Category: AEO

The main types of schema markup are Organization, LocalBusiness, Person, WebPage, Breadcrumb, Article, Video, FAQ, HowTo, Recipe, Product, Review, AggregateRating, Event, JobPosting, Course, and Dataset. Schema.org defines 826 types in total, but these 25 cover nearly every website. Each one labels a specific kind of content so search engines know exactly what they’re looking at.

So why do so many sites still get schema wrong? Most lists online haven’t kept up with Google’s changes.

That means people keep adding FAQ and HowTo markup expecting rich results that Google no longer shows. Meanwhile, useful types like ProfilePage or Dataset get skipped entirely.

This guide walks through 25 types of schema markup one by one. For each, you’ll see what it does, where it belongs, the key properties, and its 2026 status in Google.

Key takeaways

• Schema.org has 826 types, but 25 common schema types cover almost every website’s needs.
• Most sites only need five to eight types, starting with Organization, WebSite, and Breadcrumb.
• Google stopped showing HowTo rich results in 2023 and FAQ rich results in May 2026, though both are still valid code.
• Some types, like Person, WebPage, and Service, never earn a rich result but still help search engines understand entities.
• Product, Review, and AggregateRating work together to show prices and stars in search.
• No schema type is required for AI Overviews, but clear entity markup supports how search engines describe your brand.

How many types of schema markup are there?

It depends on which list you’re reading. Three numbers explain the whole picture.

Number	What it counts	Source
826	Every type in the schema.org vocabulary (version 30.1, September 2026)	schema.org full hierarchy
25	Rich result features Google currently documents	Google search gallery
5 to 8	Types a typical business site actually uses	Practical rule of thumb

Every schema.org type sits inside one family tree. It starts with Thing, then branches into groups like CreativeWork, Organization, Person, Place, Product, and Event.

That tree matters.

A Bakery is a FoodEstablishment, which is a LocalBusiness, which is an Organization, so picking the most specific type gives you every property above it.

Quick reference: all 25 schema types and their 2026 status

Short on time? Scan this table first, then jump to the types of schema markup you need.

#	Schema type	Best for	Google rich result in 2026
1	Organization	Brand homepage, about page	Yes, logo and company details
2	Local business	Shops, clinics, restaurants	Yes
3	Person	Authors, founders, team members	No standalone result
4	Web page	Any page	No standalone result
5	WebSite	Homepage	Yes, site names
6	Breadcrumb	Inner pages	Yes
7	Article	Blog posts, news	Yes
8	Video	Pages with video	Yes
9	FAQ	FAQ sections	Retired May 2026
10	How to	Step-by-step guides	Retired September 2023
11	Recipe	Food and cooking pages	Yes
12	Book	Publishers, bookstores	Limited (Book actions)
13	Profile page	Author and creator pages	Yes
14	Discussion forum	Forums, community threads	Yes
15	Q&A	Single-question pages with answers	Yes
16	Image metadata	Photos and licensed images	Yes
17	Product	Product pages	Yes
18	Product review	Reviewed products	Yes, review snippets
19	Aggregate rating	Average star ratings	Yes, inside review snippets
20	Software	Apps and SaaS products	Yes
21	Service	Service pages	No standalone result
22	Event	Concerts, webinars, classes	Yes
23	Job posting	Careers pages	Yes
24	Course	Course catalogs	Yes, course lists (course info retired)
25	Dataset	Research and open data	Yes, in Dataset Search

Site and entity schema types

These types describe who you are and how your site is organized. Most websites need several of them.

1. Organization schema

Organization schema describes your company as a whole. It’s the anchor that every other type on your site can point back to.

• Use it on: your homepage or about page.
• Key properties: name, url, logo, contactPoint, sameAs.
• Google status: supported, and it can help Google show your logo and company details.

The sameAs property is worth extra attention. It links your brand to official profiles like LinkedIn, which strengthens your entity.

2. Local business schema

LocalBusiness is a more specific kind of Organization for places customers can visit. It has hundreds of subtypes, such as Dentist, Restaurant, and Store.

• Use it on: each location page, one block per location.
• Key properties: address, geo, openingHoursSpecification, telephone, priceRange.
• Google status: supported for local business details.

Organization or LocalBusiness? Use Organization for the brand, and LocalBusiness for each physical branch. Link each branch back to its parent brand.

3. Person schema

Person schema describes an individual, usually an author, founder, or expert. It ties a name to real credentials and profiles.

• Use it on: author pages, team pages, and inside Article markup.
• Key properties: name, jobTitle, worksFor, sameAs, image.
• Google status: no rich result of its own, but it feeds author details and Profile page markup.

Person markup supports trust. A clearly identified author with real credentials beats an anonymous byline.

4. Web page schema

WebPage schema describes the page itself rather than its main subject. It acts as a hub that connects the article, the site, and the breadcrumb trail.

• Use it on: any page, often added automatically by SEO plugins.
• Key properties: name, url, isPartOf, breadcrumb, datePublished.
• Google status: no rich result, but useful for connecting entities with @id.

Subtypes like AboutPage, ContactPage, and FAQPage tell search engines what kind of page it is.

5. WebSite schema

WebSite schema describes your whole site. Google uses it to choose the site name shown above your search results.

• Use it on: your homepage only.
• Key properties: name, alternateName, url.
• Google status: supported for site names.

It’s also the most common type online. The HTTP Archive Web Almanac 2024 found WebSite JSON-LD on 12.73% of mobile pages, ahead of Organization at 7.16%.

6. Breadcrumb schema

BreadcrumbList shows the path from your homepage to the current page. Google can display that trail in place of a raw URL.

• Use it on: almost every inner page.
• Key properties: itemListElement, with position, name, and item for each step.
• Google status: supported.

Breadcrumbs pair nicely with good internal linking, since both show how your pages connect.

Content schema types

These types describe what a page says or shows. Publishers, bloggers, and media sites rely on them most.

7. Article schema

Article schema tells search engines a page is a written piece, with a headline, an author, and dates. Use BlogPosting for blogs and NewsArticle for news.

• Use it on: blog posts, news stories, and guides.
• Key properties: headline, image, author, datePublished, dateModified, publisher.
• Google status: supported.

Article markup works best when the piece is already well organized. It’s worth learning how to structure a blog post before tagging it.

8. Video schema

VideoObject schema helps Google show your video’s thumbnail, length, and upload date. Longer videos can also get key moments.

• Use it on: any page where a video is the main content.
• Key properties: name, description, thumbnailUrl, uploadDate, duration, contentUrl.
• Google status: supported.

9. FAQ schema

FAQPage schema marks up a list of questions and answers. For years it produced expandable questions under your listing.

• Use it on: pages with a real FAQ section written by you.
• Key properties: mainEntity, with Question and acceptedAnswer pairs.
• Google status: retired. FAQ rich results stopped showing for all sites in May 2026.

Should you still use it? The code stays valid, so it won’t hurt. The visible FAQ section still helps readers and answer engines, so keep the content either way.

10. How to schema

HowTo schema describes step-by-step instructions, with tools, supplies, and time needed for each step.

• Use it on: tutorials and step-by-step guides.
• Key properties: name, step (HowToStep), totalTime, tool, supply.
• Google status: retired. HowTo rich results stopped showing on desktop and mobile in September 2023.

Clear numbered steps in plain HTML still work well. Readers and AI tools can follow them, markup or not.

11. Recipe schema

Recipe schema is one of the oldest and most visual types. It can show cook time, ratings, and calories right in search.

• Use it on: individual recipe pages.
• Key properties: name, image, recipeIngredient, recipeInstructions, cookTime, nutrition.
• Google status: supported, including recipe carousels.

12. Book schema

Book schema describes a book’s title, author, and editions. Google also supports Book actions, which let people borrow or buy a book from search.

• Use it on: book pages from publishers, bookstores, and libraries.
• Key properties: name, author, isbn, bookFormat, workExample.
• Google status: limited. Google planned to retire Book actions in 2025, then reversed that in November 2025.

13. Profile page schema

ProfilePage schema marks a page that’s mainly about one person or organization. It’s a strong signal for creator and author pages.

• Use it on: author bios, creator profiles, and user profile pages.
• Key properties: mainEntity (a Person or Organization), dateCreated, dateModified.
• Google status: supported.

14. Discussion forum schema

DiscussionForumPosting describes threads and posts on forums and community sites. It helps Google surface real conversations.

• Use it on: forum threads, community posts, and comment-led pages.
• Key properties: headline, author, datePublished, text, comment.
• Google status: supported.

15. Q&A schema

QAPage schema marks a page built around one question with answers from users. Think support communities, not your own FAQ list.

• Use it on: pages where users submit answers to a single question.
• Key properties: mainEntity (Question), acceptedAnswer, suggestedAnswer, answerCount.
• Google status: supported.

Not sure whether you need Q&A or FAQ? If you wrote all the answers, it’s FAQ. If users answer, it’s Q&A.

16. Image metadata schema

ImageObject markup tells Google who created an image and how it can be licensed. That can add a “Licensable” badge in Google Images.

• Use it on: photography sites, stock libraries, and original image pages.
• Key properties: contentUrl, license, acquireLicensePage, creator, creditText.
• Google status: supported.

Product, review, and service schema types

These types matter most for stores, SaaS brands, and service businesses. Price, stock, and stars in a listing can tip a buyer’s choice before they click.

17. Product schema

Product schema describes an item you sell. Combined with an Offer, it can show price and availability in search and in Google Shopping.

• Use it on: individual product pages, not category pages.
• Key properties: name, image, description, SKU, brand, offers (price, priceCurrency, availability).
• Google status: supported for product snippets and merchant listings, including shipping and return details.

The payoff can be real. In Google’s structured data case studies, Rotten Tomatoes saw a 25% higher click-through rate on pages with structured data.

18. Product review schema

Review schema marks up a single review of a product, with the reviewer and their rating. Editorial review sites use it heavily.

• Use it on: product review articles and individual customer reviews.
• Key properties: itemReviewed, author, reviewRating, reviewBody.
• Google status: supported as review snippets.

One rule to remember: reviews a business writes about itself aren’t eligible for stars. Keep it to genuine, independent reviews.

19. Aggregate rating schema

AggregateRating summarizes many reviews into one average score and count. It’s what produces the “4.7 stars from 128 reviews” line.

• Use it on: products, recipes, software, and other items with real ratings.
• Key properties: ratingValue, reviewCount or ratingCount, bestRating.
• Google status: supported inside review snippets.

AggregateRating never stands alone. Nest it inside the Product, Recipe, or SoftwareApplication it describes.

20. Software schema

SoftwareApplication schema describes apps, games, and SaaS tools. It can show ratings and price in search.

• Use it on: app landing pages and software product pages.
• Key properties: name, operatingSystem, applicationCategory, offers, aggregateRating.
• Google status: supported.

SaaS brands often overlook this one. It’s a natural fit for pricing and product pages.

21. Service schema

Service schema describes something you do rather than something you sell in a box. Think SEO audits, plumbing, or legal advice.

• Use it on: individual service pages.
• Key properties: serviceType, provider, areaServed, offers.
• Google status: no rich result, but it clarifies what your business offers.

Agencies and consultants get the most from it. Pair each Service with your Organization or LocalBusiness as the provider.

Event, job, and education schema types

These types fit content tied to a date, a role, or a learning goal. Each has its own dedicated Google experience.

22. Event schema

Event schema describes something happening at a set time, online or in person. It can surface in Google’s event listings.

• Use it on: event pages for concerts, webinars, workshops, and classes.
• Key properties: name, startDate, endDate, location, eventStatus, eventAttendanceMode, offers.
• Google status: supported.

Update eventStatus if plans change. Google can then show an event as postponed or cancelled.

23. Job posting schema

JobPosting schema puts open roles into Google’s job search experience. It’s one of the most valuable types for hiring.

• Use it on: each individual job listing page.
• Key properties: title, description, datePosted, validThrough, hiringOrganization, jobLocation, baseSalary.
• Google status: supported.

Remove the markup, or set validThrough, once a role is filled. Expired listings frustrate applicants.

24. Course schema

Course schema describes a class or training program. Google now uses it for course lists, which show several courses from one provider.

• Use it on: course catalog and course detail pages.
• Key properties: name, description, provider, hasCourseInstance, offers.
• Google status: supported for course lists. The separate Course info result was retired in 2025.

25. Dataset schema

Dataset schema describes data tables, research files, and open data. It helps your data appear in Google Dataset Search.

• Use it on: pages hosting downloadable or public datasets.
• Key properties: name, description, creator, license, distribution, temporalCoverage.
• Google status: supported in Dataset Search.

It’s a niche type, but a powerful one. Research teams and publishers with original data should never skip it.

Which schema types has Google retired?

Google has spent the last few years trimming features that rarely helped searchers. Every entry below comes from Google’s own Search Central updates log.

When	What changed
May 2026	FAQ rich results stopped showing for all sites
November 2025	Practice problem deprecated; Book actions kept after Google reversed its earlier notice
June 2025	Course info, Claim review (Fact check), Estimated salary, Learning video, and Vehicle listing deprecated
April 2025	Special announcement deprecated
September 2023	HowTo rich results removed on desktop and mobile; FAQ limited to well-known government and health sites

Here’s the key point. Retired features don’t make the code invalid. They simply stop producing a special listing in Google.

Which types of schema markup should your site use?

You don’t need all 25. Use this table as a starting kit for your kind of site.

Site type	Must-have types	Add when relevant
Blog or publisher	Organization, WebSite, Breadcrumb, Article, Person	Video, Profile page, Image metadata
Ecommerce store	Organization, WebSite, Breadcrumb, Product	Product review, Aggregate rating
Local business	Local business, WebSite, Breadcrumb	Service, Event, Product review
SaaS company	Organization, WebSite, Software, Breadcrumb	Article, Video, Person
Agency or consultant	Organization, WebSite, Service, Breadcrumb	Person, Article, Profile page
Events or education	Organization, Event or Course, Breadcrumb	Video, Q&A
Community or forum	Organization, WebSite, Discussion forum	Q&A, Profile page
Research or data	Organization, Dataset, Article	Person, Image metadata

Start with the must-haves on your top pages. Then roll out the extras once the basics validate cleanly.

Schema is only one piece of on-page SEO, so don’t skip titles, headings, and content quality along the way.

Which schema types matter most for AI search?

The short answer: the ones that define your entity. Organization, Person, Product, and LocalBusiness tell search systems exactly who and what you are.

Google is clear that you don’t need any special markup to appear in AI features. Its AI features guidance says there’s “no special schema.org structured data that you need to add.”

Still, consistent entity data helps search engines connect your brand across the web. That supports AI search optimization and the brand mentions behind citation SEO.

The best way to know if it’s paying off? Track your AI visibility before and after you roll out new markup.

How Contentpen supports a schema-ready content strategy

Markup describes your content, but it can’t fix weak content. Contentpen, an AI SEO tool, helps you build pages that each schema type can describe cleanly.

Here’s how it fits into your schema workflow:

• Structure built for extraction. The AI search optimization tool scores content with a real-time GEO score and adds key takeaways and a linked table of contents.
• Clean article basics. SEO scoring checks heading hierarchy, meta details, image alt tags, and named entities, the same fields Article markup relies on.
• Publishing to your CMS. Posts go straight to WordPress, Shopify, Webflow, and more, where your schema plugin adds the JSON-LD.
• Proof it’s working. Website analytics pulls in Search Console data, so you can watch clicks and CTR on pages with new markup.

Managing schema across dozens of client sites? See how Contentpen for agencies handles content at scale.

Fewer schema types, done well, beat a long list

There are 25 schema types worth knowing, but no site needs all of them. Chasing every type wastes time on markup that shows nothing.

Start with the site and entity types, add the ones that match your pages, and treat FAQ and HowTo as optional. Then validate, publish, and check the results in Search Console.

A short, accurate set of types will always outperform a long, messy one.

Frequently asked questions

Schema markup for AI optimization means using structured data to help AI search systems identify your brand, products, and authors without guessing. It won’t get you cited on its own.

Google says no special schema is needed for AI Overviews, and a 1,885-page study found almost no citation lift. However, schema still strengthens the search indexes and entity data that AI answers draw from.

Sounds confusing? You’re not alone.

Half the internet says schema is the secret to AI visibility, and the other half says AI ignores it.

That noise leads teams to spend weeks on markup and then wonder why ChatGPT still doesn’t mention them. Or they skip schema entirely and leave their entity data a mess.

This guide sorts the evidence, explains how AI systems actually treat schema, and gives you a seven-step plan plus a way to test it.

Here’s what we know in 2026.

Key takeaways

• Schema markup supports AI optimization indirectly, mainly by making entities clear to search indexes and knowledge graphs.
• Google states there is no special schema required to appear in AI Overviews or AI Mode.
• A controlled Ahrefs study of 1,885 pages found AI citations barely moved after adding schema.
• LLMs that fetch pages live tend to read JSON-LD as plain text, valid or not.
• Organization, Person, Product, and LocalBusiness, linked with sameAs and @id, matter most.
• Test it yourself with control pages and AI visibility tracking instead of trusting vendor claims.

What is schema markup for AI optimization?

It’s the practice of using schema.org markup to make your content easier for AI-powered search to understand. The goal isn’t a rich result. It’s entity clarity. It’s one small part of generative engine optimization.

When an AI system builds an answer, it needs to know who you are and what you sell. It also needs to know which facts on your page are current.

Schema states those facts in a fixed format. Think of it as the fact sheet stapled to your content. It sits beside the broader work of answer engine optimization, which focuses on answers worth quoting.

How do AI search engines use schema markup?

Here’s where most guides get it wrong. “AI search” isn’t one system, and schema plays a different role in each path.

Pathway	What happens	Does schema help?
Model training	Pages are scraped and cleaned into training text	Rarely, since common pipelines strip scripts, including JSON-LD
Live retrieval	Tools like ChatGPT search or Perplexity fetch a page when answering	Partly, as JSON-LD may be read as plain text, not parsed as schema
Search index and knowledge graph	Google and Bing index pages and build entity graphs that AI features draw from	Yes, this is where structured data is actually used

The third path is why schema still matters. Google’s AI Overviews and Bing Copilot lean on the same indexes that have used structured data for years.

What does the evidence actually say?

Let’s look at the sources, not the hype. This table pulls together the main statements and studies so far.

Source	Finding	How strong is it?
Google, AI features and your website	“There’s also no special schema.org structured data that you need to add” for AI Overviews or AI Mode	Official guidance
Bing, via Search Engine Land	Fabrice Canel said at SMX Munich 2025 that schema helps Microsoft’s LLMs understand content	Paraphrased report, some dispute the context
Ahrefs, 1,885 pages	After adding schema: AI Overviews citations fell 4.6%, AI Mode rose 2.4%, ChatGPT rose 2.2%	Controlled study; only the AI Overview change was significant
Search Engine Land experiment	Only the page with well-built schema appeared in an AI Overview	Three pages, described by its authors as inconclusive
Mark Williams-Cook test, via Search Engine Roundtable	ChatGPT and Perplexity returned an address found only in invalid JSON-LD	Small test, but clear on how live retrieval reads code

So what’s the verdict? Schema isn’t a citation switch. It’s infrastructure that helps the search side of AI understand you.

Does ChatGPT read JSON-LD?

Sometimes, but probably not the way you’d hope. In the Williams-Cook test, ChatGPT pulled a fact from broken JSON-LD, which suggests it read the code as text.

That means it may notice what’s in your markup. It just doesn’t seem to reward valid schema over the visible content on your page.

Do you need special schema for AI Overviews?

No. Google’s guidance says AI Overviews and AI Mode have no extra technical requirements beyond normal Search eligibility.

It does list one structured data best practice: your markup should match the visible text on the page. Accuracy beats volume.

Which schema types matter most for AI search?

Focus on schema types that define who and what you are. These carry the entity facts AI answers repeat most.

Schema type	Why it helps AI search	Key properties
Organization	Confirms your brand name, logo, and official profiles	name, url, logo, sameAs
Person	Ties authors to real credentials and profiles	name, jobTitle, worksFor, sameAs
Product with Offer	States price, availability, and ratings precisely	name, offers, aggregateRating
LocalBusiness	Fixes your address, hours, and service area	address, openingHoursSpecification, geo
Article or BlogPosting	Signals freshness and authorship	datePublished, dateModified, author
BreadcrumbList	Shows how your topics connect	itemListElement

What about FAQPage? Google stopped showing FAQ rich results in May 2026. A clear, visible FAQ section is still worth keeping, though, because AI tools quote well-formed questions and answers.

How to use schema markup for AI optimization in 7 steps

Ready to put this into practice? Follow these steps in order.

1. Audit your current markup: Run key pages through the Rich Results Test and the Schema Markup Validator. Note errors, duplicates, and missing types.
2. Define your core entities: List your brand, key people, products, and locations. Each one should get a single, authoritative page.
3. Mark up each entity once, properly: Add Organization on the homepage, Person on author pages, and Product or LocalBusiness where relevant.
4. Connect entities with @id and sameAs: Give each entity a stable @id and link it to its official profiles. This builds one consistent identity.
5. Match markup to visible content: Every fact in your JSON-LD should appear on the page, with the same price, name, and dates.
6. Keep facts fresh: Update dateModified and prices whenever the page changes, and never fake freshness.
7. Measure before and after: Track the AI prompts you care about for a few weeks before the change and a few weeks after.

This entity-first approach is one of the biggest differences in AI search optimization vs. traditional SEO.

How can you test whether schema helps your AI visibility?

Don’t take anyone’s word for it, ours included. Run a simple test on your own site.

• Pick matched pages: Choose 10 to 20 similar pages and add schema to half of them. Leave the other half as your control group.
• Track the same prompts: Monitor the questions buyers ask in ChatGPT, Perplexity, Gemini, and Google AI Mode.
• Wait, then compare: Give it at least four weeks, then compare citation changes between the two groups.
• Check live retrieval: Put a harmless, unique detail only in your JSON-LD, then ask an AI tool about it.

A structured AI visibility audit gives you the baseline to make this comparison fair.

When does schema matter most for AI?

Not every site gains the same amount. Schema tends to matter more in a few situations:

• New or small brands that search engines don’t know yet.
• Ambiguous names that clash with other companies, products, or people.
• Product catalogs where price and stock change often.
• Local businesses with several locations or service areas.

It matters less for well-known brands that already have a clear knowledge panel. That may be why the Ahrefs study, which tested pages already being cited, saw so little change.

What mistakes hold back schema for AI?

These errors waste effort or, worse, send conflicting signals.

• Treating schema as a shortcut: Markup can’t make thin content quotable.
• Mismatched facts: A price in JSON-LD that differs from the page confuses every system that reads both.
• Fake freshness: Bumping dateModified without real changes erodes trust.
• Inconsistent entity names: Using “Brand Inc.” in one place and “Brand” in another splits your identity.
• Ignoring off-site signals: AI answers lean heavily on mentions elsewhere, which is why share of voice in AI results matters as much as your own code.

How Contentpen helps you measure AI optimization

Schema is only worth the effort if you can see whether it moves anything. Contentpen, an AEO tool built for SEO and AI search, gives you that visibility.

• Track AI mentions across seven engines: The AI visibility tool monitors ChatGPT, Google AI, Copilot, Perplexity, Gemini, Grok, and Claude for the prompts you choose.
• Write content worth citing: The GEO optimization tool scores drafts in real time and flags fixes, so the page under your schema is clear and extractable.
• Compare before and after: Shareable visibility reports and exportable analytics make your control-group test easy to run and report.
• Work from your AI assistant: The new Contentpen MCP server connects Claude, ChatGPT, Cursor, and other MCP-compatible assistants to your workspace.

Contentpen doesn’t generate schema for you. It shows whether your schema and content changes actually change what AI says about your brand.

AI Visibility is included in every plan. Check Contentpen pricing and start tracking your first prompts.

Schema is the label, your content is the reason

Schema markup won’t make AI cite you by itself. The best evidence in 2026 says it’s a supporting layer, not a growth lever.

What it does well is remove doubt. It tells search indexes exactly who you are, what you offer, and how your pages connect.

So mark up your core entities, keep the facts accurate, and spend most of your energy on content worth quoting. Then measure, and let your own data decide.

Frequently asked questions

SEO vs GEO vs AEO comes down to where you want to show up. SEO gets your page ranked in search results. AEO gets your content pulled out as the direct answer, and GEO gets your brand cited inside AI answers from tools like ChatGPT and Gemini.

All three share one foundation: useful, well-structured content that machines can trust. The difference is the surface you win on and how you measure the win.

Yet most marketers are being pitched these as three separate services, each with its own playbook and price tag.

That leaves most teams guessing. Do you rewrite everything for AI? Do you stop building links? Do you hire a “GEO specialist” and hope for the best?

You don’t need three strategies. You need one content system that ranks, answers, and earns citations at the same time.

This guide breaks down what each term means, where they overlap, how to measure them, and a 30-day plan to cover all three.

Let’s start with the basics.

Key takeaways

• SEO wins rankings and clicks, AEO wins the direct answer, and GEO wins citations in AI-generated responses.
• AEO is about being extracted. GEO is about being trusted enough to be one of the few sources an AI blends into its answer.
• GEO does not replace SEO. AI engines still pull from pages that are crawlable, indexed, and authoritative.
• AIO, LLMO, AI SEO, and LLM SEO are mostly new labels for parts of AEO and GEO.
• Each layer needs its own metrics: rankings for SEO, answer ownership for AEO, and citation share for GEO.
• One well-built page can serve all three if it leads with a clear answer, uses clean structure, and backs claims with sources.

What do SEO, AEO, and GEO each optimize for?

Think of them as three questions a search system asks about your content. Should this page rank? Is this the answer? Should I trust and cite this brand?

SEO, or search engine optimization: earning the ranked spot

SEO is the practice of getting your pages to rank in the organic results on Google and Bing. The goal is a click to your site.

It rests on three pillars:

• On-page work: keywords, headings, meta data, and content that matches what the searcher wants.
• Technical SEO: crawlability, speed, indexing, canonicals, and mobile usability.
• Off-page signals: backlinks, brand mentions, and overall authority.

AEO, or answer engine optimization: becoming the answer

AEO is the practice of structuring content so a search system can lift it out as the direct answer. That answer might be a featured snippet, a People also ask box, a voice reply, or a line inside Google AI Overviews.

The focus shifts from the whole page to the single passage. Short, self-contained answers under question-based headings tend to win here.

GEO, or generative engine optimization: becoming the cited source

GEO is the practice of making your brand and content the source that large language models cite when they write an answer. Think ChatGPT, Gemini, Perplexity, Claude, Copilot, and Google’s AI Mode.

The term comes from a 2023 research paper by Aggarwal and colleagues. They found that GEO methods could lift visibility in generative engine responses by up to 40%.

GEO cares about more than your own pages. It weighs how often trusted third parties mention you, how consistently your brand is described, and whether your content carries facts worth quoting.

How do SEO, AEO, and GEO compare side by side?

Let’s line them up. Full forms first, then the details that actually change your workflow.

Factor	SEO	AEO	GEO
Full form	Search engine optimization	Answer engine optimization	Generative engine optimization
Core question	Should this page rank?	Is this the answer?	Should I cite this brand?
Where you win	Organic results on Google and Bing	Featured snippets, PAA, voice assistants, AI Overviews	ChatGPT, Gemini, Perplexity, Claude, Copilot, AI Mode
Query types it serves best	Commercial, transactional, and navigational searches	Quick factual and how-to questions	Complex, comparison, and recommendation prompts
Unit that competes	The whole page	A single passage	Your brand across the web
How the system uses you	Lists your link	Extracts your text	Blends your facts with other sources
Content format that wins	In-depth pages matched to search intent	40 to 60 word answers, lists, steps, tables	Original data, expert quotes, clear definitions, fact-dense sections
Strongest signals	Relevance, backlinks, technical health	Clear answers, heading structure, schema	Authority, third-party mentions, consistent brand info, original data
Where the work happens	Mostly on your site, plus link building	Almost entirely on your site	On your site and across reviews, forums, press, and directories
Key tactics	Keyword research, on-page optimization, technical fixes, link building	Question-based headings, answer-first copy, FAQ and HowTo schema	Digital PR, community presence, sourced stats, entity consistency
Technical must-haves	Crawlable, fast, indexed pages with clean canonicals	Valid structured data and clean HTML	Access for AI crawlers like OAI-SearchBot and PerplexityBot
Control over the output	High: your title and meta show as written	Medium: your words, chosen by the engine	Low: the AI rewrites and blends your content
Typical outcome	A click	Often a zero-click view	A mention or citation, sometimes a click
Speed of results	Slow to build, compounds over time	Can move within weeks on pages that already rank	Slowest, follows authority built over months
Main metric	Rankings and organic traffic	Answer ownership	Citation share and AI visibility
Risk if you ignore it	AI engines have fewer indexed pages of yours to draw from	Competitors become the default answer	AI tools recommend competitors when buyers ask

The big takeaway?

The further right you move in the table, the less you control the final output. That’s why GEO leans so heavily on reputation built outside your own site.

Is GEO the same as AEO?

Not quite, though the line is blurry. Many people now use AEO as an umbrella term for all AI answers, which is where the confusion starts.

The cleanest way to split them is by what the system does with your content:

• AEO is extraction: The engine finds one passage on your page and shows it, often word for word.
• GEO is synthesis: The engine reads many sources, writes its own answer, and cites a few of them.

So AEO is mostly won on the page. GEO is won on the page and off it, through reviews, forum threads, directories, and press that mention you.

Want a concrete AEO vs GEO example? Picture someone asking, “What is a canonical tag?”

• AEO win: your 45-word definition appears as the featured snippet, exactly as you wrote it.
• GEO win: someone asks ChatGPT “best way to fix duplicate content issues,” and the answer cites your guide alongside two others.

Is GEO the same as SEO, or is it replacing it?

No, on both counts. GEO sits on top of SEO rather than replacing it.

The reason is simple. AI engines still need to find your content before they can cite it, and most of them lean on web search indexes to do that. If a page can’t be crawled or doesn’t rank anywhere, its odds of being cited drop sharply.

What changes is the scoring. Traditional SEO rewards relevance and links to a page, while GEO rewards how believable and quotable your brand looks across the whole web.

Where do AIO, LLMO, and AI SEO fit in?

If you’ve searched “SEO vs GEO vs AEO vs AIO” or “vs LLMO,” you’ve seen how fast the labels multiply.

The good news?

Most of them describe the same work from a slightly different angle.

Term	Stands for	What it usually means	Closest to
AIO	AI optimization, or AI Overview optimization	Getting featured in Google AI Overviews, or AI search in general	AEO
LLMO	Large language model optimization	Shaping how LLMs describe and recommend your brand	GEO
AI SEO	AI search engine optimization	SEO practices adapted for AI-driven results	GEO + AEO
LLM SEO	LLM search engine optimization	Same idea as LLMO, framed as an SEO task	GEO
GSO	Generative search optimization	Optimizing for hybrid search like Google AI Mode	GEO
SXO	Search experience optimization	SEO plus UX and conversion on the landing page	SEO

Don’t let the alphabet soup derail your planning. If you cover rankings, extractable answers, and brand authority, you’ve covered every one of these.

Why does the difference matter for your traffic in 2026?

Because clicks are getting harder to earn when an AI summary sits on top of the results. The data so far points in one direction.

• A Pew Research Center study of 900 U.S. adults found users clicked a traditional result on 8% of visits when an AI summary appeared, versus 15% without one.
• In the same study, people clicked a link inside the AI summary itself on only about 1% of visits.
• Gartner predicted back in 2024 that traditional search engine volume would drop 25% by 2026 as people shift to AI chatbots and virtual agents.

What does that mean in practice?

Ranking alone no longer guarantees attention. You also need to be the answer, and the brand the AI names when it skips the click entirely.

What does one page built for all three look like?

This is the part most comparisons skip. You don’t need three versions of a page. You need one page with three layers baked in.

Each part of the page pulls its weight in a different way:

Page element	SEO job	AEO job	GEO job
Answer in the first 100 words	Matches search intent fast	Gives engines a clean passage to lift	Gives LLMs a quotable summary
Question-based H2s and H3s	Targets long-tail queries	Mirrors how people ask	Helps chunk-level retrieval
Comparison tables	Earns rich results	Easy to extract	Structured facts LLMs reuse
Original data and cited stats	Earns backlinks	Adds precision to answers	Makes you citation-worthy
Author bio with real credentials	Supports E-E-A-T	Builds answer trust	Strengthens your brand entity
FAQ and article schema	Eligible for rich results	Clarifies Q&A pairs	Helps machines parse context
Contextual internal links	Spreads authority	Connects related answers	Shows topical depth

One tip that pays off across all three: write each section so it makes sense on its own. AI systems often pull a single chunk, not your whole article.

How do you measure each one?

This is where teams go wrong most often. They judge GEO with SEO metrics, then decide it isn’t working.

Layer	What to track	Where to find it
SEO	Rankings, impressions, organic clicks, conversions	Google Search Console, Ahrefs, your analytics tool
AEO	Featured snippets owned, PAA appearances, AI Overview inclusions	Rank trackers with SERP feature data, manual checks
GEO	Brand mentions and citations in AI answers, sentiment, share of voice against competitors	AI visibility trackers like Contentpen’s AI visibility tool, prompt testing, referral traffic from AI tools

A simple rule helps. Keep a single content plan, give each layer its own scorecard, and begin GEO with an AI visibility audit so you have a baseline.

Which one should your team prioritize first?

Start with SEO if your basics are shaky. Without crawlable, ranking pages, AEO and GEO have very little to work with.

After that, the right mix depends on how your buyers search:

Business type	Where to lean	Why
Local services and ecommerce	SEO first, then AEO	Buyers still search with transactional intent and click to buy or book
B2B SaaS	All three, with GEO rising	Buyers ask AI tools to compare vendors before they ever visit a site
Agencies	All three, sold as one program	Clients want rankings and AI visibility, and reporting both sets you apart
Publishers and educators	AEO and SEO	Definitions and how-to answers are prime snippet and AI Overview material
New brands with low authority	AEO, then GEO	Clear answers can win features faster than backlinks can build rank

Not sure where you stand?

Pick five questions your buyers ask. Search them on Google, then ask ChatGPT and Perplexity. Where you’re missing tells you where to start.

A 30-day plan to cover SEO, AEO, and GEO together

Ready to put this into motion? This is a realistic month for a small team.

Week 1: Baseline and fix the foundation

• Record rankings and clicks for your top 20 pages.
• Run 20 to 30 buyer prompts across AI tools and note who gets cited.
• Fix crawl errors, broken canonicals, and pages blocked by robots.txt.

Week 2: Rebuild your top pages for answers

• Add a direct answer in the first 100 words of each priority page.
• Turn vague headings into the questions people actually ask.
• Add a comparison table or step list wherever readers need to choose or act.

Week 3: Add proof and structure

• Replace unsourced claims with stats linked to the original study.
• Add FAQ and article schema, plus real author bios.
• Tighten internal linking so related answers point to each other.
• Fill topic gaps using semantic SEO so each page covers the full subject, not just one keyword.

Week 4: Build authority off your site

• Pitch one data point or expert quote to industry publications.
• Show up where AI engines look for opinions, using Reddit SEO and relevant communities.
• Get listed on trusted review sites and directories, a core part of citation SEO.
• Rerun your week 1 prompts and compare.

Don’t expect GEO to move in a month. Rankings and snippets can shift within weeks, but AI citations tend to follow authority, and authority takes longer.

How Contentpen helps you run all three from one workspace

Juggling a rank tracker, a writing tool, a schema plugin, and an AI monitoring tool gets messy fast. Contentpen is an SEO and AEO tool that brings that whole loop into one place.

It maps neatly to each layer:

• For SEO: find what to write with keyword research and topic clusters, then see what top pages cover with SERP and gap analysis. Google Search Console data sits right inside your workspace.
• For AEO: write in an editor with live SEO and GEO scoring. Failing checks can be fixed with one AI pass, so answers, headings, and structure stay tight.
• For GEO: AI Visibility tracks how ChatGPT, Google AI, Gemini, Perplexity, Copilot, Grok, and Claude mention your brand. It shows share of voice, sentiment, top cited sources, and the source gaps where competitors get cited and you don’t.

Once a draft is ready, automated linking and one-click publishing to WordPress, Shopify, Wix, and other CMSs take care of the busywork. Teams can also connect Contentpen to AI assistants through its API and MCP server.

Managing this for clients? See how Contentpen for agencies handles multiple brands in one account.

Want to see where you stand across search and AI?

Start with Contentpen today and track your rankings, answers, and AI citations in one place.

One search strategy, three ways to win

SEO, AEO, and GEO aren’t rivals. They’re three layers of the same job: making your content easy to find, easy to extract, and easy to trust.

SEO gets you ranked. AEO gets you chosen as the answer. GEO gets your brand named when an AI writes the answer itself.

Build one strong page at a time, measure each layer on its own terms, and keep earning mentions beyond your site. Do that, and the labels stop mattering.

Frequently asked questions

A schema markup is a short block of JSON-LD code that describes a page’s content using the schema.org vocabulary. The simplest one names your organization:

{“@context”: “https://schema.org“, “@type”: “Organization”, “name”: “Brightleaf”, “url”: “https://example.com”}

Wrap it in a script tag, paste it into your page, and search engines can read it.

The trouble is that most guides show schema as screenshots. You can’t copy an image, and retyping code by hand is how errors creep in.

Worse, many examples online are outdated. Some still promise FAQ rich results that Google stopped showing in 2026.

Below you’ll find 10 copyable schema markup examples, a connected multi-type example, and the steps to test them.

Grab the one you need and adapt it.

Key takeaways

• Every example here uses JSON-LD, the format Google recommends whenever your setup allows it.
• Start with Organization, WebSite, and BreadcrumbList, then add page-level types like Article or Product.
• Always fill Google’s required properties, or valid code still won’t qualify for rich results.
• Connect multiple types on one page with @graph and @id instead of separate, disconnected blocks.
• FAQPage code is still valid, but it no longer earns a rich result in Google Search.
• Test every snippet in the Rich Results Test and the Schema Markup Validator before going live.

What does a schema markup example look like?

Every JSON-LD example follows the same pattern. Once you see it, every other snippet becomes easy to read.

Part	What it does	Example value
<script type=”application/ld+json”>	Tells the browser this is structured data	Wraps every snippet
@context	Names the vocabulary	“https://schema.org”
@type	Names the thing you’re describing	“Organization”, “Product”
Properties	The facts about that thing	name, url, price, author
Nested objects	A thing inside a thing	An Offer inside a Product

That’s the whole structure. Now let’s look at real examples.

10 schema markup examples in JSON-LD

Each snippet below includes the script tag, so you can paste it straight into a page. Swap the sample values for your own.

1. Organization schema example

Use this on your homepage or about page. The sameAs list ties your brand to its official profiles.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “Organization”,   “name”: “Brightleaf”,   “url”: “https://example.com”,   “logo”: “https://example.com/logo.png”,   “contactPoint”: {     “@type”: “ContactPoint”,     “contactType”: “customer support”,     “email”: “support@example.com”   },   “sameAs”: [     “https://www.linkedin.com/company/brightleaf”,     “https://x.com/brightleaf”   ] } </script>

2. WebSite schema example

This one tells Google your preferred site name. Place it on the homepage only.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “WebSite”,   “name”: “Brightleaf”,   “alternateName”: “Brightleaf Studio”,   “url”: “https://example.com” } </script>

3. BreadcrumbList schema example

Breadcrumbs show the page’s path instead of a raw URL. Each step needs a position, a name, and a link.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “BreadcrumbList”,   “itemListElement”: [     { “@type”: “ListItem”, “position”: 1, “name”: “Home”, “item”: “https://example.com” },     { “@type”: “ListItem”, “position”: 2, “name”: “Blog”, “item”: “https://example.com/blog” },     { “@type”: “ListItem”, “position”: 3, “name”: “Schema guide” }   ] } </script>

The last item can skip the item URL, since it’s the current page.

4. Article schema example

Use BlogPosting for blog posts and NewsArticle for news. Keep dateModified honest, because stale dates erode trust.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “BlogPosting”,   “headline”: “How to plan a content calendar”,   “image”: “https://example.com/images/calendar.jpg”,   “datePublished”: “2026-09-02”,   “dateModified”: “2026-10-10”,   “author”: {     “@type”: “Person”,     “name”: “Sara Khan”,     “url”: “https://example.com/authors/sara”   },   “publisher”: {     “@type”: “Organization”,     “name”: “Brightleaf”,     “logo”: “https://example.com/logo.png”   } } </script>

Article markup works best on content that’s already well built. If you’re still drafting, learn how to write a blog post for SEO first.

5. Product schema example

This is the snippet ecommerce stores ask about most. It combines Product, Offer, and AggregateRating in one block.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “Product”,   “name”: “Brightleaf Ceramic Mug”,   “image”: “https://example.com/images/mug.jpg”,   “description”: “A 350 ml handmade ceramic mug.”,   “sku”: “BL-MUG-01”,   “brand”: { “@type”: “Brand”, “name”: “Brightleaf” },   “offers”: {     “@type”: “Offer”,     “url”: “https://example.com/mug”,     “price”: “24.00”,     “priceCurrency”: “USD”,     “availability”: “https://schema.org/InStock”   },   “aggregateRating”: {     “@type”: “AggregateRating”,     “ratingValue”: “4.7”,     “reviewCount”: “128”   } } </script>

Only add ratings that come from real customer reviews shown on the page. Google’s product structured data guide lists the extra properties for merchant listings, such as shipping and returns.

6. LocalBusiness schema example

Use the most specific subtype you can, such as Dentist, Restaurant, or Store. Add one block per location page.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “CafeOrCoffeeShop”,   “name”: “Brightleaf Cafe”,   “image”: “https://example.com/images/cafe.jpg”,   “telephone”: “+1-555-0142”,   “priceRange”: “$$”,   “address”: {     “@type”: “PostalAddress”,     “streetAddress”: “18 Elm Road”,     “addressLocality”: “Austin”,     “addressRegion”: “TX”,     “postalCode”: “78701”,     “addressCountry”: “US”   },   “geo”: { “@type”: “GeoCoordinates”, “latitude”: 30.2672, “longitude”: -97.7431 },   “openingHoursSpecification”: [{     “@type”: “OpeningHoursSpecification”,     “dayOfWeek”: [“Monday”, “Tuesday”, “Wednesday”, “Thursday”, “Friday”],     “opens”: “07:00”,     “closes”: “18:00”   }] } </script>

7. Event schema example

This works for in-person and online events. Always include eventStatus so you can mark changes like postponements.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “Event”,   “name”: “Content Strategy Workshop”,   “startDate”: “2026-11-20T15:00:00+05:00”,   “endDate”: “2026-11-20T17:00:00+05:00”,   “eventStatus”: “https://schema.org/EventScheduled”,   “eventAttendanceMode”: “https://schema.org/OnlineEventAttendanceMode”,   “location”: { “@type”: “VirtualLocation”, “url”: “https://example.com/workshop” },   “organizer”: { “@type”: “Organization”, “name”: “Brightleaf”, “url”: “https://example.com” },   “offers”: {     “@type”: “Offer”,     “price”: “0”,     “priceCurrency”: “USD”,     “availability”: “https://schema.org/InStock”,     “url”: “https://example.com/workshop”   } } </script>

8. Person and ProfilePage schema example

Use this on author pages. It links a writer to their real-world profiles, which supports expertise signals.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “ProfilePage”,   “mainEntity”: {     “@type”: “Person”,     “name”: “Sara Khan”,     “jobTitle”: “Head of Content”,     “worksFor”: { “@type”: “Organization”, “name”: “Brightleaf” },     “sameAs”: [“https://www.linkedin.com/in/sarakhan-example”]   } } </script>

9. VideoObject schema example

Video markup helps Google show thumbnails and durations. The duration uses ISO 8601 format, so 4 minutes 30 seconds is PT4M30S.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “VideoObject”,   “name”: “How to brew pour-over coffee”,   “description”: “A step-by-step pour-over tutorial.”,   “thumbnailUrl”: “https://example.com/images/pourover.jpg”,   “uploadDate”: “2026-08-14”,   “duration”: “PT4M30S”,   “contentUrl”: “https://example.com/videos/pourover.mp4” } </script>

10. FAQPage schema example (and its 2026 status)

Here’s a heads-up before you copy this one. Google’s Search Central updates log confirms FAQ rich results stopped showing in Google Search in May 2026.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “FAQPage”,   “mainEntity”: [{     “@type”: “Question”,     “name”: “Do you ship internationally?”,     “acceptedAnswer”: {       “@type”: “Answer”,       “text”: “Yes, we ship to 40 countries. Delivery takes 5 to 10 business days.”     }   }] } </script>

The code is still valid schema.org, so it won’t cause errors. Just don’t expect expandable questions under your listing. The visible FAQ section on the page still helps readers and answer engines, as many AEO examples show.

How do you connect several schema types on one page?

Most pages need more than one type of schema. Instead of pasting three separate blocks, connect them in a single @graph and link them with @id.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@graph”: [     {       “@type”: “Organization”,       “@id”: “https://example.com/#org”,       “name”: “Brightleaf”,       “url”: “https://example.com”     },     {       “@type”: “WebPage”,       “@id”: “https://example.com/blog/calendar#webpage”,       “url”: “https://example.com/blog/calendar”,       “isPartOf”: { “@id”: “https://example.com/#website” }     },     {       “@type”: “BlogPosting”,       “headline”: “How to plan a content calendar”,       “mainEntityOfPage”: { “@id”: “https://example.com/blog/calendar#webpage” },       “publisher”: { “@id”: “https://example.com/#org” }     }   ] } </script>

Why bother? Each @id works like a name badge. Search engines see one connected story, with the article on the page, the page on the site, and the publisher behind it all.

Define #website with your WebSite block from example 2, given the same @id.

JSON-LD vs Microdata vs RDFa: the same example three ways

All three formats can describe the same organization. Here’s how each one looks.

JSON-LD keeps the code separate from your HTML:

<script type=”application/ld+json”> { “@context”: “https://schema.org”, “@type”: “Organization”, “name”: “Brightleaf”, “url”: “https://example.com” } </script>

Microdata adds attributes to tags you already have:

<div itemscope itemtype=”https://schema.org/Organization”>   <a itemprop=”url” href=”https://example.com”><span itemprop=”name”>Brightleaf</span></a> </div>

RDFa does the same with different attribute names:

<div vocab=”https://schema.org/” typeof=”Organization”>   <a property=”url” href=”https://example.com”><span property=”name”>Brightleaf</span></a> </div>

Format	Easy to maintain?	Touches your design HTML?	Google’s view
JSON-LD	Yes	No	Recommended
Microdata	Harder	Yes	Supported
RDFa	Harder	Yes	Supported

Google’s introduction to structured data recommends JSON-LD where possible. It also shares results like Food Network’s 35% increase in visits after adding structured data to 80% of its pages.

Where should you paste schema markup?

JSON-LD can sit in the <head> or the <body>. Where you add it depends on your platform.

Platform	Easiest way to add schema
WordPress	An SEO plugin such as Yoast or Rank Math, or a custom HTML block for one-off pages
Shopify	Theme files (product.liquid or a JSON-LD snippet), or a schema app
Webflow	Page settings, under custom code in the head
Wix	SEO settings, under structured data markup
Next.js or React	A script tag with type application/ld+json rendered server-side
Any site	Google Tag Manager, though server-rendered code is more reliable

Render the code on the server whenever you can. Markup injected late by JavaScript can be missed or delayed. It’s one of those technical SEO basics that saves headaches later.

How do you test a schema markup example?

Never ship a snippet you haven’t tested. It takes two minutes.

1. Paste your code or URL into Google’s Rich Results Test to check rich result eligibility.
2. Run the same code through the Schema Markup Validator to catch general schema.org errors.
3. Fix any red errors first, then review the yellow warnings for missing recommended properties.
4. Publish, then request indexing in Search Console.
5. Watch the enhancement reports in Search Console over the next few weeks.

Once rich results appear, compare clicks before and after. Our guide on how to calculate CTR walks through the math.

What are the most common schema markup errors?

These are the errors that turn up most often when people adapt an example. Each one has a quick fix.

Error	Why it happens	Fix
Missing required field	Example was trimmed too far	Check Google’s docs for that type’s required list
Trailing comma	Last property ends with a comma	Remove it; JSON doesn’t allow trailing commas
Curly quotes	Code was pasted from a word processor	Retype quotes as straight quotes
Wrong date format	Dates written as “Oct 10”	Use ISO 8601, such as 2026-10-10
Markup doesn’t match the page	Price or rating not visible to users	Mark up only what visitors can see
Duplicate blocks	Plugin and theme both output schema	Turn one off

How Contentpen fits into your schema workflow

A perfect snippet can’t save a weak page. Contentpen, the SEO tool online for SEO and AEO teams, helps you build the page your schema describes.

• Better source material: The SEO scoring tool checks headings, meta details, alt tags, FAQ blocks, and named entities as you write. Those become the values in your Article markup.
• Clean handoff to your CMS: Contentpen’s CMS integrations publish posts to WordPress, Shopify, Wix, Webflow, Ghost, and more, where your schema plugin or template adds the JSON-LD. Here’s how to connect WordPress to Contentpen.
• See what AI engines say: AI visibility tracking shows whether ChatGPT, Perplexity, Gemini, and other engines mention your brand after you publish.

Want every new post to arrive structured, scored, and ready for markup? Try Contentpen on your next article.

Start with one snippet and build from there

You don’t need all 10 examples on day one. Start with Organization and WebSite on your homepage, then BreadcrumbList across the site.

After that, add the page-level type that fits each template, such as Article, Product, or LocalBusiness. Test each one before it goes live.

Small, accurate snippets beat sprawling ones every time. Copy, adapt, validate, and repeat.

Frequently asked questions

SEO (search engine optimization) helps your pages rank in Google’s results so people click through. GEO (generative engine optimization) helps your brand get mentioned and cited inside answers written by ChatGPT, Perplexity, Gemini, and Google AI Overviews.

One earns a position. The other earns a place in the answer itself.

Think about the last time you asked an AI tool for a recommendation. Did you scroll through ten blue links afterward, or did you trust the three names it gave you?

Your buyers do the same. SparkToro’s 2026 clickstream study found that 68% of US Google searches now end without a click. Strong rankings still matter, but they no longer guarantee you get seen.

The smart move isn’t to drop SEO for GEO. It’s to understand what each one rewards and run them as one strategy.

Below, you’ll see how they differ, how AI engines pick sources, which tactics carry over, and how to split your effort.

Key takeaways

• SEO wins rankings and clicks. GEO wins mentions, citations, and recommendations inside AI answers.
• SEO evaluates whole pages. GEO is judged passage by passage and across everything the web says about your brand.
• Ranking still helps you get cited, but the link is weakening as AI engines pull from deeper in the results.
• GEO is not a replacement for SEO. It’s an extra layer built on crawlable, trusted, well-structured content.
• Measure GEO with share of voice, citation rate, and sentiment alongside rankings and traffic.
• Most teams can run both with one content process and a small shift in time and priorities.

What does SEO mean in 2026?

SEO is the practice of improving your website so search engines rank it higher for relevant queries. The reward is a click from someone who chose your result over the others.

The core hasn’t changed much. You still need:

• Content that matches search intent
• A site Google can crawl, render, and index
• Backlinks and mentions that signal authority
• A page experience people actually enjoy

What has changed is the results page around you. AI Overviews, AI Mode, videos, and forums now compete for the same screen space. 

What does GEO mean, and where did it come from?

GEO is the practice of shaping your content and online presence so generative AI engines mention, quote and recommend you. Success isn’t a position on a page. It’s being part of the answer.

The term comes from a 2023 research paper on generative engine optimization by researchers at Princeton and partner institutions. They showed that content changes like adding statistics, quotes, and sources could lift a page’s visibility in AI responses by up to 40%.

So what does a generative engine actually do?

It reads many sources, writes one answer, and credits a handful of them. GEO is about being one of those few, and it sits inside the wider practice of AI search optimization.

GEO vs SEO: what’s the actual difference?

The biggest shift is what gets judged. SEO scores a page. GEO scores passages from your page plus everything else the web says about your brand.

Dimension	SEO	GEO
Full form	Search engine optimization	Generative engine optimization
Core goal	Rank and earn the click	Get mentioned, cited, or recommended in the answer
Where you appear	Google and Bing results pages	ChatGPT, Perplexity, Gemini, Claude, Copilot, Google AI Overviews and AI Mode
Typical query	2 to 5 keywords	Full questions with context, constraints, and follow-ups
What the user sees	A list of options to compare	One synthesized answer with a few named sources
What gets evaluated	The whole page	Individual passages plus your brand’s overall reputation
How content is found	Crawled, indexed and ranked	Retrieved through query fan-out from search indexes, plus what the model learned in training
Main selection signals	Relevance, backlinks, technical health, page experience	Clear answers, specific facts, entity consistency, third-party mentions
Role of links	Backlinks are a core ranking signal	Unlinked brand mentions and co-citations matter as much as links
Content that wins	Comprehensive pages matched to search intent	Self-contained passages, original data, quotes and comparisons
Off-site work	Link building and digital PR	Reviews, Reddit and forums, listicles, news coverage and community answers
Technical focus	Crawlability, site speed, Core Web Vitals, schema	Same basics, plus access for AI crawlers and key content in plain HTML text
Traffic pattern	Clicks are the main payoff	Many answers end without a visit, so visibility counts even without clicks
Personalization	Results vary mainly by location and device	Answers vary by wording, conversation history and follow-up questions
Success metrics	Rankings, CTR, organic traffic, conversions	Mention rate, citation rate, share of voice, sentiment
Typical tools	Search Console, Ahrefs, rank trackers	AI visibility trackers and repeated prompt testing
Stability	Fairly stable week to week	Answers can change between runs, models and updates
Time to results	Weeks to months after indexing	Days for engines that search live, longer for what models learn in training
Maturity	25+ years, with official search engine guidelines	Named in 2023, with few official guidelines so far

One row deserves a second look: what the user sees. In SEO, you compete for attention on a list. In GEO, the AI has already made the shortlist for the user.

How do AI engines decide which sources to cite?

No AI company publishes a full formula. Still, most AI search tools follow a similar path when they answer a question.

1. They expand the question: One prompt becomes several related searches behind the scenes, often called query fan-out.
2. They retrieve candidate pages: Many pull from a live search index, so crawlable, indexed pages have the edge.
3. They pick useful passages: Short, self-contained answers with clear facts are easier to lift.
4. They write the answer: The model blends those passages with what it already knows about each brand.
5. They attribute sources: A few URLs get cited or linked, and some brands get named without a link.

This is where SEO and GEO start to drift apart.

In July 2025, Ahrefs found that about 76% of AI Overview citations came from pages ranking in Google’s top 10. By March 2026, Ahrefs’ updated study put that figure at roughly 38%.

In other words, ranking still helps.

But more citations now go to pages that rank lower or not at all, as long as they answer the sub-question well.

Is GEO replacing SEO?

No, and the reason is simple. Most AI engines still need the open web to answer fresh questions, and they reach it through search indexes.

If Google or Bing can’t crawl and trust your page, AI tools built on those indexes are less likely to find it. Google’s own guidance on generative AI features in Search frames this work as part of SEO, not a separate discipline.

What is changing is the payoff. A top ranking used to mean steady clicks. Now it often means being one input to an answer the user reads without visiting you.

What does SEO still do for GEO?

More than most GEO advice admits. A lot of the groundwork is shared.

• Crawlability and indexing: AI search tools can’t cite what they can’t fetch.
• Topical authority: A cluster of strong pages signals expertise to rankers and models alike.
• Backlinks and mentions: Quality SEO backlinks double as trust signals that models pick up.
• Clear on-page structure: Headings, short paragraphs, and lists help both crawlers and passage extraction.
• Freshness: Updated facts help you rank and stop AI from repeating stale details about you.

If your site already passes a solid on-page SEO checklist, you’ve done much of the GEO prep without realizing it.

Where do AEO and AIO fit next to GEO and SEO?

You’ll see a few more acronyms in this space. Our SEO vs GEO vs AEO guide compares all three.

Here’s the short version of each full form.

• SEO (search engine optimization): ranking pages in search results.
• AEO (answer engine optimization): winning the single direct answer in snippets, voice, and AI Overviews.
• GEO (generative engine optimization): earning mentions and citations in AI-written answers.
• AIO (AI optimization): a loose umbrella term, sometimes used just for Google AI Overviews.

Think of SEO as the foundation, answer engine optimization as the bridge, and GEO as the newest layer. The labels overlap, so focus on the outcome you want rather than the acronym.

If you’re deciding between the two AI layers, read AEO vs GEO.

Which SEO tactics should you keep, and what should you add for GEO?

You don’t need a second playbook. You need a few additions to the one you have.

Keep doing this for SEO	Add this for GEO
Target keywords with clear intent	Target full questions and follow-up prompts buyers ask AI
Write comprehensive pages	Open every section with a direct, quotable answer
Build backlinks	Earn brand mentions in reviews, listicles, forums and news
Optimize title tags and meta descriptions	Describe your brand, category, and audience the same way everywhere
Add schema markup	Publish original data, quotes and named sources
Refresh content when rankings drop	Refresh when AI answers describe you wrongly or skip you

Notice the theme? SEO tactics mostly live on your site. GEO tactics push you outward to the places models learn from.

Each engine also behaves a little differently. Our comparison of how Perplexity and ChatGPT differ shows why it pays to test prompts on more than one.

How do you measure GEO compared with SEO?

SEO reporting is mature. GEO reporting is newer, so you’ll need a few fresh metrics next to your usual SEO analytics.

SEO metric	GEO counterpart
Keyword rankings	Mention rate across a fixed set of prompts
Organic traffic	AI referral visits plus branded search lift
Click-through rate	Citation rate (how often your URL is linked)
Share of top 10 positions	Share of voice versus competitors in AI answers
Backlink growth	Growth in third-party sources AI engines cite about you

Run the same prompts every month. AI answers vary between runs, so trends tell you far more than one screenshot.

How should you split time between SEO and GEO?

There’s no universal ratio, and anyone quoting one is guessing. Your split should follow where your buyers research.

• New site with little authority: put most effort into SEO basics. AI engines rarely cite brands nobody has heard of.
• Established site with steady rankings: keep SEO running and move a meaningful slice of time to GEO work like digital PR and prompt tracking.
• B2B or high-consideration products: lean further into GEO. Buyers often ask AI tools for shortlists before they ever search your brand.
• Local or transactional businesses: stay SEO-heavy, since many searches still end on maps, product pages, and booking forms.

Review the split each quarter. If your AI share of voice grows while rankings hold, you’ve found a balance that works.

What mistakes do teams make when moving from SEO to GEO?

A few patterns show up again and again.

1. Pausing SEO to fund GEO: You weaken the foundation AI engines rely on.
2. Chasing a single AI tool: Visibility in ChatGPT doesn’t guarantee visibility in Gemini or AI Overviews.
3. Publishing vague thought pieces: Models quote specifics, not opinions without evidence.
4. Ignoring what others say about you: Outdated reviews and old listicles shape AI answers too.
5. Expecting overnight results: Off-site mentions take time to build and get picked up.

How does Contentpen help you run SEO and GEO together?

Splitting SEO and GEO across separate tools makes it hard to see the full picture. Contentpen keeps both in one workflow, from research to reporting.

• Spot what to fix first. SEO opportunities surface competitor gaps, pages worth recovering and keyword cannibalization from your Search Console data.
• Write for rankings and answers. Articles come with key takeaways, FAQs and question-based headings that AI engines can lift easily.
• Check both scores live. SEO and GEO scoring grades each draft as you write, and “Fix with AI” resolves issues from both sides at once.
• Optimize for AI search. The AI search optimization tool helps shape content for how AI engines read and cite pages.
• Track where you show up. AI visibility tracking covers ChatGPT, Google AI, Perplexity, Gemini, Copilot, Grok, and Claude, with share of voice and source gaps.

You can publish straight to WordPress, Shopify, Wix, and other platforms when a piece is ready.

Want to rank on Google and get cited by AI from one dashboard? Start with Contentpen’s AI SEO tool today.

Rank for the click, earn the citation

SEO and GEO chase different rewards. SEO wins the visit, while GEO wins a spot in the answer before anyone visits.

They still share the same roots: crawlable pages, real expertise, clear structure, and a trusted brand. Keep your SEO strong, add GEO tactics on top, and measure both every month.

The brands that do this now will be the names AI keeps repeating later.

Frequently asked questions

Schema markup is a small piece of code you add to a web page to tell search engines exactly what that page is about.

It uses a shared vocabulary from schema.org to label things like a business name, a product price, an author, or an event date. Google, Bing, and AI search tools read these labels to understand your content, and sometimes reward it with a rich result.

Search engines are smart, but they still guess. Without clear labels, a page that mentions “Apple” could be about a fruit, a phone, or a record label.

When they guess wrong, a competitor with star ratings and prices in their listing takes your click. With AI answers now sitting above the links, a fuzzy page is even easier to skip.

This guide explains schema markup in plain English, shows you real code, and walks through adding and testing it.

Let’s start with the simple version.

Key takeaways

• Schema markup is code, usually JSON-LD, that labels your content with the schema.org vocabulary.
• It isn’t a direct ranking factor, but rich results can lift clicks. Google’s own case studies show CTR gains of 25% to 82%.
• Google recommends JSON-LD, which now appears on 41% of web pages.
• FAQ rich results stopped showing in Google Search in May 2026, so focus on types Google still supports.
• Google says no special schema is needed for AI Overviews, but markup still helps search engines understand entities.
• Always validate your code with the Rich Results Test and the Schema Markup Validator.

What is schema markup in simple terms?

Think of schema markup as a name tag for your content. Visitors see your page as usual, while search engines see the page plus a tidy label that says “this is a recipe, it takes 30 minutes, and it has 4.8 stars.”

The code sits in your page’s HTML, usually inside a script tag. Readers never see it, so it won’t touch your design.

It’s part of technical SEO because it works behind the scenes. Yet it shapes what people actually see in the results.

A quick before and after

Here’s how it plays out. Picture a bakery page that reads

Open 8 to 6, 22 Main Street, call 555-0100.

• Without schema: a crawler reads plain text and has to infer that “8 to 6” means opening hours.
• With schema: the same facts are tagged as openingHours, address, and telephone on a Bakery entity.

The second version leaves nothing to interpret. That clarity is the whole point.

Schema markup vs structured data: are they the same thing?

Not quite, although most people use the two terms as if they were. This table untangles four terms that often get mixed up.

Term	What it means	Simple analogy
Structured data	Any information organized in a standard, machine-readable format	The idea of labeling things
Schema.org	The shared vocabulary of types and properties	The dictionary
Schema markup	Structured data written with the schema.org vocabulary on a web page	The labels you stick on
Rich results	Enhanced listings Google may show based on that markup	The reward you might earn

In short, all schema markup is structured data. Not all structured data is schema markup, though. Open Graph tags for social previews are structured data too, but they use a different vocabulary.

How does schema markup work?

Every piece of schema markup has two parts: a vocabulary and a syntax. Search engines crawl your page, parse the code, and connect those labels to what they already know.

The vocabulary comes from schema.org

Google, Microsoft, Yahoo, and Yandex founded schema.org to give the web one common language. Version 30.1, released in September 2026, includes 826 types and 1,540 properties.

That sounds like a lot. The good news?

Most websites only need five to eight of them.

Adoption is massive, too. According to schema.org, more than 45 million domains marked up their pages with over 450 billion schema.org objects as of 2024.

The syntax: JSON-LD, Microdata, or RDFa

You can write schema markup in three formats. They all say the same thing in different ways.

Format	How it’s added	Share of pages (2024)	Best for
JSON-LD	A separate script block in the head or body	41%	Almost every site, and Google’s preferred format
Microdata	Attributes inside your existing HTML tags	26%	Older templates already built this way
RDFa	Attributes inside HTML, also used by Open Graph	66%	Linked data projects and social tags

These adoption figures come from the HTTP Archive Web Almanac 2024. RDFa looks high only because Open Graph tags count toward it.

JSON-LD is the one to watch. Its share grew from 34% of pages in 2022, and Google recommends it whenever your setup allows.

Why is schema markup important for SEO?

Schema markup gives search engines certainty. That certainty pays off in a few ways.

It can turn a plain link into a rich result

Rich results are listings with extras like star ratings, prices, images, or breadcrumbs. They take more space on the page and pull the eye.

The numbers back this up. Google’s structured data case studies report:

• Rotten Tomatoes saw a 25% higher click-through rate on pages enhanced with structured data.
• Food Network saw a 35% increase in visits after adding it to 80% of its pages.
• Nestlé measured an 82% higher click-through rate on pages that showed as rich results.

A better click-through rate means more traffic from rankings you already hold. No new backlinks needed.

It helps search engines understand entities

Search engines no longer just match words. They map people, brands, products, and places as entities, then connect them in a knowledge graph.

Schema markup lets you state those facts outright. A sameAs property, for example, ties your Organization to its LinkedIn or Crunchbase profile.

It’s the same thinking behind semantic SEO, where meaning matters more than exact-match keywords.

Is schema markup a ranking factor?

No, not directly. Google has said for years that structured data alone doesn’t push a page higher.

But here’s the catch. Schema can still grow traffic through better CTR, eligibility for search features, and clearer entity signals. Treat it as a visibility tool, not a ranking trick.

Does schema markup help with AI search?

It’s a fair question. Schema helps AI engines extract your content more easily, but it isn’t directly tied to AI citations.

Think of it this way. Clean markup hands AI systems your key facts, like your brand name, prices, and authors, in a format they can’t misread.

Whether they actually cite you is a different matter. That depends on how well your content answers the question and how much the web trusts your brand.

Google’s page on AI features and your website states there’s “no special schema.org structured data that you need to add” to appear in AI Overviews or AI Mode. It does ask that your structured data match the visible text on the page.

Independent data points the same way. When Ahrefs tracked 1,885 pages adding schema, ChatGPT and AI Mode citations moved only about 2%, a change indistinguishable from zero.

So where does schema still earn its keep? It feeds the search indexes and knowledge graphs that Google AI Overviews and Bing Copilot draw from. That makes it one supporting layer of answer engine optimization, next to clear answers, solid structure, and trusted mentions.

What are the most common types of schema markup?

You won’t need all 826 types. These nine cover most websites.

Schema type	Where to use it	What it can unlock in Google
Organization	Homepage or about page	Logo and company details
WebSite	Homepage	Your site name in results
BreadcrumbList	Most inner pages	A breadcrumb trail instead of a raw URL
Article or BlogPosting	Blog posts and news	Headline, image, author, and date details
Product with Offer	Product pages	Price, stock status, and review stars
LocalBusiness	Location pages	Hours, address, and map details
Review or AggregateRating	Reviewed items	Star ratings
Event	Event pages	Event listings with dates
VideoObject	Pages with video	Thumbnails and key moments

Our guide to 25 types of schema markup covers the rest.

One big 2026 change: FAQ rich results stopped appearing in Google Search on May 7, 2026, according to Google’s Search Central updates log. FAQPage is still valid schema.org code, but it no longer earns a special listing.

Google’s search gallery lists every feature it still supports. Check it before you build anything new.

What does schema markup look like in code?

Here’s the bakery from earlier, written as LocalBusiness markup in JSON-LD. You’d paste it into the page’s HTML.

<script type=”application/ld+json”> {   “@context”: “https://schema.org”,   “@type”: “Bakery”,   “name”: “Main Street Bakery”,   “telephone”: “+1-555-0100”,   “openingHours”: “Mo-Sa 08:00-18:00”,   “address”: {     “@type”: “PostalAddress”,     “streetAddress”: “22 Main Street”,     “addressLocality”: “Springfield”,     “addressCountry”: “US”   } } </script>

Each part has one job:

• @context tells the crawler you’re using schema.org.
• @type names the thing you’re describing, here a Bakery, which is a kind of LocalBusiness.
• Everything else is a property, like the name, phone, hours, and address.

Check our guide with 20+ schema markup examples to view more samples.

How do you add schema markup to a website?

You don’t need to be a developer for most sites. Follow these steps.

1. Pick the right type: Match the main subject of the page, such as a product, an article, or a location.
2. Generate the code: Write it by hand, use a schema generator, or ask an AI assistant for a first draft.
3. Fill the required properties: Google’s documentation lists required and recommended fields for each type.
4. Add it to the page: Paste the JSON-LD into your template, or use a CMS plugin, theme setting, or Google Tag Manager.
5. Test before you publish: Run the code through the validation tools below.
6. Monitor after launch: Search Console flags errors as Google recrawls your pages.

How do you check if schema markup is working?

Three free tools cover almost every check you’ll need.

Tool	What it checks	When to use it
Rich Results Test	Whether a page is eligible for Google rich results	Before and right after publishing
Schema Markup Validator	Whether any schema.org code is valid	Debugging any type, even ones Google ignores
Search Console enhancement reports	Errors and valid items across the whole site	Ongoing monitoring

Keep one thing in mind. Passing the validator doesn’t guarantee a rich result, because Google applies its own eligibility rules.

Make schema checks a standing item in every SEO audit you run.

Which schema mistakes should you avoid?

Most schema problems come from a handful of habits. Watch for these:

• Marking up hidden content: Google’s structured data policies say markup must describe what users can see, or you risk a manual action.
• Self-serving reviews: Adding star ratings your business wrote about itself breaks the rules.
• Missing required properties: The code may validate, but it won’t qualify for the feature.
• Duplicate markup: A theme and a plugin both outputting Organization schema can send mixed signals.
• Stale values: An old price or dateModified that no longer matches the page erodes trust.
• The wrong type: LocalBusiness on a blog post confuses more than it helps.

Run these checks alongside your on-page SEO checklist so nothing slips through.

How Contentpen helps you get more out of schema markup

Schema only works as well as the content underneath it. If the page is vague, the markup has nothing solid to describe.

Contentpen is an SEO AEO tool that makes sure the content is clear, structured, and ready to be understood. It doesn’t write JSON-LD for you, but it handles everything the markup depends on:

• Live SEO and GEO scoring checks heading hierarchy, answer-box paragraphs, FAQ blocks, meta details, and named entity coverage as you write.
• AI-extractable structure adds key takeaways and a hyperlinked table of contents, so answer engines can lift your content cleanly.
• One-click CMS publishing sends posts to WordPress, Shopify, Wix, Webflow, Ghost, and more, where your schema plugin can tag them automatically.
• The AI visibility tool tracks how ChatGPT, Google AI, Perplexity, Gemini, Copilot, Grok, and Claude mention your brand, so you can see what’s working.

Ready to publish pages that search engines and AI answers both understand? Start your first article in Contentpen today.

Schema markup turns your page into a clear answer

Schema markup is a label that removes guesswork. It tells search engines who you are, what you offer, and how each fact on your page fits together.

It won’t lift rankings by itself. It can, however, win richer listings, sharper entity signals, and a cleaner path into the systems AI answers rely on.

Start with Organization, WebSite, and BreadcrumbList. Add the types that match your pages, validate everything, and keep the values fresh.

Frequently asked questions

AEO (answer engine optimization) gets your content picked as the single, direct answer to a question. Think featured snippets, voice replies, and Google AI Overviews. GEO (generative engine optimization) gets your brand cited and recommended inside AI-written answers from ChatGPT, Perplexity, Gemini, and Claude.

So AEO wins the answer. GEO wins the mention.

Your rankings might look fine while clicks keep slipping. In a Pew Research Center study, Google users clicked a result in just 8% of visits when an AI summary appeared, compared with 15% when it didn’t.

Meanwhile, half the advice online treats AEO and GEO as rivals. The other half calls them the same thing. You end up with two half-built strategies and no clear way to measure either.

Once you see what each discipline actually optimizes for, you can build one content system that serves both.

Let’s break down the differences, the overlap, real examples, and the exact tactics to use.

Key takeaways

• AEO targets one extractable answer. GEO targets citations and brand mentions inside synthesized AI responses.
• AEO success looks like a featured snippet or AI Overview extract. GEO success looks like share of voice across AI engines.
• Both sit on top of SEO. Google itself says optimizing for its AI features “is still SEO.”
• Most of the work overlaps: answer-first structure, clear entities, fresh facts, and strong authority signals.
• GEO leans harder on off-site signals like reviews, Reddit threads, listicles, and press mentions.
• Measure both with AI visibility metrics, not just rankings and clicks.

What does AEO mean?

AEO stands for answer engine optimization. It’s the practice of shaping content so a search or AI system can lift one clean answer straight from your page.

The idea started in the voice search era. Assistants like Alexa and Siri could read only one answer aloud, so being “the answer” mattered more than being on page one.

Today, answer engine optimization covers a few surfaces:

• Featured snippets and People Also Ask boxes
• Google AI Overviews and AI Mode extracts
• Voice assistant replies
• Knowledge panels

The win is precise. Your sentence, your definition, or your list becomes the response.

What does GEO mean?

GEO stands for generative engine optimization. It focuses on how your brand shows up when an AI model writes a full answer by pulling from many sources.

The term comes from a 2023 research paper by a team from Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi. In the original GEO study, the authors found that targeted content changes could boost source visibility by up to 40% in generative engine responses.

Here, you’re not chasing one slot. You’re trying to be one of the three to five sources a model trusts, quotes, and recommends.

GEO mostly plays out on:

• ChatGPT and ChatGPT search
• Perplexity
• Gemini and Google AI Mode
• Claude, Copilot and Grok

How are AEO and GEO different?

The simplest split is this. AEO optimizes a passage. GEO optimizes a brand’s presence across many passages and many sites.

Factor	AEO	GEO
Full form	Answer engine optimization	Generative engine optimization
Main goal	Be the direct answer	Be cited or recommended in AI answers
Unit of success	One extracted snippet	Mentions and citations across prompts
Main surfaces	Featured snippets, PAA, voice, AI Overviews	ChatGPT, Perplexity, Gemini, Claude, Copilot
Query type	Short, factual, single-intent	Long, conversational, comparison or advice
Content style	Concise definitions, steps, lists	Depth, original data, clear positioning
Where signals come from	Mostly your own page	Your site plus reviews, forums, media, and listicles
Key metrics	Snippet wins, AI Overview inclusion	Share of voice, citation rate, sentiment
Origin	Voice search, around 2017 and 2018	Academic research, 2023

Notice the “where signals come from” row. That one difference shapes most of your strategy.

Where do AEO and GEO overlap?

A well-built page can often win in both places.

Both approaches reward:

• Answer-first writing: Lead each section with the direct answer, then add context.
• Clear entities: Name your brand, product, category, and people the same way everywhere.
• Structure machines can parse: Question-based headings, short paragraphs, tables and lists.
• Freshness: Updated stats, current years, and accurate product details.
• Trust signals: Real authors, cited sources, and a consistent reputation off-site.

That’s why many teams treat AEO as the on-page half of the job and GEO as the on-page plus off-page whole. If you already invest in semantic SEO, you’re halfway there.

AEO vs GEO vs SEO, AIO and LLMO: what’s the full form of each?

The acronyms keep multiplying. Let’s sort them out in one place.

Term	Full form	What it focuses on
SEO	Search engine optimization	Ranking pages in traditional search results
AEO	Answer engine optimization	Being the single direct answer
GEO	Generative engine optimization	Being cited in AI-generated answers
AIO	AI optimization (sometimes AI Overviews optimization)	A broad label for optimizing for AI search, or Google AI Overviews specifically
LLMO	Large language model optimization	How models understand and describe your brand

For a full side-by-side of all three, read SEO vs GEO vs AEO.

SEO is still the base layer. Google’s own guide to generative AI features in Search says optimizing for those features “is still SEO” and that no special schema markup is needed.

AIO and LLMO mostly overlap with GEO. The labels differ, but the work and the metrics are nearly identical.

For a deeper look at how AI search optimization compares with traditional SEO, see our full breakdown.

What do AEO and GEO look like in a real search?

Theory is easy. Let’s run one query through both lenses.

The query: “How often should I update old blog posts?”

The AEO outcome

Google shows an AI Overview or featured snippet. It pulls a two-sentence answer from one page: “Review high-value posts every three to six months. Update them sooner if rankings, stats, or product details change.”

The winning page had a question heading that matched the query. The answer sat directly underneath in under 50 words.

The GEO outcome

A user asks ChatGPT: “What’s the best way to keep my old blog content fresh, and which tools help?“

The model writes a longer answer. It blends advice from several sources, cites three of them, and names a few content refresh tools.

The brands that got named had something extra. They appeared in comparison articles, had helpful Reddit threads, and published their own refresh data.

See the pattern? AEO rewarded one tight passage. GEO rewarded a reputation spread across the web. You’ll find more real-world AEO examples in our separate guide.

Should you focus on AEO or GEO first?

It depends on how your buyers search. Use this as a starting point.

Business type	Start with	Why
Local service business	AEO	Customers ask short, urgent questions on Google and voice
Publisher or content site	AEO	Snippets and AI Overviews drive most of your visibility
B2B SaaS	GEO	Buyers ask AI tools for tool comparisons and shortlists
Ecommerce brand	Both	Product questions need AEO; “best X for Y” prompts need GEO
Marketing agency	Both	Clients want reporting on Google and AI engines

Still unsure? Start with AEO on your top 20 pages. It’s faster to ship, and that same structure feeds GEO later.

The pressure to act is real. Gartner predicted that traditional search engine volume would drop 25% by 2026 as people move to AI chatbots and virtual agents.

How do you optimize content for AEO?

AEO is mostly an on-page job. Small formatting changes can move the needle quickly.

Match headings to real questions

Pull questions from People Also Ask, autocomplete, and your support inbox. Turn them into H2s and H3s word for word where it reads naturally.

Answer in the first 40 to 60 words

Put the direct answer right under the heading. Then expand with detail, examples, and caveats.

Use the format the query expects

• “What is” queries want a one- or two-sentence definition.
• “How to” queries want numbered steps.
• “Best” and “vs” queries want tables and lists.

Add structured data where it fits

FAQPage, HowTo, Article schema, and other types of schema help machines read your page. They won’t force a snippet, but they remove ambiguity. Keep your technical SEO basics clean too, so crawlers can reach the page at all.

Keep each passage self-contained

AI systems often lift a paragraph out of context. Avoid “as mentioned above” and name the subject in every key answer.

How do you optimize content for GEO?

GEO starts with everything above. Then it asks a bigger question: what does the rest of the web say about you?

Publish facts worth citing

Original surveys, benchmarks, and case study numbers give models a reason to quote you. The GEO paper found that adding statistics, quotations, and cited sources were among the strongest levers.

Build your brand footprint off-site

Models learn from reviews, forums, listicles and news coverage. Earn mentions on G2, Capterra, industry roundups and relevant communities. A smart Reddit SEO plan can help here.

Be clear about your positioning

Say plainly who you serve, what you do, and how you differ. Vague copy gives a model nothing to repeat.

Earn citations from trusted sources

Mentions on high-authority sites act like votes for your expertise. That’s the core idea behind citation SEO.

Connect your content with internal links

Strong internal linking helps crawlers and models see your topical depth. A cluster of linked pages beats one lonely article.

How do you measure AEO and GEO results?

Rankings alone won’t tell you much anymore. You need a mix of classic and AI-specific metrics.

Metric	Tracks	Best for
Featured snippet wins	Pages owning position zero	AEO
AI Overview inclusion	Pages cited in Google’s AI answers	AEO
Share of voice	Your mentions vs competitors across prompts	GEO
Citation rate	How often your URLs are linked as sources	GEO
Sentiment	Whether AI describes you positively	GEO
AI referral traffic	Visits from ChatGPT, Perplexity and others	Both
Branded search growth	People searching your name after seeing it in AI	Both

Start with a baseline. An AI visibility audit shows where you appear today and which competitors get cited instead.

Then track monthly. AI answers shift often, so one snapshot can mislead you.

What are the most common AEO and GEO mistakes?

We see the same slip-ups again and again. Avoid these, and you’re ahead of most competitors.

1. Building separate teams for each acronym: The work overlaps heavily. Split by task, not by label.
2. Writing “AI-only” content: Thin, robotic pages don’t earn citations from AI or rankings from Google.
3. Ignoring Google’s AI features: Many teams chase ChatGPT and forget how AI Overviews already shape clicks.
4. Relying on llms.txt or special markup alone: Google says its Search doesn’t use llms.txt files at all.
5. Measuring only traffic: Many AI answers are zero-click. Visibility and mentions matter just as much.
6. Letting facts go stale: Old pricing or outdated stats get your page skipped or, worse, quoted wrongly.

How can Contentpen help you win at AEO and GEO?

Running both playbooks by hand means juggling five or six tools. Contentpen puts research, writing, optimization, and AI tracking in one place.

Here’s how it maps to the work:

• Find the questions people ask: Keyword research and topic clusters surface the queries worth answering.
• See what ranking pages cover: SERP and content gap analysis show the angles competitors miss.
• Write answer-first content: The AI writer builds structured articles with key takeaways, FAQs, and question-based headings.
• Score as you write: Live SEO and GEO scoring flags gaps, and “Fix with AI” resolves SEO and GEO issues together.
• Track AI mentions: The AI visibility tool monitors ChatGPT, Google AI, Perplexity, Gemini, Copilot, Grok and Claude, with share of voice and source gaps.
• Publish in one click: Push to WordPress, Shopify, Wix and other CMSs, or let Autopilot handle the schedule.

Agencies can also export visibility reports as PDFs or share read-only links with clients.

Ready to stop guessing? Try Contentpen, the SEO AEO tool built for both search and AI answers.

One content system, two kinds of answers

AEO and GEO aren’t competing strategies. AEO makes your page the answer. GEO makes your brand part of the conversation.

Both stand on solid SEO. Both reward clear structure, real expertise, and fresh facts.

Start with answer-first pages, then widen your footprint across the web. Track AI visibility alongside rankings, and you’ll know exactly which half needs more work.

Frequently asked questions

Generative engine optimization (GEO) is the practice of shaping your content so AI tools like ChatGPT, Gemini, Perplexity, and Google’s AI Overviews find it, quote it, and cite it in their answers. Think of it as SEO for the answer, not just the link.

Here’s the problem. Your page can sit at the top of Google and still go unseen, because an AI summary above it already answered the question.

And it hurts more than it sounds. Ahrefs found that when an AI Overview appears, the top-ranking page gets 34.5% fewer clicks on average.

The good news? AI engines still need sources, and they lean on pages that are clear, specific, and trustworthy. This guide covers what GEO means, how it differs from SEO, what the research says works, and how to measure it.

Let’s start with the basics.

Key takeaways

• GEO means optimizing content so generative AI engines retrieve, summarize, and cite it.
• It builds on SEO. Google’s own 2026 guidance calls AI search optimization “still SEO.”
• In the original GEO study, adding quotes, statistics, and citations lifted visibility by up to 41%. Keyword stuffing made it worse.
• Success is measured in citations, mentions, and AI share of voice, not only rankings and clicks.
• Clear answers, real data, first-hand expertise and third-party mentions are your strongest levers.

What is generative engine optimization?

Generative engine optimization is the process of making your content easy for large language models (LLMs) to find, understand, and reference. The “engine” here is any tool that writes a response instead of just listing links.

That includes ChatGPT search, Google AI Overviews and AI Mode, Perplexity, Gemini, Microsoft Copilot, Claude and Grok.

In plain terms, GEO asks one question. When someone asks AI about your topic, does your brand show up in the answer?

You’ll also hear it called AI search optimization, LLM optimization (LLMO), or AI optimization (AIO). The labels differ, but the goal is the same.

Where did the term GEO come from?

The term took off after a 2023 research paper titled GEO: Generative Engine Optimization, by researchers from IIT Delhi and Princeton University. It was later presented at KDD 2024, a major data mining conference.

The team tested a set of content changes to see which ones made a source appear more in AI answers. Their headline finding was that the right changes can boost visibility by up to 40%.

We’ll get into exactly which changes worked a little further down.

How do generative engines pick which sources to cite?

Most AI search tools follow a similar three-step loop. Once you see it, every GEO tactic starts to make sense.

1. Retrieve: The engine runs one or more searches behind the scenes and pulls a shortlist of pages. Google calls this multi-search approach “query fan-out.”
2. Read and weigh: It scans those pages for passages that directly answer the prompt, and judges how trustworthy each source looks.
3. Generate and cite: The model writes an answer in its own words, then links the sources it leaned on most.

So what does that mean for you? You need to be found in step one, quotable in step two, and credible enough to be cited in step three.

Why does generative engine optimization matter in 2026?

Because search behavior has already shifted. People ask longer questions, and they accept the AI answer more often.

• Bain & Company found that about 80% of search users rely on AI summaries for at least 40% of their searches.
• The same research estimates that zero-click behavior could cut organic web traffic by 15% to 25%.
• Bain also found that about 60% of searches now end without a click to another site.

Now here’s the twist. Fewer clicks don’t mean less influence.

If an AI answer names your brand as the best option, that recommendation lands before anyone visits a website. For agencies and B2B brands, being left out of the answer is the new page two.

GEO vs SEO vs AEO: what’s the difference?

All three aim to make your content visible. They just target different places on the results page.

	SEO	AEO	GEO
Main goal	Rank pages in search results	Be the direct answer to a question	Be cited or mentioned in AI-written answers
Where you show up	Blue links on Google and Bing	Featured snippets, voice answers, AI Overviews	ChatGPT, Perplexity, Gemini, Copilot, AI Mode
Query style	Short keywords	Questions	Long, conversational prompts
Content focus	Relevance, links, technical health	Concise, well-structured answers	Evidence, clarity, authority across the web
Main metrics	Rankings, clicks, traffic	Snippet wins, answer presence	Citations, mentions, AI share of voice

See SEO vs GEO vs AEO for a side-by-side table

In practice, the lines blur. Many marketers use AEO and GEO as one discipline, and both sit on top of SEO.

Want a deeper side-by-side? Read our breakdown of AI search optimization vs traditional SEO.

Is GEO replacing SEO?

No. And Google says so directly.

In its guide to optimizing for generative AI features, Google states that “optimizing for generative AI search is optimizing for the search experience, and thus still SEO.” Its AI features run on the same core ranking and quality systems as regular search.

That tracks. A page that isn’t indexed can’t be retrieved, and a page that can’t be retrieved can’t be cited.

So think of GEO as a layer, not a replacement. Strong SEO gets you onto the shortlist. GEO helps you get picked from it.

Our GEO vs SEO guide covers what changes and what stays the same.

What did the original GEO research find?

Here’s where most guides stop short. The GEO paper didn’t just coin a term; it measured how specific edits changed a source’s presence in AI answers.

Tactic tested	What it means	Change in visibility vs baseline
Quotation addition	Adding relevant quotes from credible people	+41%
Statistics addition	Swapping vague claims for real numbers	+31%
Fluency optimization	Making text smoother and easier to read	+28%
Cite sources	Referencing credible sources in the text	+27%
Keyword stuffing	Repeating the target keyword more often	-8%

Source: Table 1 of Aggarwal et al., KDD 2024, position-adjusted word count. Percentages calculated against the paper’s baseline score of 19.3.

The lesson is hard to miss. AI engines reward evidence and clarity, while old keyword tricks actually backfire.

One caveat is worth knowing. The authors note that results vary by domain, so test what works in your niche.

How to do generative engine optimization: 8 strategies

Ready to put this into practice? These eight strategies map back to the research and to how AI engines pull content.

1. Lead with the answer

Open each page, and each section, with a one or two sentence answer. AI engines often lift a single passage, so make that passage stand on its own.

Then add context, examples, and nuance below it. Quick test: if someone read only the first two lines under a heading, would they get the answer?

Our guide on how to structure a blog walks through this in more detail.

2. Add statistics and quotes from real sources

Replace “most marketers agree” with a number and a source. Add a short quote from a named expert, a customer, or someone on your own team.

These were the two strongest tactics in the GEO study. Just never invent a figure, because AI engines and readers both punish shaky claims.

Here’s how to fact-check AI-generated content before it goes live.

3. Cite primary sources, not roundups

Link to the original study, documentation, or dataset, not a blog that summarized it. The shorter the trail, the more a claim gets trusted.

It also protects you from repeating numbers that were wrong to begin with. Learn more about how citations work in SEO.

4. Format for easy lifting

Use question-based headings, short paragraphs, bullet lists, and comparison tables. Add a key takeaways block near the top and an FAQ section at the end.

Structure doesn’t trick the model. It simply makes your best passages easy to find and quote. Our on-page SEO checklist covers the basics.

5. Show first-hand experience

Here’s the catch with generic content. AI can already write it, so it has little reason to cite yours.

Original data, screenshots, test results, and honest opinions give the engine something it can’t produce alone. A quick SERP and content gap analysis shows what everyone else already covers, so you know where your own insight adds something new.

Pair all of this with real author bios that show each writer’s actual role.

6. Get mentioned beyond your own site

AI answers lean heavily on comparisons, reviews, forums, and industry lists. Earn mentions on trade publications, review platforms, podcasts, and communities like Reddit.

Keep your brand description consistent everywhere, so models describe you accurately. One warning, though: Google’s guide treats fake or paid-for inauthentic mentions as a spam violation.

7. Keep pages fresh

On fast-moving topics, AI engines favor current information. Update stats, dates, pricing, and screenshots on your key pages on a set schedule.

Show a visible “last updated” date too. If a page is aging, a content refresh is often faster than writing something new.

8. Make sure AI crawlers can reach you

Check that your pages are indexable, and that robots.txt doesn’t block crawlers like Googlebot, Bingbot, OAI-SearchBot, or PerplexityBot. Keep important content in the HTML rather than hidden behind heavy JavaScript.

If a crawler can’t read the page, nothing else on this list matters. Brush up on technical SEO if you’re unsure where to start.

What does GEO look like in practice?

Let’s make this concrete. Say you run a project management tool and want AI to cite you for “how to run a sprint retrospective.”

Before:

Sprint retrospectives are very important for agile teams. There are many ways to run them, and every team is different. In this post, we’ll explore some ideas.

After:

A sprint retrospective works best as a 45-minute meeting built around three questions: what went well, what didn’t, and what we’ll change next sprint. Across [X] retros, our team cut repeat blockers by [Y]% after limiting each session to two action items with named owners.

What changed? Quite a lot, in very few words.

• The answer comes first, in one self-contained passage.
• Vague filler became a specific format and timeframe.
• A first-hand result (your real numbers go in the brackets) gives AI something only you can offer.

Need more inspiration? Browse these answer engine optimization examples.

How do you measure generative engine optimization?

Rankings alone won’t tell you much here. You need to track how often AI actually names and links you.

What to track	What it tells you	Where to find it
AI citations	How often your URLs are linked as sources in AI answers	Contentpen’s AI Visibility tool
Brand mentions	How often AI names you, with or without a link	Contentpen’s AI Visibility tool, or other AI visibility tools running a fixed prompt set
AI share of voice	Your mentions compared with competitors for the same prompts	Contentpen’s AI Visibility tool (what is share of voice?)
Accuracy and sentiment	Whether AI describes your brand correctly and positively	Manual review of answers
Google AI performance	Impressions and clicks from Google’s AI features	Search Console’s generative AI performance report
AI referral traffic	Visits from chatgpt.com, perplexity.ai and similar	The referral sources in your analytics tool

A practical way to start is to pick 20 to 50 prompts your buyers actually ask. Your keyword research, sales calls, and support tickets are good places to find them. Track them weekly and watch the trend, not any single answer.

Why the trend? AI responses can vary from one run to the next. An AI visibility audit gives you a clean baseline to compare against.

Which GEO myths can you safely ignore?

GEO has attracted plenty of hype. Google’s own guide and the GEO research put a few popular claims to rest.

• You need an llms.txt file: Google says its Search doesn’t use these files. They won’t hurt, but they won’t help your Google visibility either.
• Break every page into tiny chunks: Google says there’s no need, because its systems can find the relevant part of a page on their own.
• Special schema unlocks AI answers: No special markup is required for AI features. Keep using structured data for rich results.
• Repeat the keyword for the AI: Keyword stuffing scored below baseline in the GEO study.
• GEO is a one-time project: AI answers shift as models and sources change, so treat it as ongoing work.

How Contentpen helps you win AI citations

Doing all of this by hand across dozens of pages gets heavy fast. Contentpen is an all-in-one SEO and AEO tool that puts research, writing, GEO scoring and AI visibility tracking in one workspace.

Here’s how it maps to the strategies above:

• Live SEO and GEO scoring: score drafts as you write, then use Fix with AI to apply SEO and GEO fixes in one go.
• AI-ready structure: articles come with key takeaways, FAQs and a clean heading hierarchy, all part of Contentpen’s AI search optimization tool.
• AI Visibility tracking: monitor your prompts across up to seven engines, including ChatGPT, Google AI, Copilot, Gemini, Perplexity, Grok, and Claude, and compare your share of voice with competitors.
• Automated linking: add internal links and links to credible external sources without the manual hunt.
• Content refresh: SEO opportunities flag pages worth recovering, so you can update aging posts and keep them citable.
• One-click publishing: push articles to WordPress, Shopify, Wix, and other CMSs, or let SEO Autopilot handle the routine.

Want to see where your brand stands in AI answers today? Start your 7-day free trial of Contentpen and run your first AI visibility check.

GEO is SEO with a new finish line

Generative engine optimization is about earning a place inside the answer, not just a spot in the list below it. The foundations haven’t changed: be crawlable, be useful, and be trustworthy.

What has changed is the bar. Clear answers, real numbers, cited sources, and outside mentions now decide who gets quoted.

Start small. Pick your ten most important pages, rewrite their openings, add evidence, and track a handful of prompts. Then build from there.

Frequently asked questions

By default, there is no switch to turn off Google AI Overviews. However, there are certain ways in which you can bypass or “trick” Google’s AI features into not appearing on your screen.

Closing AI summaries is a choice that some people make to enjoy surfing the web without distractions. That said, as a business, we recommend keeping them on to ensure better AEO efforts.

In this post, we will learn how to turn off AI Overviews in Google search using 3 different methods. We will also cover a way to turn AI Overviews off on mobile.

So, let’s get started.

1. Use the ‘-AI’ tag while searching

The first method of removing AI Overviews from your search is to use the NOT (-) operator while typing in your query. This method was also mentioned by one of the members in the Google community.

Let’s say we want to search “how to cook rice” for organic results. We’ll add an “-AI” at the end of the query to avoid getting any AI Overviews in our response.

Instantly, we can see that our trick has worked and there are no AI Overviews present on our screen. Instead, we’ve got an article in the featured snippet, which Google thought covers the searcher’s intent the best.

2. Switch to Web results

Have you ever noticed search filters that appear right underneath your search bar? One of these filters is the “Web” filter that helps you remove the AI Overview panel completely.

Once you click on this filter, you’ll see only the organic listings for the typed query and no AI summaries at the top.

Unfortunately, you cannot set the “Web” filter by default, which means that you’ll have to manually set it every time you search.

Related read: Defining AI search optimization.

Also, when using this filter, YouTube previews and featured snippets won’t appear on your screen, as you’ve specifically requested Google to show only textual web links.

3. Add &udm=14 to URLs

‘&udm=14’ is a Google search parameter that forces the search engine to show results only with its “Web” filter mode. It is kind of like method 2, but a fancier way to turn off AI Overviews.

There are multiple ways to go about this:

i) Append ‘&udm=14’ at the end of each search URL manually

This one is pretty much straightforward but tedious. Every time you search, you go to the end of your generated URL and add &udm=14 at the end without a space. Tiresome, but works.

ii) Use the udm14.com website for search

The second way is to use the udm14.com website to search for something. It basically adds the ‘&udm=14’ search parameter to all your search URLs to turn off AI Overviews.

Proxy sites like this can read your search queries, so consider your comfort level before proceeding.

iii) Permanently add ‘&udm=14’ to your Google settings

Another way to turn off AI Overviews is to use your Google Chrome settings and add the ‘&udm=14’ parameter permanently to your searches. This way, you won’t have to go to proxy sites like udm14.com or compromise on your data privacy.

Go to chrome://settings/searchEngines on your Chrome browser.

Next to the ‘Site Search’ section, click the ‘Add’ button and enter the following details:

Name: Google Search

Shortcut: @web

URL: https://www.google.com/search?q=%s&udm=14

After you’re done adding the site search shortcut, make it default. 

Now, Google AI Overviews will be turned off by default the next time you search something up online. But, just like the “Web” filter, you will only see textual search results and no YouTube embeds or featured snippets.

How to turn off AI Overviews on mobile?

To turn off AI Overviews on Android or iPhone, follow the given steps:

Since mobile browsers don’t generally allow the addition of custom search engines as we did previously, we’ll use OpenSearch for this method. 

OpenSearch is basically a simple XML file that instructs your mobile browser to add the ‘&udm=14’ URL parameter to all your Google searches.

For Chrome on Android:

1. Visit TenBlueLinks.org.
2. Open a new tab on your browser and search for anything on Google (important).
3. Tap on the three-dot menu in the top right corner.
4. Choose “Settings”, then “Search engine”.
5. Select “Google Web” in the “Recently visited” section.

After this step is done, you’ll officially add the “Web” filter to all your searches on mobile, turning off Google AI Overviews.

Chrome will show “tenbluelinks.org” as the source where it got the instructions, but all your search queries will be sent directly to Google, not this website. So, your browsing data will be safe while you turn off AI Overviews with this method.

Repeat the same procedure for iPhone to turn off Google AI on Chrome browser.

However, keep in mind that this procedure won’t work on the Safari browser. For that, you’ll have to install a separate extension called CSE from the App Store and set the ‘&udm=14’ parameter accordingly in its settings.

You can also use the “Web” filter on iPhone while searching (as we did in method 2) to turn off AI Overviews.

Why turning off Google AI Overviews is not recommended for businesses

As a business, you need to know how your product or service is being mentioned in AI summaries above the organic results. 

In 2026, 68% of all Google searches end without a click (called zero-click searches). This means if you are not in AI Overviews, you risk not being seen at all.

Therefore, if you keep your AI Overviews on as a business, you’ll know the status of your business citation in AI answers. Only then would you be able to make the proper amends to your content through GEO or AEO (answer engine optimization) to boost your AI visibility.

That said, performing GEO or AEO work manually is a lot of hassle. You’ll have to ensure the answer-first formatting in your content, take care of statistical accuracy, not to mention strengthening semantic and authority signals, all by yourself.

This is where Contentpen supports your journey. The SEO AEO tool scores every draft for SEO and GEO as you write, and Fix with AI resolves issues in both, so your content is built to rank on SERPs and appear in AI summaries.

Once you’ve published some content, you can track your AI citations, share of voice, and brand sentiment in Google AI and other AI engines with the AI visibility tool, included in every plan, without switching tabs.

Summing it up

Learning how to turn off AI Overviews can be important for a lot of users to surf the Internet freely without getting burdened by AI summaries they never asked for.

In this post, we saw 3 ways to turn off Google AI Overviews:

1) adding the ‘-AI’ tag to your search,

2) using the “Web” filter, and

3) adding the ‘&udm=14’ search parameter to your URLs.

We also learned the technique to bypass AI Overviews on mobile devices. However, the method for iPhones can be a bit more complicated than Androids.

Finally, we learned why not to turn off AI Overviews as a business and saw how you can use tools like Contentpen to help you improve your AI visibility.

Frequently asked questions

Google’s AI Overviews are an organic search results page feature that provides AI summaries in response to a user’s query. They appear at the very top of the results page, often recognized as “position zero.”

As of 2026, this summary can handle complex multi-part questions and work across text, voice, and image searches.

This guide explains what Google AI Overview is, how it works, and how it affects organic traffic. It also provides practical, step-by-step advice on how to appear in these overviews and how to improve your brand visibility.

So, let’s get started.

Key takeaways

• AI Overviews typically appear at the top of search results when a user types in a query on Google
• AI Overviews now reach more than 200 countries and over 40 languages. They can fill around 67% of the desktop screen and 76% of a mobile screen when appearing together with featured snippets
• Public reporting suggests only a very small share of users click the source links shown inside an AI Overview. Many searchers read the summary and stop there, especially for informational intent queries
• One widely cited study by Yahoo found that Quora and Reddit are the most frequent sources inside AI Overviews (as of 2025). This trend shows that AI rewards clear, answer-first content

What are Google AI Overviews?

AI Overviews are a type of highly visible search feature from Google that provides answers to certain queries.

These AI summaries mostly work for informational queries, although Google has now expanded this feature to commercial, transactional, navigational, and even branded queries.

For example, if you type in Google “how to eat healthy,” it will automatically generate an answer for you like this:

How do Google AI Overviews and Google AI mode work together?

Since January 2026, Google has incorporated its chatbot-style AI, called AI mode, inside Google AI Overviews. 

You can seamlessly transition to AI mode by clicking the ‘Show more’ button at the end of an AI Overview.

To understand the way these two AI features work, you need to see some differences:

• AI Overviews: These are static text snapshots that appear directly at the top of standard search results for straightforward queries. Overviews synthesize indexed data from different sites to give you a quick summary. 
• AI Mode: This is a dedicated, interactive, and conversational search interface designed for multi-part, complex tasks. It allows users to ask continuous follow-up questions to satisfy the searcher’s intent.

According to Google’s guide to search AI features, both AI Overviews and AI Mode use a specialized version of the Gemini models.

Both AI features also use the query fan-out process to break down the user’s question into small subparts.

For example, we asked Google’s AI Mode, “How to cut down sugar as a diabetic person who is in their 50s?”

This question essentially had 3 main parts to it. 

1. The user is asking to cut down on sugar levels
2. The user is diabetic
3. The user is in their 50s

If you look closely, AI Mode included four subparts in its response: cutting down on liquid sugars, portioning food, reading grocery labels, and improving exercise. 

The last bit is particularly included to cover the requirements of a mature-age person. This shows the query fan-out process being implemented by AI in real time.

Do AI Overviews answer the same every time?

Short answer: No. The reason behind this is the nature of the operation of AI features.

The large language model builds a mental map of key facts, definitions, and steps, then writes a new answer that blends those pieces. This process is similar to the multi-step retrieval and reasoning workflows described in research on agentic AI frameworks and applications. 

Since data is being taken from each node on the RAG (retrieval-augmented generation) system probabilistically, the chances are that you’ll see a different answer every time you type a query.

But that doesn’t necessarily mean you’ll get a “wrong” answer. It just means that your answer can vary in phrasing or nuance depth.

AI Overview vs featured snippet: What is the difference?

AI Overview and featured snippets both appear at the top of Google Search, but they work in different ways. 

A featured snippet is a direct excerpt from a single page that best matches the user’s query. An AI Overview is a fresh answer written by the model using several pages at once. 

Both can appear together on one results page, although AI Overviews have greatly reduced featured snippets in 2026.

Also read: How to turn off AI Overviews.

Here is a quick comparison table to help you understand the differences between them.

Element	Featured snippet	AI Overview
Source style	Exact excerpt from one page	New summary built from many pages
Format	One block of text or a simple list	Multi-paragraph answer, often with follow-up prompts
Placement	Usually, the top organic spot	Above organic results, sometimes with its own background
Screen share	Takes up some space on the first screen	With snippets, it can reach a large share of desktop and mobile screen area (67% and 76%, respectively)

Where and how can you see AI Overviews in Google Search?

AI Overviews appear for many informational searches in supported countries and languages whenever Google thinks a summary will help. 

The feature now reaches more than 200 countries and territories in over 40 languages. France was one of the last major markets to get it: Google launched AI Overviews and AI Mode there on July 22, 2026, after a delay it attributed to “regulatory obstacles.”

Why am I not getting AI Overview on Google consistently?

In most supported regions, the feature is on by default, so the main reasons for not seeing it can relate to the account, app, or query type. 

If your Google app or Chrome browser is out of date, the AI layer may not appear consistently, so updating them is a useful first step.

Next, make sure you are logged into a regular Google account and have language settings that match a supported language such as English, Spanish, or Japanese. 

Lastly, the appearance of Google AI Overviews also depends on the query asked.

For simple product searches like exact model numbers or clear transactional searches such as “buy running shoes near me,” Google often skips AI Overviews and shows shopping blocks or nearby business cards instead.

What about AI Overviews in Gmail and other Google products?

Gmail does have AI tools that summarize long email threads and suggest replies, powered by Google’s Gemini models, but those are separate from the Search AI Overview feature. 

The similar naming confuses a lot of people because both use phrases like AI summary or AI overview in product screens and help pages.

The same pattern shows up in Docs, Drive, and YouTube, where generative tools add summaries or outlines on top of existing content. 

While these tools share technology and branding with AI Overview in Google Search, they have separate settings and rollout plans. 

How do AI Overviews impact SEO and website traffic?

AI Overviews impact SEO and website traffic by sitting above classic organic rankings and often answering the query without a click, also known as zero-click search. 

This means brands that are not appearing in AI Overviews risk not being seen at all by users online.

Secondly, AI Overviews cover a large portion of your screen when appearing with featured snippets. For desktops, that is 67% of your screen and 76% for mobile screens. This leaves a little wiggle room for organic blue links to fight for users’ attention.

SEO specialists now have to think about traditional SEO and AI Overview optimization, not just classic ranking factors.

This shift also changes how brands plan content around the funnel. 

Top-of-funnel questions, definitions, and basic HowTos are more likely to appear in Google AI Overviews. 

Mid- and bottom-of-funnel queries with strong local or transactional intent, such as “best dentist near me” or “pricing for content marketing software”, still tend to send more clicks to websites. 

Marketers now watch not only ranking positions but also whether a query shows an AI Overview and how their brand appears, if at all, inside that box.

What do publishers and regulators have to say about AI Overviews?

The traffic impact from AI Overviews appears in both reported data and courtroom claims. 

Penske Media, the publisher behind Rolling Stone and The Hollywood Reporter, has alleged that a notable share of searches that could lead to its sites now display an AI Overview above organic results.

Penske Media has claimed that this has harmed its visits and ad income. 

In response, Google has replied in public statements that AI Overviews send traffic to a wider variety of sites and help smaller sources get attention. However, that view is still widely contested in 2026.

Legal action in Europe adds another angle. A Munich regional court ruled that AI Overviews make independent, new, and substantive statements rather than simply reflecting third-party content.

This means Google may carry more direct responsibility for content accuracy than it has pledged otherwise.

Together, these disputes show that the impact of AI Overviews on SEO and traffic is real enough for large publishers and regulators to treat it as a serious business and policy issue.

How to optimize your content to rank and appear in AI Overviews

Optimizing content to appear in AI Overviews means shaping pages so Google’s models can easily understand, trust, and reuse them. 

The goal is not to “game” the system, but to match how the AI reads structure, intent, and clarity.

This newer practice often goes by the name generative engine optimization, GEO, or AEO, and it sits alongside classic SEO work and technical health.

To adapt your content:

• Focus on search intent, which is the real problem behind each query, and build content that directly solves that problem in the first few lines. Expand with examples, personal experience, and other sections later.
• Use clear headings that mirror how people phrase questions, including spoken questions. Searches made by voice or with conversational phrasing tend to be longer.
• Add FAQ sections and simple step lists where they make sense, because both formats map well to the way language models break content into chunks.
• Keep facts up to date and well-sourced. Unclear or outdated claims are more likely to be twisted or misquoted when the AI writes its own summary.

Writing content in an “answer-first” format with good structure does help. But what’s most important to appear in AI Overviews and improve brand visibility is to speak with authority.

That means avoiding fluff and adding real depth to the content with anecdotes, real-life examples, case studies (personal or professional), or any other way to add value to readers.

Such content is most likely to be cited by AI engines, regardless of whether it’s AI-generated or not.

Since Quora and Reddit show up often in the AI cards, brands should treat community presence as part of their AI Overview optimization plan.

Try to provide helpful answers on these platforms that can signal trust to Google’s systems with accurate data.

How Contentpen helps you build AI Overview-ready content

Contentpen is an AEO tool that helps teams produce AI Overview-ready content by guiding every stage from idea to published post, then tracking whether AI engines cite it.

The platform starts with intent-based keyword research, so each article is tied to real questions people ask across Google, Gemini, and other AI assistants.

Once a topic is chosen, Contentpen generates detailed outlines for it with answer-first intros, strong headings, and FAQs, which line up well with how AI Overviews select and organize information.

During writing, the tool gives both SEO and GEO scores, pointing out where a draft may confuse readers or AI systems. Fix with AI resolves issues in both scores in one pass, helping writers create clear section openers, consistent terminology, and factual content.

Once the content is ready, you can publish it with one-click publishing or schedule it for later with the content planner.

The tool also provides web analytics and the new, improved SEO opportunities that help you identify and fix CTR gaps, cannibalization issues, content decay, and more for published content.

Contentpen’s AI visibility tool also allows businesses to monitor their AI SOV, audit brand visibility and sentiment, and view exact citation source gaps from competitors.

Final thoughts

Google AI Overviews are now a regular part of search in 2026, not a short-term test you can ignore. They sit above traditional results, take a large area above the fold on many devices, and often answer a query without sending a click anywhere. 

That new layer of search reshapes how people discover brands and how content teams should plan topics.

AI visibility now depends on being citation-worthy inside AI answers as well as ranking on the classic results page. Clear structure, answer-first paragraphs, accurate facts, and steady topic authority give your pages a better shot at being selected than otherwise.

Tools such as Contentpen make that work easier by creating SEO- and GEO-optimized blogs every time and tracking whether AI Overviews cite them, so you can earn mentions in AI answers while sustaining your SERP rankings.

Frequently asked questions