-E-A-T in a GEO context:

Indicator	What It Measures	Recommended Tool
AI citations	Number of times the domain is cited in AI responses	Specialized GEO tracking tools
Brand search volume	Perceived awareness and authority	Google Trends, Search Console
AI-referred traffic	Visits coming from AI platforms	Google Analytics (source/medium)
Citation rate vs. impressions	E-E-A-T effectiveness	Cross-analysis of data

E-E-A-T Audit: Essential Questions

To assess the strength of your E-E-A-T with GEO in mind, you should ask yourself the following questions:

Are authors clearly identified with verifiable biographies?
Are sources systematically cited and traceable?
Is the content regularly updated with visible dates?
Is the site cited by other authoritative sources in its domain?
Is Schema.org structured data correctly implemented?
Is topical coverage sufficiently deep and consistent?

In 2025, only 23% of marketers invest in prompt tracking and GEO measurement. This represents a considerable opportunity for those who structure their E-E-A-T approach now. To understand the fundamentals of artificial intelligence and its impact on search, it is essential to continuously follow industry developments.

Link building reinforces E-E-A-T signals: discover the best link building agencies. For SMBs looking to build credibility, consult our ranking of the best SEO agencies for SMBs.