Have you ever felt uncertain about the quality and reliability of content published on your website? Or wondered whether a page would pass the scrutiny of Google's quality raters? These are questions that matter more than ever, because the stakes have changed. EEAT (Experience, Expertise, Authoritativeness, and Trustworthiness) is no longer just a factor in traditional search rankings. It now acts as a gatekeeping filter for whether your content gets cited by AI-powered search tools like Google AI Overviews, ChatGPT, and Perplexity.
This is where our Google Colab script comes in. Using AI, it evaluates the EEAT signals of any URL, returns a final score, explains the reasoning behind that score, and gives you concrete suggestions to improve the page. You can even assess multiple URLs at the same time.
Before we get into how the script works, it helps to understand what EEAT actually measures, how each component is evaluated, and why getting it right is now critical for both traditional SEO and AI search visibility.
What EEAT means and why it matters now more than ever
EEAT stands for Experience, Expertise, Authoritativeness, and Trustworthiness. Google introduced this framework in its Search Quality Rater Guidelines to help human evaluators assess the quality of web content. But its influence has expanded well beyond human raters.
Today, Google's algorithms use EEAT signals to decide which pages rank well in organic results. More importantly, AI systems, including Google's own AI Overviews, use these same signals to determine which sources get cited. If your page lacks strong EEAT, it is unlikely to appear in AI-generated answers, regardless of how well it ranks in classic search.
EEAT in traditional SEO vs. AI-powered search
In classic Google SEO, EEAT worked as a quality gradient. Pages with stronger signals tended to rank higher than those with weaker signals, but they could still rank at some level.
In AI-powered search, EEAT functions more like a binary filter. Either your content meets the threshold to be considered a credible, citable source, or it gets excluded entirely from AI-generated responses. This shift makes EEAT assessment far more urgent for any site that wants visibility in the modern search landscape.
Different AI platforms also weigh signals differently. Google AI Overviews heavily favor structured data and on-page authority signals. ChatGPT and Perplexity tend to draw from sources with strong external recognition, such as backlinks, citations, and earned media coverage. A multi-platform approach to EEAT is now a practical necessity, not an optional extra.
Breaking down each EEAT component
Understanding each component in concrete terms makes it much easier to evaluate and improve a page. Here is what each one actually means and which signals matter most.
Experience: First-hand, real-world content
Experience refers to direct, personal involvement with a topic. It is the difference between someone who has actually used a product and is reviewing it, versus someone who compiled information from other reviews without using the product themselves.
Google's quality raters are trained to spot this distinction. Generic how-to content that could have been written by anyone is rated lower than content that demonstrates genuine familiarity with the subject. Signals that indicate real experience include:
- Personal accounts, case studies, or real examples from the author's own work.
- Specific details that only come from hands-on involvement (exact figures, personal observations, lessons learned).
- Photos, screenshots, or original data that the author produced themselves.
- Content that acknowledges limitations or nuances a non-practitioner would likely miss.
When our script evaluates a URL, it looks for these markers of genuine experience versus content that appears assembled from secondary sources.
Expertise: Visible credentials and domain knowledge
Expertise means the author or publisher has the knowledge, skills, or qualifications to speak credibly on the topic. For YMYL (Your Money or Your Life) content, such as medical, legal, or financial topics, formal credentials matter a great deal. For other topics, demonstrated knowledge and consistent depth of coverage can serve as expertise signals.
The key word here is visible. Expertise that is not communicated to readers and search engines does not count. Concrete signals include:
- A detailed author bio that explains the writer's professional background and relevant experience.
- Links to the author's other published work, social profiles, or professional pages.
- Formal qualifications, certifications, or job titles where relevant.
- Content reviewed or contributed to by recognized experts in the field.
- Consistent publication of high-quality content within a specific topic area.
If your pages do not include author bios with meaningful credential information, this is one of the fastest EEAT improvements you can make.
Authoritativeness: External recognition and citations
Authoritativeness is not something you claim for yourself. It is earned through external recognition. The most reliable signal is that other trusted sources reference, link to, or cite your content.
This is where traditional link building intersects with EEAT. But it goes beyond links. Signals of authoritativeness include:
- Backlinks from established, relevant websites in your industry.
- Citations in news articles, academic papers, or industry reports.
- Mentions in earned media (press coverage, podcast appearances, expert quotes).
- Brand mentions, even without a hyperlink, from reputable sources.
- Reviews and recognition from independent third-party platforms.
For AI search visibility specifically, earned media coverage is particularly valuable. AI systems like ChatGPT and Perplexity learn from large corpora of text that include news articles, blog posts, and web content. Brands that appear frequently in credible third-party sources are more likely to be recognized as authoritative by these systems.
Our script can flag when a page lacks indicators of external authority and suggest specific directions for building recognition, such as pursuing relevant backlinks or pitching expert commentary to industry publications.
Trustworthiness: Verifiable signals of credibility
Trustworthiness is the most foundational of the four components. Google's guidelines describe it as the most important element of EEAT. A page can demonstrate experience, expertise, and authority, but if basic trust signals are missing, everything else is undermined.
Trustworthiness is built from concrete, verifiable details that users and algorithms can check. Key signals include:
- HTTPS: a secure connection is the baseline expectation. Pages served over HTTP signal a lack of attention to basic security.
- Clear authorship: every piece of content should have a named, real author. Anonymous content is difficult to assess for expertise or accountability.
- Contact information: a visible email address, phone number, or contact form reassures users that there is a real organization behind the content.
- Transparent policies: privacy policy, terms of service, and editorial guidelines (where appropriate) demonstrate that the site operates responsibly.
- Accurate, up-to-date information: outdated or factually incorrect content is a major trust signal failure.
- Citations and references: linking to primary sources supports the claims made in the content and shows intellectual honesty.
Schema markup and structured data: Making EEAT machine-readable
One of the most underused EEAT tools is structured data. Schema markup communicates key authority signals directly to search engines and AI systems in a format they can parse reliably. Research suggests that pages with relevant schema markup have a significantly higher chance of being included in AI Overviews compared to equivalent pages without it.
The most relevant schema types for EEAT include:
- Author schema: links the content to a named author entity with a verifiable identity, credentials, and published works.
- Organization schema: confirms the publisher's name, contact details, logo, and social profiles.
- Article schema: marks up the publication date, modification date, and authorship of editorial content.
- Person schema: establishes an individual as a recognized entity with a professional identity.
- Review and rating schema: supports trust signals for product and service pages.
Adding these schema types does not guarantee inclusion in AI-generated answers, but it removes ambiguity. When an AI system can clearly identify who wrote the content, who published it, and what organization stands behind it, it is far more likely to treat the page as a credible source.
Entity optimization: Helping Google and AI recognize your brand
Beyond individual pages, EEAT operates at the entity level. Google and large language models recognize brands, authors, and organizations as entities in a knowledge graph. The more clearly defined and consistently referenced your entity is across the web, the stronger your baseline authority becomes.
Entity-level signals that support EEAT include:
- A Google Knowledge Panel or Wikidata entry for your brand or key authors.
- Consistent name, address, and contact information across all platforms.
- Active profiles on authoritative platforms (LinkedIn, Crunchbase, industry directories).
- Awards, recognitions, or contributions cited by credible external sources.
- Social media presence that reinforces brand identity and topical focus.
When our script evaluates a URL, it identifies gaps in entity-level signals and flags opportunities to strengthen how your brand or authors are recognized across the web.
A practical EEAT checklist for any URL
Use this checklist to manually evaluate any page before or after running the script. It covers the most critical signals across all four EEAT components.
Experience
- Does the content include first-hand accounts, real examples, or original data?
- Does the author demonstrate direct involvement with the subject matter?
- Are there specific details (measurements, timelines, personal outcomes) that indicate real experience?
Expertise
- Is there a named author with a detailed, credible bio?
- Are the author's qualifications or professional background clearly stated?
- Does the content cover the topic with appropriate depth and accuracy?
- For YMYL topics, is the content written or reviewed by a qualified professional?
Authoritativeness
- Does the page or domain have backlinks from relevant, reputable sources?
- Has the author or brand been mentioned or cited in third-party publications?
- Are there any industry awards, accreditations, or recognitions associated with the brand?
- Is the content cited or referenced by other credible sites?
Trustworthiness
- Is the page served over HTTPS?
- Is there a visible, real author name on the page?
- Does the site have clear contact information?
- Are there accessible privacy and editorial policies?
- Is the content accurate, current, and supported by credible references?
- Is the relevant schema markup implemented (Author, Organization, Article)?
How the Google Colab script works
Evaluating all of these signals manually for every URL is time-consuming. That is exactly why this script exists. Using Google Colab and AI, the script automates the assessment process and delivers structured, actionable output for any URL you provide.
Here is what the script does:
- Fetches and parses the content of the target URL.
- Analyzes the page for EEAT signals across all four components.
- Assigns a final score based on the strength of those signals.
- Provides a written explanation of the score, identifying what is working and what is missing.
- Returns specific, prioritized suggestions for improving the page's EEAT profile.
You can run it on a single URL or batch-process multiple URLs at once, which makes it practical for auditing entire sections of a site.
A few notes before you start:
- EEAT stands for Experience, Expertise, Authoritativeness, and Trustworthiness. These are the core quality signals used by Google's quality raters and, increasingly, by AI search systems.
- Google Colab is a cloud-based environment for running Python code. No local installation is required.
- Basic familiarity with Python and web scraping concepts will help you get the most from the script, though the setup is straightforward.
Why assessing EEAT is more important than it used to be
Ensuring that your content meets Google's quality standards has always been good practice. But the reasons to prioritize EEAT have multiplied. Traditional organic rankings reward strong EEAT, but so do AI Overviews, and so do the citation decisions made by ChatGPT and Perplexity when answering user queries.
A page that scores poorly on EEAT is not just less likely to rank well. It is likely to be invisible in AI-generated search results entirely. As more users rely on AI summaries to answer their questions, that exclusion becomes increasingly costly.
Using this script regularly, combined with the checklist above and targeted improvements to your schema markup, author bios, and external authority signals, gives you a systematic way to stay competitive across both traditional and AI-powered search.