# AEO Vs GEO Vs SEO: What Changes in Practice?

AEO and GEO are SEO with a different scoreboard. See how retrieval differs from indexing, which technical base all three share, and what changes in content, measurement and reporting.

Search teams adding AI answers to an SEO programme face one practical question. Is this new work, or the same work measured differently? The answer below comes first, then the mechanics, the evidence and a tool map.

- AEO and GEO are SEO with a different scoreboard, not separate stacks to build from scratch.
- All three rely on crawlable, indexable pages, and Google says AI features need no special optimization.
- What changes is the unit of success, from a ranked page to a cited passage or brand mention.
- Rankings still help, yet a 2026 Conductor study found most AI Overview citations come from outside the top 10.
- Measurement changes most, since clicks drop when AI summaries appear and Search Console has no AI split.

This applies to teams whose buyers research in Google, ChatGPT, Copilot or Perplexity and who already have, or are building, an organic search base. Citation studies disagree with each other by sample, date and counting method, so treat any single overlap figure as a range indicator, not a rule.

## What Is The Difference Between AEO, GEO And SEO?

SEO earns a ranked link in search results, AEO earns the direct answer, and GEO earns a mention or citation inside an AI-generated response, a term coined in [the arXiv paper Generative Engine Optimization by Aggarwal and colleagues](https://arxiv.org/abs/2311.09735). In practice, AEO and GEO are SEO with a different scoreboard, not separate stacks to build.

**SEO, AEO and GEO side by side**

| Dimension | SEO | AEO | GEO |
| --- | --- | --- | --- |
| Goal | Rank a page | Become the direct answer | Get cited or mentioned |
| Where it shows | Organic results | Answer boxes, AI Overviews | ChatGPT, Copilot, Perplexity, AI Mode |
| Unit of success | Ranked URL | Extracted answer passage | Citation or brand mention |
| Main metric | Rankings and clicks | Answers won, citations | Mentions, citations, share of voice |
| Main data source | Search Console | Search Console, prompt tracking | Prompt tracking, Bing AI Performance |

The three terms describe one discipline aimed at three surfaces. SEO is the established discipline, and its scoreboard is the ranked blue link. AEO, answer engine optimization, is the older answer-box term, built around answers that lift one passage from one page.

GEO is the newest label, and it comes from research, not from an agency deck. The paper by Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande (version 3 dated June 28, 2024) named the practice and tested it on a benchmark of its own, GEO-bench.

The line between AEO and GEO is blurry, and the work behind both is the same. Both are judged by whether an AI-written answer uses your page or names your brand. Google Search Central says there are no special optimizations needed to appear in AI Overviews or AI Mode, and that fundamental SEO best practices still apply.

So the working judgement in this post is simple. The crawling, indexing and content quality work of SEO stays. What gets added is a new unit of success and new ways to measure it.

This post sits within our [AI search visibility](https://growthtribune.com/search-ai-visibility/ai-search-visibility/) coverage. Readers who want the definition first can start with [what AI search visibility means](https://growthtribune.com/what-is-ai-search-visibility/) and come back for the practice.

## Retrieval Versus Indexing In AI Search

Google's AI Overviews and AI Mode can run a [query fan-out, issuing multiple related searches across subtopics](https://developers.google.com/search/docs/appearance/ai-features) and pulling supporting pages while the answer is generated, so a page is retrieved for the sub-question it answers, not only for the head keyword. Indexing decides whether a page can be found, and retrieval decides which indexed pages an answer uses.

Classic SEO is mostly an indexing and ranking problem. A crawler fetches a page, the engine indexes it, and the ranking system orders it against other pages for a query. The searcher then picks a link.

AI answers add a retrieval step at the moment of the question. The engine searches its own index, often more than once, picks the passages that fit and writes an answer that cites some of them.

> **Retrieval:** The step where an AI search engine queries its index at answer time and selects the pages or passages it will use and cite in a generated response.

Google, OpenAI and Microsoft each document this pattern in their own words:

- **Google:** AI Overviews and AI Mode may search across subtopics and data sources, and they show a wider set of links than classic web search. A page qualifies as a supporting link only when it is indexed and eligible to show in Google Search with a snippet.
- **OpenAI:** ChatGPT search surfaces websites through OAI-SearchBot, its search crawler. GPTBot is a separate crawler that collects content to improve OpenAI's foundation models, and ChatGPT-User handles actions a user starts, not automatic crawling.
- **Microsoft:** Bing Webmaster Tools reports grounding queries in its AI Performance report, alongside citations across Microsoft Copilot and AI-generated summaries in Bing.

> **Grounding:** Tying a generated answer to sources retrieved at answer time, so the model writes from pages it found for the question rather than only from what it learned in training.

The practical consequence is that a page is no longer judged only against its head keyword. A fan-out answer about AEO vs GEO vs SEO may also search for how each is measured, which tools help and whether rankings still matter. A page that answers those sub-questions in clear, self-contained passages gives retrieval more to pick from.

Indexing is still the gate. A page that is not indexed cannot be a supporting link in Google's AI features. A site that opts out of OAI-SearchBot will not be shown in ChatGPT search answers, though it can still appear as a navigational link.

Retrieval is a new filter on top of that gate, not a replacement for it. Each engine retrieves from its own search index, which is why the crawl access in the next section comes first.

## What Technical Foundations Do SEO, AEO And GEO Share?

Google states that there are no additional requirements to appear in AI Overviews or AI Mode, so the technical base for AEO and GEO is the same crawlable, indexable, snippet-eligible page that SEO already needs. Each engine's search crawler must reach the page, and the page must be indexed and allowed to show a snippet.

The shared base, item by item:

- [ ] Allow Googlebot, Bingbot and OAI-SearchBot in robots.txt, so each engine's search crawler can reach the page
- [ ] Keep key pages indexable, with no stray noindex tag
- [ ] Keep pages eligible to show in Google Search with a snippet, the condition for being a supporting link in AI features
- [ ] Review nosnippet, data-nosnippet and max-snippet, because the same Search controls limit what AI features show from a page
- [ ] Decide on GPTBot and Google-Extended separately from the search crawlers
- [ ] Serve clean HTML with the main content in the page source, real headings and one topic per section
- [ ] Check crawl, index and serving status for key pages in Search Console URL Inspection

Blocking a training crawler and blocking a search crawler are two different decisions. OpenAI documents GPTBot as the crawler for improving its foundation models, and disallowing it indicates that content should not be used in training. OAI-SearchBot is the crawler that surfaces sites in ChatGPT search.

A publisher can say no to the first and yes to the second. A blanket block on every OpenAI agent removes a site from ChatGPT search answers as well as from training. Google-Extended works on the same principle, governing use in training and grounding for some of Google's other systems.

The same logic is the test for vendors selling "GEO-specific" technical fixes. Google says no special optimizations are necessary for AI Overviews or AI Mode, and that fundamental SEO best practices still apply.

A fix that only matters for AI answers should come with platform documentation behind it. If it does not, it is usually standard technical SEO under a new name, and it belongs in the existing SEO backlog.

## Does Ranking In Google Still Get You Cited In AI Answers?

Conductor's study of 167,867,680 US AI Overview citations from June 15 to August 15, 2026 found that [57% of AI Overview citations go to pages outside the organic top 10](https://www.conductor.com/academy/aio-vs-organic-rankings/), so a top-10 ranking helps but no longer predicts a citation. An earlier, smaller Ahrefs study pointed the other way, and the gap comes down to method.

**57%** (June 15 to August 15, 2026, 167,867,680 US AI Overview citations): The share of US AI Overview citations that pointed to pages outside the organic top 10 in Conductor's dataset, counting every citation in each answer. Source: [57% of AIO Citations Come From Outside Organic Top 10](https://www.conductor.com/academy/aio-vs-organic-rankings/).

In July 2025, Ahrefs (analysis by Louise Linehan) found that [76.10% of AI Overview-cited pages rank in Google's top 10](https://ahrefs.com/blog/search-rankings-ai-citations), with 9.50% ranking 11 to 100 and 14.40% not ranking at all. That sample was 1.9 million citations across 1 million AI Overviews, and it counted only the top three citations in each response.

**Two citation-overlap studies side by side**

| Study detail | Ahrefs | Conductor |
| --- | --- | --- |
| Owner | SEO software vendor | AI visibility software vendor |
| Period | Published July 2025 | June 15 to August 15, 2026 |
| Sample | 1.9M citations, 1M AI Overviews | 167.9M US citations |
| Citations counted | Top three per answer | All citations |
| Headline finding | 76.10% from top 10 | 57% outside top 10 |

Both numbers come from software vendors with a stake in the answer, Ahrefs as an SEO tool company and Conductor as an AI visibility platform. Neither is independent research, and the two should never be merged into one figure. Three method choices explain most of the gap:

- **Counting method:** Ahrefs counted only the top three citations per answer. Conductor counted every citation in each answer.
- **Date:** The studies sit about a year apart, so they describe different versions of the same product.
- **Sample size:** Conductor's dataset is roughly 88 times larger than Ahrefs' in citations counted.

Read together, the two studies give a trend, not a rule. Rankings still help, and a top-10 page is a strong candidate for a citation.

The newer, larger dataset shows a bigger share of citations going to pages beyond the top 10. That is consistent with query fan-out, which pulls in pages for sub-questions the head keyword never ranked for. Treat any single overlap figure as a range indicator, and plan for both rankings and passage-level coverage.

## What Changes In Practice For Content, Measurement And Reporting?

Pew Research Center found that Google users who saw an AI summary [clicked a traditional result in 8% of visits, against 15% without one](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/), which is why AEO and GEO need a citation and mention metric of their own instead of borrowing SEO's click count. Content shifts from pages to passages, and reporting adds a citation line.

**What changes in practice**

| Area | SEO | AEO And GEO |
| --- | --- | --- |
| Unit of work | Page and keyword | Passage and entity |
| Success metric | Rankings and clicks | Mentions and citations |
| Data source | Search Console | Prompt tracking, Bing AI Performance |
| Reporting basis | Rank checks, traffic trends | Sampled prompt panels |
| Who owns it | SEO lead | SEO and content leads together |

### Content Moves From Pages To Passages

SEO content is planned around a page and its keyword. AEO and GEO content is planned around the sub-questions an answer engine fans out to. The page stays, and the writing inside it changes.

Each passage should make sense when quoted on its own. In practice that means three habits:

- Open each section with the answer to one sub-question, then give the reasoning.
- Name the product, company or standard instead of writing "it" or "the platform".
- Keep the unit and the owner on every number, so a quoted passage carries its own evidence.

### Measurement Needs A Citation Metric

Clicks fall when an AI summary appears. In the same Pew Research Center study of 900 US adults' browsing data in 2025, a link inside the summary itself was clicked in 1% of visits, and 18% of the searches produced an AI summary. A team that judges AI visibility by clicks alone will under-count it.

Search Console does not separate the two. Google reports appearances in AI features inside overall search traffic, in the Performance report under the Web search type, with no separate AI Overview or AI Mode report.

Bing has gone further. Its AI Performance report in Bing Webmaster Tools, a public preview launched on February 10, 2026, shows total citations, average cited pages, grounding queries, page-level citation activity and visibility trends across Microsoft Copilot, AI-generated summaries in Bing and select partner integrations. It reports citation activity, not clicks.

For Google's AI answers, ChatGPT and Perplexity, that leaves prompt tracking. A tracker runs a set list of prompts on a schedule and records whether your brand is mentioned or your pages are cited. The workflow to [measure AI visibility without double-counting](https://growthtribune.com/how-to-measure-ai-visibility-without-double-counting/) keeps one row per answer and keeps Search Console data apart.

### Reporting Treats Prompt Panels As Samples

Prompt panels are samples, not demand. Semrush documents that its Brand Performance reports use synthetic prompts generated from the domain and location, not real user queries, and that they update weekly.

That makes a panel useful for trend lines and competitor share, and misleading if presented as how many people asked a question. Report it with its prompt count and engines named, next to Search Console traffic and never merged with it. Choosing the prompts well matters as much as the tool, which is the job of an [AI search prompt tracking list](https://growthtribune.com/how-to-build-an-ai-search-prompt-tracking-list/).

A reporting pack that holds up in a leadership review has three separate lines:

- Search Console clicks and impressions, as the SEO baseline.
- Citation and mention share from a prompt panel, labelled as a sample.
- Bing AI Performance citations, where Copilot matters to your buyers.

## What Do Practitioners And Researchers Actually Claim?

Google's Danny Sullivan told WordCamp US that [good SEO is good GEO, or AEO](https://searchengineland.com/google-danny-sullivan-good-seo-good-geo-461464), an on-record view from the platform itself, while the academic GEO paper reports gains of up to 40% only on its own benchmark, GEO-bench. Neither is a measurement of live AI engines, so each needs its label.

Each view below carries its owner, so opinion and observed data stay apart.

### Opinion From The Platform

> Good SEO is good GEO, or AEO, AIO, LLM SEO, or LMNOPO.
>
> — Danny Sullivan, WordCamp US keynote speaker, Google. Source: [Google's Danny Sullivan: 'Good SEO is good GEO'](https://searchengineland.com/google-danny-sullivan-good-seo-good-geo-461464).

Sullivan made the point in his WordCamp US keynote on August 28, as reported by Search Engine Land, adding "don't panic. What you've been doing for search engines generally... is still perfectly fine." On a podcast reported by Search Engine Journal on December 18, 2025, he said "just because the formats are changing didn't mean you have to change everything that you had to do".

Read this as the platform's stated position. Google has an interest in how publishers respond to its AI features, so Sullivan's view is an informed opinion from an interested party, not a measurement. It does agree with Google's own documentation, which sets no additional requirements for AI features.

### Research Finding From The GEO Paper

The GEO paper by Aggarwal and colleagues reports that GEO methods can boost visibility in generative engine responses by up to 40%. That figure comes from GEO-bench, the paper's own benchmark, run under controlled conditions.

It is a lab result, not a measurement of ChatGPT, AI Overviews or any other live engine. Quoting it as an expected uplift for a real site stretches it past what the paper tested.

### Observed Market Data

The observed data sits in the sections above. The Ahrefs and Conductor citation studies are datasets owned by software vendors, and the Pew Research Center click study is independent research. Those are the numbers to plan from, read with their owners, dates and methods attached.

> **Warning:** Agency "time to impact" figures and uplift percentages are service claims unless a named dataset backs them. Ask for the sample, the dates and who owns the data before putting any such figure in a plan.

## Which Tools Cover SEO, AEO And GEO Work?

The five tools cover different layers, so a working stack pairs a search data source such as Google Search Console with a prompt-based AI tracker and a crawler, and adds a content operations platform only when refresh volume justifies it. The table maps each of the five tools to its layer of work.

**Which layer each tool covers**

| Tool | Layer | What It Shows | Main Limitation |
| --- | --- | --- | --- |
| Google Search Console | SEO baseline | Google queries, clicks, indexing | No AI Overview split |
| Semrush | SEO plus AI tracking | Rankings and prompt-based AI visibility | Synthetic prompts, not demand |
| Profound | AEO and GEO monitoring | AI answers and crawler visits | Needs CDN or log integration |
| Screaming Frog | Technical crawl | Page elements, LLM prompts, embeddings | Shows pages, not citations |
| AirOps | Content operations | Share of voice, page updates | Heavier than a tracker |

These are layers, not rival products, so the right question is which layers a team is missing. For a deeper look at trackers on engine coverage and answer evidence, see the [AI visibility platforms compared](https://growthtribune.com/best-ai-visibility-platforms/) side by side.

### Google Search Console

Google Search Console is Google's own record of how a site performs on Google Search, and a baseline for reading AI visibility numbers.

**Layer of work:** SEO and index health. URL Inspection gives crawl, index and serving information directly from the Google index, and index coverage shows whether Google has the freshest view of the site.

**What it shows:** The Performance report shows queries, impressions, clicks and position on Google Search, with appearances in AI Overviews and AI Mode counted inside the Web search type.

**Limitation:** There is no separate AI Overview or AI Mode report, so Google Search Console cannot say how much traffic came from AI features. It covers Google Search only.

**Best fit:** Every team, as the SEO baseline, and the first tool for a site that does not rank yet. Not a fit as the only source for AI visibility.

### Semrush

Semrush puts SEO data and prompt-based AI tracking in one suite.

**Layer of work:** SEO plus AEO and GEO tracking. Semrush tracks ChatGPT, Gemini and Google AI Mode in Visibility Overview, Competitor Research, Prompt Research and Position Tracking. It tracks Google AI Overviews in Visibility Overview, Position Tracking and Organic Rankings, and Perplexity in Brand Performance only.

**What it shows:** Rankings next to AI visibility, plus a Site Audit check for whether a site blocks AI bots such as ChatGPT-User, PerplexityBot and Claude-SearchBot. Competitor Research compares up to four competitors at once, and the AI Traffic dashboard estimates ChatGPT and Gemini referral traffic from clickstream data.

**What drives the cost:** The daily AI prompt allowance is the main AI cost driver by plan, with Starter tracking 50 AI prompts daily, Pro+ 100 and Advanced unlimited, alongside the websites and keywords tracked. Tracking on AI platforms needs Semrush One or the AI Visibility Toolkit, and each additional user is a paid add-on.

**Semrush pricing**

| Plan | Price | Billing | Notes |
| --- | --- | --- | --- |
| Free | $0 | per month |  |
| SEO | $139.95 | per month |  |
| Starter | $199 | per month |  |
| Pro+ | $299 | per month |  |
| Advanced | $549 | per month |  |
| AI Visibility Toolkit (AI Visibility Toolkit) | $99 | per month | per user |

**Limitation:** Brand Performance runs synthetic prompts generated from the domain and location, not real user queries, and its reports update weekly while Position Tracking monitors daily. Perplexity appears in Brand Performance only.

**Best fit:** Teams with strong rankings that want AI visibility in the same suite as their SEO data, and that will report prompt results as a sampled panel. Not the right first buy for a site that does not rank yet.

### Profound

Profound is built for answer-engine monitoring and AI crawler analytics.

**Layer of work:** AEO and GEO monitoring. Profound groups its product into Monitor (Answer Engine Insights, Prompt Volumes, Shopping, Agent Analytics) and AI Marketer (Agents, Context Manager). It lists ChatGPT, Perplexity, Claude, Gemini, Microsoft Copilot, DeepSeek and Google AI Overviews among the engines it covers.

**What it shows:** How a brand appears in AI answers, plus Agent Analytics, which identifies and classifies AI crawlers from OpenAI, Anthropic, Google, Perplexity, Microsoft, Apple, Meta and DeepSeek, with crawl patterns, frequency and page-level access.

**Profound pricing**

| Plan | Price | Billing | Notes |
| --- | --- | --- | --- |
| Agency Enterprise (agency tab) | Custom pricing | per custom |  |
| Agency Growth (agency tab) | Custom pricing | per custom |  |
| Enterprise | Custom pricing | per custom |  |
| Trial | Custom pricing | per custom |  |

**Limitation:** Agent Analytics collects its data through a CDN integration, the recommended route, or a server integration with log ingestion. AWS S3 and Azure CDN integrations are announced on Profound's roadmap and are not available.

**Best fit:** Teams with strong rankings but weak AI presence that want engines beyond Google tracked and a view of which AI crawlers reach which pages. Not a fit for a team that only needs Google data.

### Screaming Frog

Screaming Frog is the technical crawl foundation, with LLM prompts and embeddings run during a crawl.

**Layer of work:** Technical SEO, the crawlable and indexable base all three disciplines share. The SEO Spider connects to OpenAI, Gemini, Anthropic and Ollama APIs to run custom prompts against page elements while crawling and to extract embeddings.

**What it shows:** Crawl data with AI analysis on top. Version 23.0, released October 20, 2025, added semantic similarity embedding rules and inlinks in the semantic content cluster diagram, and updated the default AI models for OpenAI, Gemini and Anthropic prompts.

**What drives the cost:** Paid LLMs need the user's own API key and are billed by the provider, so the cost of AI analysis grows with the pages and prompts a team runs. Ollama runs local models without an API key.

**Screaming Frog pricing**

| Plan | Price | Billing | Notes |
| --- | --- | --- | --- |
| Paid version, 20+ licences | $235 | per year | per user |
| Paid version, 10 to 19 licences | $249 | per year | per user |
| Paid version, 5 to 9 licences | $265 | per year | per user |
| Paid version, 1 to 4 licences | $279 | per year | per user |

**Limitation:** Screaming Frog shows what a page contains, not whether any AI engine cites it. Prompt and embedding results are only as useful as the prompts a team writes.

**Best fit:** Technical SEO leads who want to audit crawlability and passage structure at scale, such as checking whether each section answers one sub-question. Not a fit as a citation tracker.

### AirOps

AirOps is a content operations platform for publishing and refreshing pages for AI search.

**Layer of work:** Content operations. AirOps positions itself as a platform plus a team that runs an AI discovery strategy, with a continuous system to research, publish and refresh content and a market-share view of where a brand stands with target buyers.

**What it shows:** Visibility, recommendations, citations, sentiment and position, with share of voice broken down by model, audience, region, topic, buying stage, competitor and source. Its Content Updates log records every page created, refreshed or published, and drafts can be scored for readability, claim support, SEO and AEO before publishing through CMS integrations.

**AirOps pricing**

| Plan | Price | Billing | Notes |
| --- | --- | --- | --- |
| Enterprise | Custom pricing | per custom |  |
| Pro | Custom pricing | per custom |  |
| Solo | Custom pricing | per custom |  |

**Limitation:** AirOps is a content system, not a light tracker, and it pays back only when there is a real volume of pages to create or refresh. A small site will use a fraction of it.

**Best fit:** Teams with a large content library to refresh for AI search that want tracking and publishing in one loop. Not a fit for a team that only needs to measure citations.

## Should You Prioritize SEO, AEO Or GEO?

If a site does not yet rank, SEO comes first because Google's AI features only cite pages that are indexed and eligible to be shown with a snippet; once rankings exist, AEO and GEO add the citation tracking that rankings alone no longer explain. The order matters more than the label.

The reason is the shared gate. Google's AI features retrieve from the same index that classic search uses, and Google sets no additional requirements beyond fundamental SEO best practices. A page that is not indexed cannot be a supporting link in an AI answer, however well its passages are written. For a site with no organic base, AEO and GEO work has nothing to act on yet.

Once pages are indexed and ranking, the question changes. Rankings still feed citations, yet they no longer explain all of them, because fan-out answers pull in pages for sub-questions the head keyword never covered. That is the point where passage-level writing and a citation metric start to pay back.

**Verdict.** SEO first, then AEO and GEO on top of it. The technical base is shared, so nothing built for SEO is wasted. What AEO and GEO add is passage-level writing and a citation metric, and those pay off once a site has pages that can be retrieved.

Pick the next step by situation:

- **No organic base yet:** Start with SEO. Google's AI features use only indexed, snippet-eligible pages, and Ahrefs' 2025 data found most AI Overview citations came from top-10 pages. Pair Google Search Console with Screaming Frog to get crawl access and indexing right first. Passage-level rewrites can wait until key pages are indexed and eligible for a snippet.
- **Strong rankings, weak AI presence:** Add AEO and GEO measurement. Conductor's 2026 data puts 57% of AI Overview citations outside the top 10, so rankings alone no longer explain who gets cited. Track a prompt panel against the pages that already rank, and rewrite sections of ranking pages that are never cited so each opens with a quotable answer. Choose Semrush to keep SEO and AI tracking in one suite, or Profound for a wider published engine list and AI crawler analytics.
- **Traffic falling while impressions hold:** Report citations as their own line. In Pew Research Center's study, clicks on traditional results fell from 15% to 8% of visits when an AI summary appeared, so lost clicks can hide visibility that is still there. A falling click line on its own is not proof that a page lost its place in search or in AI answers.
- **Large content library to refresh:** Add AirOps once the volume of pages to create or refresh justifies a content operations platform.

## Frequently Asked Questions

**Can I block AI training but still appear in ChatGPT search?**

Yes, a site can block OpenAI's GPTBot from training while allowing OAI-SearchBot, because OpenAI documents the two crawlers separately and only OAI-SearchBot decides whether a site appears in ChatGPT search answers. Disallow GPTBot in robots.txt and leave OAI-SearchBot allowed. Sites opted out of OAI-SearchBot can still appear as navigational links.

**Does Search Console show AI Overview traffic separately?**

No. Google reports appearances in AI Overviews and AI Mode inside overall search traffic, in the Search Console Performance report under the Web search type, with no separate AI report. To see AI exposure, pair Search Console with a prompt tracker or Bing Webmaster Tools AI Performance, which reports citations and grounding queries.

**Do I need separate content for AEO and GEO?**

No. Google says AI features need no special optimization beyond fundamental SEO best practices, so one page can serve SEO, AEO and GEO. What changes is how the page is written. Each section should answer one sub-question in its first sentence, name entities explicitly and still make sense when quoted on its own.

## Sources

- [GEO: Generative Engine Optimization](https://arxiv.org/abs/2311.09735), arxiv.org
- [AI Features and Your Website | Google Search Central](https://developers.google.com/search/docs/appearance/ai-features), developers.google.com
- [57% of AIO Citations Come From Outside Organic Top 10](https://www.conductor.com/academy/aio-vs-organic-rankings/), conductor.com
- [76% of AI Overview Citations Pull From the Top 10](https://ahrefs.com/blog/search-rankings-ai-citations), ahrefs.com
- [Google users are less likely to click on links when an AI summary appears in the results](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/), pewresearch.org
- [Google's Danny Sullivan: 'Good SEO is good GEO'](https://searchengineland.com/google-danny-sullivan-good-seo-good-geo-461464), searchengineland.com

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Source: https://growthtribune.com/aeo-vs-geo-vs-seo-what-changes-in-practice/