Helpful content & E-E-A-T
E-E-A-T for Content Teams: What Google Actually Expects and What You Can Control
What E-E-A-T actually means in Google's own documentation, which myths to drop, and what content teams can control: a page checklist, a YMYL decision table, a worked example and an audit order.
16 min readUpdated
Updated November 14, 2026: Rechecked against Google's current guidance and the September 2025 rater guidelines, with a myth-vs-docs table, a YMYL decision table, a page checklist and a worked example.
This guide answers one question for content and SEO leads: what does Google actually mean by E-E-A-T, and which parts of it can your team change on the page and across the site? It sticks to what Google documents in its own guidance and in the Search Quality Rater Guidelines, separates that from industry folklore, and gives you a page-level checklist, a YMYL decision table, a worked example and an audit order you can run on a whole library.
The short version: E-E-A-T is not a score and not a switch. Google says it is not a specific ranking factor, but its systems look for a mix of signals that line up with it, and they weigh those signals more heavily on topics where bad information can hurt people. Trust matters most. Most of what you control comes down to three things: who wrote and reviewed the page, how well its claims are supported, and how honestly the site presents itself. For Google's wider helpful-content questions turned into a scoring rubric, start with Google's helpful content guidance: a working rubric.
What E-E-A-T is, in Google's own words
E-E-A-T stands for Experience, Expertise, Authoritativeness and Trustworthiness. It comes from the Search Quality Rater Guidelines, the handbook Google gives the people who rate search results. It was E-A-T until 15 December 2022, when Google added Experience: first-hand involvement, such as having used the product or visited the place.
Three statements from Google set the frame for everything else on this page:
- It is not a specific ranking factor. Google's helpful content guidance says E-E-A-T itself isn't a specific ranking factor, but that its systems use a mix of factors that can identify content with good E-E-A-T, and give more weight to it on topics that affect health, finances, safety or society.
- Raters do not rank pages.The same page says search raters have no control over how pages rank and that rater data is not used directly in ranking algorithms. The rater guidelines themselves say no single rating can directly change how a page appears. Ratings are used to check whether Google's systems are working.
- Trust is the most important part.Both the helpful content guidance and the rater guidelines put trust at the centre: an untrustworthy page has low E-E-A-T however experienced, expert or authoritative it looks. The rater guidelines' example is a financial scam run by a very skilled scammer.
So the useful question is not "how do we optimise for E-E-A-T?" but "would a careful reader, checking who we are and what we claim, trust this page?" The rest of this guide turns that question into checks.
E-E-A-T myths, checked against Google's docs
A lot of E-E-A-T advice is repeated rather than sourced. Here is what Google's own documentation says about the most common claims.
| Common claim | What Google documents |
|---|---|
| "E-E-A-T is a ranking factor with a score." | Not a specific ranking factor. Systems use a mix of signals that align with it (helpful content guidance). |
| "Quality raters can demote my pages." | Raters have no control over rankings; their data is not used directly in ranking algorithms. |
| "Author schema boosts E-E-A-T." | Google recommends accurate bylines where readers expect them. Article structured data has no required properties, helps Google tell authors apart, and comes with no guarantee of any search feature. Google does not link it to E-E-A-T. |
| "AI-written content is penalised." | AI content must meet the same standards. Generating many pages without adding value can break the scaled content abuse policy. The rater guidelines say using generative AI does not by itself decide a page's effort or quality rating. |
| "Longer content shows more expertise." | Google says it has no preferred word count and lists writing to a word count as a sign of search-engine-first content. |
| "Update the date to look fresh." | Google lists changing dates without substantially changing the content as a search-engine-first practice. Dates should describe when the page was published or updated. |
Why it carries more weight now
Two documented changes explain why E-E-A-T comes up in every content review.
Helpfulness is part of core ranking.The helpful content system Google announced in 2022 was designed to reward original content written for people. According to Google's ranking systems guide, in March 2024 it became part of the core ranking systems. There is no separate update to wait out: the same questions about people-first content now apply all the time.
New spam policies target cheap scale. Also in March 2024, Google added three spam policies: scaled content abuse (many pages made mainly to manipulate rankings, however they were produced), site reputation abuse (third-party content riding on a host site's ranking signals) and expired domain abuse. All three describe ways of borrowing trust you have not earned, which is exactly what E-E-A-T is meant to see through.
The four parts, and what each asks of a content team
The rater guidelines tell raters to judge E-E-A-T from three places: what the site or creator says about themselves (About pages, author profiles), what independent sources say about them (reviews, news, references), and what is visible on the page itself. Keep those three in mind; they are also the three places your team can work.
Trust: the one that decides the rest
Trust asks whether a reader can rely on this page, this site and this creator. Accurate claims, clear sourcing, honest disclosures, a real organisation behind the site and a way to reach it all feed into it. The rater guidelines also flag conflicts of interest: a review by someone who owns and uses a product can be very trustworthy, while a manufacturer's "review" of its own product, or a paid influencer's, is not. For a content team, that means disclosing affiliate links, sponsorships and the fact that you sell the product you are comparing.
Experience: first-hand involvement
Experience asks whether the creator has actually done the thing: used the product, run the process, been through the situation. It shows up as specific detail a summary could not produce, such as the setting that caused the problem, the number from your own test, or the photo you took. Assign pieces to the person with the experience and let an editor make it readable, rather than the other way round.
Expertise: knowledge and skill
Expertise asks whether the creator knows the subject well enough to be relied on. It can be formal (a licensed accountant) or practical (an engineer who has run the system for years). Raters judge it from the content as much as the credentials: correct terminology, handled edge cases, and analysis beyond the obvious. A credential on a shallow page does not rescue it.
Authoritativeness: being a go-to source
Authoritativeness asks whether the site or creator is a recognised source on this topic. It is the slowest part to build because it lives largely in what others say about you: citations, coverage, reviews and references. You influence it indirectly by publishing work others want to cite, such as original data, tools and clear explanations, and by staying in the topics where you have real standing.
How the four parts relate
Trust
The deciding factor. An untrustworthy page has low E-E-A-T whatever else it shows.
Experience
First-hand involvement, visible as specific detail only a participant would know.
Expertise
Knowledge and skill, visible in the accuracy and depth of the content itself.
Authoritativeness
Recognition by others as a go-to source on this topic. Built slowly.
YMYL: decide how much proof a page needs
"Your Money or Your Life" (YMYL) topics are the ones where the rater guidelines ask for the most scrutiny. The September 2025 edition defines them by the kind of harm they could do:
- Health or safety: mental, physical or emotional health, and any form of safety, including online safety.
- Financial security:a person's ability to support themselves and their family.
- Government, civics and society: public institutions, issues of public interest, election and voting information.
- Other: anything else that could hurt people or the welfare of society.
The guidelines treat this as a spectrum: clear YMYL, definitely not YMYL, and a lot in between. They also say most topics are not YMYL. A page on choosing project management software is not; a page on payroll tax deadlines is.
Experience or expertise? A decision table
On a YMYL topic, the guidelines draw a useful line. Pages that share first-hand life experience can still rate highly if they are trustworthy, safe and consistent with expert consensus. Pages that give information or advice often need real expertise. The table below applies that line to the kind of topics business content teams publish. The examples are ours, written to illustrate the guidelines' distinction.
| Topic (YMYL type) | Experience is enough | Needs an expert author or reviewer |
|---|---|---|
| Payroll (financial security) | What changed for our finance team when we moved payroll provider | Payroll tax filing deadlines and late-filing penalties |
| Workplace safety (health or safety) | How we run a monthly warehouse safety walk | Legal training requirements for forklift operators |
| Customer data (online safety) | Handling our first data subject access request | When a company is required to appoint a data protection officer |
| Pensions (financial security) | Reviews of pension apps from people who use them | How much to contribute and which funds to choose |
Rule of thumb: if a reader could act on the page in a way that costs them money, health, safety or legal standing, name a qualified author or reviewer and cite the primary source. If the page is a story about what happened to you, say so clearly and keep it consistent with expert guidance. Spend your expert review budget on the first group; applying it everywhere wastes it.
What your team controls: a page-level checklist
You cannot see or set Google's assessment. You can control what a reader, and a rater, finds when they look. Each row below is grounded in Google's own guidance; the "who, how and why" questions come from the helpful content page.
| Check | A pass looks like |
|---|---|
| Who wrote it | A byline where readers expect one, linking to a page about the author and why they know this topic. Google strongly encourages accurate authorship information and warns that any deception makes a page untrustworthy. |
| Who checked it | On YMYL pages, a named reviewer with relevant credentials and the date of the review. |
| Where the facts come from | Specific claims link to the primary source (the regulator, the study, the official documentation), not to another blog post. |
| What is first-hand | At least one thing the reader cannot get elsewhere: your data, your test, your worked example, your screenshots. |
| How it was made | Where readers would reasonably wonder, a short note on how the content was produced, including AI or automation. Google calls such disclosures useful in that situation. |
| When it was updated | A visible, labelled date ("Published", "Last updated") that changes only when the content substantially changes. |
| Conflicts of interest | Affiliate links, sponsorships and "we sell this" are disclosed where the claim is made. |
| Why it exists | The page was made to help a reader with a task, not mainly to attract search visits. Google calls "why" perhaps the most important question. |
If you use Article structured data, follow Google's author markup best practices: include every author shown on the page, put only the name in author.name, and use url or sameAs to point to a page that identifies the author. It helps Google tell authors apart; it does not stand in for the visible byline. See schema markup opportunities for finding pages that are missing it.
Site-level trust
The rater guidelines spend a full section on finding who is responsible for a website and how to contact it. A reader should be able to find, in a click or two:
- An About page that says who runs the site and why
- Contact details appropriate to the site (an online shop needs customer service details)
- An editorial or review policy, if you publish advice
- Author pages for everyone with a byline
- Clear disclosure of how the site makes money from the content
Quality across the library matters too. One excellent guide does not offset hundreds of thin pages on the same site. Finding and fixing thin content is site-level trust work, and our guide on when to merge, prune or leave pages covers the decisions that follow.
Worked example: one page, start to finish
An illustrative example, not a client case. A company that sells HR software has a guide called "How to calculate holiday pay". It gets steady search traffic. Running the checklist:
- Classify. Holiday pay affects what people are paid, so the page sits on the financial-security side of YMYL. It gives advice, so it needs expertise, not just experience.
- Who wrote it.The byline reads "Marketing Team". Fix: a named payroll specialist as reviewer, with a short profile stating their qualification and how long they have run payroll.
- Sources.The page quotes a minimum holiday entitlement with no source, and the figure is from an earlier tax year. Fix: link the government guidance for each market the page covers and add a "last checked" line under the figures.
- First-hand value. The page restates the rules in general terms, like the top results. Fix: add a worked calculation for a typical salary and the edge cases the reviewer sees most, such as irregular hours and leavers.
- Disclosure.The page recommends the company's own product for the calculation. Fix: say plainly that it is your product and give the manual method first.
- Date.Change the visible "Last updated" date once, after the substantive changes above, not before.
None of these steps is a trick. Each one makes the page more useful and easier to verify, which is the point.
What changes by content type
Not every page carries trust the same way. Put your effort where the page type needs it.
| Page type | What carries trust | Fix first |
|---|---|---|
| Guides and editorial | Named author with relevant experience, sources, original examples | Anonymous bylines on advice pages |
| Product and service pages | Accurate claims, clear pricing and policies, genuine reviews | Claims you cannot back up, and outdated facts |
| Comparison pages | Disclosed relationship to the products, a stated method | Undisclosed "we sell one of these" |
| Help and docs | Accuracy against the current product | Steps and screenshots for features that changed |
| Landing pages | Specific, verifiable claims and real social proof | Superlatives with no evidence |
A structured E-E-A-T assessment across product and landing pages usually finds the unsupported claims quickly, because they repeat across templates.
Auditing a whole library
On a few dozen pages you can run the checklist by hand. On thousands, you need an order of work.
E-E-A-T audit process
Inventory and classify
List every page with its type, topic and YMYL position. Add clicks from Search Console.
Score the pages
Rate each page on trust, expertise and first-hand value, so weak pages are comparable.
Check site-level signals
About, contact, author pages, editorial policy and disclosures. These are checked once, by hand.
Prioritise
YMYL pages with weak trust first, then high-traffic pages with weak expertise or effort.
Fix and re-check
Assign owners, fix, and re-score after the page is updated.
A priority rule of thumb: sort by YMYL first, then by clicks. A clear-YMYL page with an anonymous byline and stale figures outranks a high-traffic opinion piece with the same gaps, because the cost of being wrong is higher. Start from a content inventory, and see how to audit website content at scale for the full audit method.
Where Morrison helps
Morrison's content analyzerscores every page in the site index against Google's helpful-content guidance on eight dimensions: originality, effort, helpfulness, skill, accuracy, trust, people-first and spam, each from Weak to Excellent. Several map directly onto E-E-A-T (skill to expertise, trust to trust, originality and effort to first-hand value), which makes the "score the pages" step a sort rather than a reading marathon. With Search Console connected, the URL grid export puts clicks beside the scores, so you can sort it for weak pages that still get clicks, and chat can check the scans of your most-clicked pages. Chat can also score a competitor's page with the same analyzer, so you can see where a ranking rival shows more trust or effort.
Two limits are worth knowing. Morrison reads each page's main content, not navigation, footers or sidebars, so site-level signals such as About and contact links, and bylines that sit in a page template, still need a manual check. And chat ranks pages by the overall score, not by one dimension such as Trust: to rank a whole section by one dimension, export the URL grid and sort it there.
Search ConsoleAI-assisted content and E-E-A-T
Google's guidance on generative AI content is plain: AI content must meet the same standards as anything else, generating many pages without adding value can break the scaled content abuse policy, and AI output should be fact-checked by a person before it is published. The rater guidelines add that using generative AI does not in itself decide how much effort or quality a page shows.
The practical gap is experience. A model can organise and phrase what is already known. It cannot supply your test results, your client situation or your professional judgement. That is why AI drafts tend to land in the middle: fluent, and missing exactly what the originality and experience questions look for. A workable split:
- Use AI for: outlines, gap-finding against the results, consistency and readability checks, and flagging pages with missing sources or stale facts.
- Keep with people: the first-hand material, the expert review on YMYL pages, the final fact-check, and any claim the company will be held to.
- Disclose when it matters:Google calls AI or automation disclosures useful where readers might reasonably wonder how the content was made. A one-line "how we made this" note is enough.
Our guide on AI for content operations goes further into where AI helps a content team and where it does not.
Regulated industries
In health, finance and law, E-E-A-T overlaps with obligations that go well beyond search. The editorial rules are the same; the review gates are stricter.
- Health: anything on diagnosis, treatment or medication needs a qualified clinician as author or reviewer, cited clinical sources, and a review cycle tied to guideline changes. See healthcare content review.
- Finance: investment, tax and lending content needs a qualified reviewer, the disclosures your regulator requires, and a re-check whenever rules or rates change. See financial content audit.
- Legal:state the jurisdiction, avoid "you can" where the honest answer is "it depends", and route advice through a lawyer.
In all three, run editorial quality and compliance and accuracy scanning as one process with one owner, not two parallel tracks.
Common mistakes
Inventing expertise
Made-up expert contributors, inflated credentials or AI-generated author personas are the most damaging mistake, because Google says any form of deception makes a page untrustworthy. Name the people who actually wrote and reviewed the content, with their real qualifications.
Credentials that don't match the topic
A marketing director reviewing clinical nutrition advice does not add expertise. Match reviewers to topics, and leave the review line off rather than use the wrong person.
Treating it as a checklist of decorations
Author boxes, trust badges and an About page do not fix a page that is generic, unsourced or out of date. The surface signals only help when they describe what is really underneath.
Fake freshness
Bumping the "Last updated" date on unchanged pages is something Google names as search-engine-first behaviour. Update the date when the content changes, and only then.
Running it as a programme
E-E-A-T decays like everything else: authors leave, sources go stale, rules change. Four habits keep it from sliding.
- Commission for experience.Assign pieces to the people who have done the work and give them editorial support, rather than giving experts' topics to generalist writers.
- Gate YMYL content. Make expert review a required step for clear-YMYL pages, with the reviewer named on the page.
- Set update triggers. Regulation changes, product releases, elapsed time on pages with figures, and falling clicks should each put a page back in the review queue. See content freshness monitoring and the content refresh playbook.
- Track a few internal measures. These are your own health checks, not things Google measures: the share of advice pages with a named author, the share of YMYL pages with a named reviewer, the share of pages with figures checked in the last 12 months, and the number of pages scoring weak on trust.
These habits belong inside your wider governance model. The complete guide to content governance covers owners, standards and review cadences. In Morrison, a weekly or monthly automation can check the pages you care about most and email the ones that need attention, so the review queue fills itself.
The short version
- E-E-A-T is not a specific ranking factor, and raters do not rank pages. Trust matters most.
- Decide how much proof a page needs from where it sits on the YMYL spectrum.
- On advice pages, name a qualified author or reviewer and link primary sources.
- Give every page something first-hand that the top results do not have.
- Be open about who made the page, how, and any commercial interest.
- Change dates only when content changes, and keep the library under review.
Sources and further reading
- 1Creating Helpful, Reliable, People-First ContentGoogle Search Central
- 2Search Quality Rater Guidelines (General Guidelines, September 11, 2025)Google
- 3Our latest update to the quality rater guidelines: E-A-T gets an extra E for ExperienceGoogle Search Central Blog
- 4A guide to Google Search ranking systemsGoogle Search Central
- 5Spam policies for Google web searchGoogle Search Central
- 6Google Search's guidance on using generative AI content on your websiteGoogle Search Central
- 7Article structured data: author markup best practicesGoogle Search Central
- 8Help Google Search know the best date for your web pageGoogle Search Central
CEO, Morrison
Ulrich is CEO of Morrison and founded Bonzer in 2017, growing it into one of Scandinavia's leading SEO agencies with 900+ clients across Copenhagen, Oslo, and Stockholm. At Morrison he leads strategy, operations and go-to-market, bringing years of hands-on SEO and content work to the platform side of the business.