Answer Engine Optimization (AEO) in 2026: How to Win Visibility in AI Search & Answer Engines

Quick answer: AEO in 60 words

Answer engine optimization (AEO) is the practice of making your brand and content the easiest and most trustworthy choice for AI‑powered systems to understand, use, and cite when they generate answers. Instead of focusing only on page rankings in SERP, AEO aims to be the answer people see and hear.

Key outcomes of good AEO:

• Your brand is mentioned and linked inside AI answers.
• You win visibility in zero‑click environments.
• You surface new, high‑intent questions that traditional keyword research misses.
• You protect and grow demand in a world where fewer people click blue links.

Throughout this guide, I will explain how SEO connects to AEO, how to build an AEO roadmap that complements your SEO roadmap, and show real data and steps from Similarweb’s Gen AI Intelligence suite.

I’ll use Chewy.com as an example brand (during the period 10 Nov 2025-10 Dec 2025), and my FIFI framework for this one, but I’ll also introduce several other AEO frameworks.

1. Why AEO was born: search is turning into answers

1.1. Zero‑click and AI summaries are the new normal

Traditional organic search is already behaving like an answer engine. A Similarweb study from July 2025 shows that zero-click search rates have risen from 56% to 69% since the launch of AI Overviews. This means that just a little over 30% of searches result in a click.

On top of that, the Pew Research Center found that when Google shows an AI summary, only 18% of searches produce one, and those summaries are about 67 words long and cite three or more sources. People are less likely to click when the answer is in front of them.

The time when users insert queries and get a handful of relevant options is over. Engines are now (and have been for a while) trying to answer the users’ questions directly.

No options, no scrolling, but one synthesized answer, trying to pre-answer the user’s follow-up questions as well.

1.2. Answer engines, not just search engines

Today, users ask questions everywhere: Google with AI Overviews, Bing with Copilot, ChatGPT, Perplexity, Gemini, Claude, and voice assistants.

These systems behave like generative engines: they decompose queries, retrieve content, and synthesize an answer. These engines pull from multiple documents, which means brands can systematically increase visibility.

If your brand is not in those synthesized answers, you gradually disappear from the way people learn and decide.

1.3. What it means for brands

If your brand is not included in AI-generated answers, you effectively disappear from how people learn and decide. As zero‑click search behavior grows, brands must ensure they are visible and cited in AI results.

Investing in AEO helps protect your hard‑won authority and ensures that the answers people see reflect your expertise.

2. What AEO is (and how it relates to SEO and GEO)

2.1. Working definition of AEO

I define AEO simply: AEO is the discipline of making your brand the most reliable, easy‑to‑quote source for the questions your customers ask in AI‑powered systems.

AEO helps brands stand out on AI platforms by increasing the likelihood that their content will appear in response to user questions.

It involves being retrieved when the LLM searches the web, being trusted enough to be used as a main source, and being cited with your brand and URL in the final answer.

2.2. AEO vs SEO vs GEO

Aspect	SEO	AEO	GEO / LLM optimization
Main surface	Classic search results	AI modules, AI chat & voice	AI chat and generative engines
Main goal	Get clicks from ranked results	Get named and cited as the answer	Maximize visibility and influence inside generative AI outputs
Unit of competition	Page and query	Brand, topic, and answer block	Brand and content across many prompts
Core metrics	Rankings, organic traffic, CTR	Mentions, citations, AI visibility	Share of voice across prompts and engines

Foundation’s GEO guide translates this into practical advice: optimize content so that LLMs are more likely to recognize and use it when answering questions. In practice, AEO can be seen as a focused part of GEO, emphasizing answers and brand visibility.

2.3. Where AEO fits in your growth stack

You still need technical SEO, strong content marketing, and digital PR. AEO builds on those foundations and adds AI visibility as a new metric.

AEO is not a replacement for SEO, but an extension that ensures your hard‑won authority carries over into AI answers.

3. How answer engines actually build answers

3.1. Questions become “query fan‑outs.”

Large language models rarely run a single simple search. They break a question into several subqueries, fetch documents for each, then fuse them together.

This query fan-out process occurs across all generative engines. When I inspected Chewy’s prompts in Similarweb’s Prompt Analysis tool, I saw how user questions cluster into natural groups:

• Definitions (“What is hypoallergenic dog food?”)
• How‑to questions (“How can I ensure my dog gets the best diet?”)
• Comparisons (“Best food for adult dogs?”)

Each of these prompts triggers different retrieval patterns and may include multiple subqueries. This happens for every brand out there. And every brand out there that’s interested in gaining visibility in generative AI engines should pay attention to how these engines interpret and break down prompts.

3.2. Where your content enters: retrieval and trust

Similarweb’s analysis of the 2025 Gen AI landscape found that 36.9% of cited sources in AI are PR websites. An additional 18.9% come from Review & UGC websites. See the full source distribution below:

This tells us that answer engines lean on high‑trust, broad coverage sources.

During my analysis, I used Similarweb’s Citation Analysis tool to identify which domains are most often cited in answers to specific Chewy-related topics (actual data later in the post).

The AI citation analysis dashboard showed that the brand’s own domain accounted for only a small share of citations in responses mentioning the brand. At the same time, competitors and independent blogs were cited more often. This was not unique for Chewy.

This demonstrates that just being mentioned is not enough: you need your pages to be so clear and authoritative that engines choose to cite them.

3.3. From sources to citations

Not every source that influences an answer gets a link, but citations matter because they tell users where the answer came from.

Pew’s study noted that most AI summaries cite at least three sources. However, Similarweb’s Gen AI studies showed that citation patterns vary significantly between platforms and that the number of sources cited in AI answers is increasing.

These findings underline the importance of building citation‑worthy content.

When you run a citation analysis, you may discover that your brand’s pages rarely appear among the most cited URLs.

If the top-cited resources come from third‑party blogs, news outlets, or community sites while your own pages are absent, it signals that your content is being used but not considered worthy of citation.

To change that, you need to publish research‑driven guides that answer questions directly and provide unique value. You need to leverage all shared and rented brand assets, as well as UGC sites in which you can insert your own frame and influence citations at the source.

Content that consolidates information and backs it up with data is more likely to earn your domain credit from answer engines.

This means brands need to publish definitive, research‑driven guides that answer questions concisely and provide unique insights.

3.4. Types of answer engines and what they care about

Answer engines differ in how they retrieve and display information:

• AI Search (Google AI Overviews/AI Mode) favors fresh, authoritative pages and often shows summary boxes that cite multiple sources.
• Chatbot engines (ChatGPT, Perplexity, Gemini) synthesize information from multiple sources and produce longer answers. In many cases, ChatGPT generates the majority of AI traffic to websites, while other engines, like Perplexity and Gemini, contribute a much smaller share.
• Voice assistants often provide single, concise answers and rely on established knowledge bases such as Wikipedia.

Understanding these behaviors helps tailor content formats. For example, short answer blocks of 40–80 words align with the length of AI summaries.

4. AEO strategy Framework (I call it FIFI):

In my work, I use a simple four‑pillar model named FIFI: Find – Implement – Focus – Increase.

These pillars are very simple and repeatable for any question your research identifies:

1. Find question‑first content insertion opportunities.
2. Implement machine‑friendly structure and schema.
3. Focus on authority, entities, and topical depth.
4. Increase brand presence and off‑site signals.

Pillar 1: Find question‑first content insertion opportunities

Goal: match how people talk to answer engines, not just how they type keywords. Whole sentences and question‑style queries are more likely to trigger AI answers than a short-tail search.

How to implement this:

1. Use the prompt analysis tool to filter prompts by topic and identify the questions people actually ask.
2. Group prompts into categories:
   1. Definition questions (e.g., “What are the best pet accessories?”)
   2. How‑to questions (“How do I groom my cat?”)
   3. Comparison questions (“Which pet toy brand is better for dogs?”).
3. Use these clusters to identify visibility gaps and opportunities for targeted content.
   1. If your brand is absent from many definition queries, create authoritative guides and product round‑ups.
   2. Where your brand is present but not dominant, improve answer blocks and include deeper research to outperform competitors.

Pillar 2: Implement machine‑friendly structure and schema

Goal: make it easy for AI engines to find, understand, and copy the right snippet.

Optimizing for “AI crawlability” means short paragraphs, bullet lists, clear headings, and accessible HTML.

After reviewing many brands’ existing content, I noted that product pages and blog posts often have long paragraphs and lack structured summaries. Most brands also did not implement the FAQ or HowTo schema.

Adding a 40-80-word answer block at the top of each post (TL;DR), using bullet lists, steps, or pros/cons content structures, would make the content more extractable. Implementing structured data (FAQPage, HowTo, Article) helps AI systems understand the page type.

Pillar 3: Focus on authority, entities, and topical depth

Goal: become the go-to, safe authority for your topic cluster.

Optimization strategies and visibility gains are domain‑specific, meaning you need to build deep topical clusters rather than one‑off posts.

How to implement this:

1. Use the topics summary and visibility dashboards to identify which topics you dominate and which you do not.
2. Compare your brand’s visibility against competitors to spot strengths and weaknesses.
3. Build deeper, more authoritative content clusters around topics where you are strong to defend your share of voice.
   1. Expand into weaker topics by publishing comprehensive guides, journey content, and definitive product round‑ups with clear answer blocks.
4. Analyze the top competitors and source categories (news sites, e‑commerce platforms, blogs, etc.) to understand where AI engines pull information.
   1. Aim to match or exceed their authority, freshness, and topical depth so that engines choose to cite your pages.

Pillar 4: Increase brand presence and off‑site signals

Goal: make sure your brand exists in the places LLMs trust.

Off‑site signals matter because AI engines rely heavily on high‑trust sources like news articles, Wikipedia, and community sites. Citation analysis shows how often your domain is cited relative to others.

How to implement this:

1. Use the citation analysis dashboard to measure your domain influence (how often your pages are cited relative to total citations) and to identify the most frequently cited domains and URLs.
   1. If your domain influence is low and most citations come from third‑party sites, you need to strengthen your off‑site presence.
   2. Perform AI citation gap analysis to understand where your competitors’ brands are cited, and where you’re not. This will give you greater visibility into the entire landscape and surface new citation opportunities for your brand.
2. Launch digital PR campaigns to secure mentions and citations from high‑authority industry blogs, trade publications, and general news sites. These earned mentions provide trusted signals for AI engines.
3. Encourage customers and bloggers to review your products on third‑party platforms.
4. Develop or update Wikipedia and Wikidata entries with accurate, well‑cited information about your brand.

Off‑site signals matter because AI engines rely heavily on high‑trust sources such as news articles, Wikipedia, and community sites.

To increase the likelihood that your brand will be cited, diversify the sources that reference you: secure mentions in high‑authority industry blogs, trade publications, and general news sites.

Encourage customers and bloggers to review your products on third‑party platforms, and maintain accurate, well‑cited entries on Wikipedia and Wikidata.

With the framework established, here’s how I applied it to Chewy’s data using Similarweb’s AI Brand Visibility tools

5. Using Similarweb tools to drive AEO: Step‑by‑step

This is the workflow I followed in Similarweb and explains what each step and metric means for Chewy’s AEO strategy.

Let’s pull out Chewey’s data and see what it tells us:

5.1. Set up the AI Brand Visibility campaign

1.       Log in to Similarweb and open the AI Brand Visibility dashboard.
2.       Select the ChatGPT model from the model dropdown.
3.       Set the time range to Nov 10-Dec 10, 2025.

This opened an overview showing Chewy’s brand visibility score (3.55%), brand mention share (0.48%), and raw counts of answers and mentions.

These metrics tell us how often the brand appears and how significant its presence is relative to the total number of answers.

5.2. Explore topics summary

1. Scroll down to the Topics table to see Chewy’s visibility across different categories. Chewy’s topics bar chart shows visibility by topic.
   1. In our Chewy example, the bar chart showed the brand had the highest visibility at 9% in Pet Accessories and Pet Grooming, followed by 7% in Pet Toys and much lower percentages in Pet Supplies, Pet Health, and Pet Food.

2. For each topic, examine the top competing brands and source categories to see which dominate it.
   2. For the pet supplies category, you’ll see that 40% of the mentioned websites are news & publisher sites, and 33% are ecommerce sites. You can drill down into each topic to see which categories are most visible there.
   3. The top competing brands included Petco, Earthbath, Kong, PetSmart, Amazon, and Walmart.

These steps highlight where Chewy is strong and where it is weak.

For example, Chewy’s low visibility in Pet Food suggests it should invest in authoritative content on nutrition and feeding, while still defending its position in Pet Accessories.

5.3. Analyze prompt patterns

1. Choose Prompt Analysis from the menu.
2. Filter prompts by topic or leave it on All Topics to see the full list.
3. Examine the table showing each prompt, the top-mentioned brand, and the share of mentions by brand.
4. For each prompt, note whether your brand was mentioned and at what share.
5. Also note prompts where your brand is absent or not the top brand.
   For example, for the prompt “What are the best pet supplies for pet health?”, Chewy was mentioned, but Zesty Paws was the top brand, with the most visibility.
6. Export these prompts and group them further by query type into the three categories I listed before:
   1. Definition questions (“What are the best pet accessories?”)
   2. How‑to questions (“How do I groom my cat?”)
   3. Comparison questions (“Which pet toy brand is better for dogs?”)

For the “pet supplies” topic, under the “definition questions” group, some prompts showed Chewy as the top brand, while others did not.

This highlights visibility gaps that need to be closed:

As a brand, your purpose would be to be mentioned at the top of every AI answer (and dare I say, more than once per answer).

Grouping prompts by topic and question type reveals where your brand dominates and where it’s absent, allowing you to prioritize high‑impact content and aim to be the top‑cited source for each key question.

Adding another grouping layer enables deeper analysis of your gaps relative to other brands, helping you create a more accurate roadmap to increase your visibility.

This data shows where Chewy is already recognized and where it lags.

To defend its share in strong topics and close gaps in weaker ones, the brand needs deeper, more authoritative content clusters (particularly around Pet Accessories and Pet Grooming) and new guides targeting Pet Food and Pet Health, where visibility is low.

What it means for the brand:

Chewy needs to create content that directly answers these common questions.

• For prompts where Chewy is absent, there is an opportunity to produce authoritative guides and product round‑ups.
• For prompts where Chewy is present but not the top brand, existing pages may need clearer answer blocks or deeper research to outperform competitors.

5.4. Review citation data

1. Go to the Citation Analysis tool.
2. Check your brand’s domain influence and share of citation. This is the baseline for how you view your visibility vs. your competitors.
   1. Chewy’s domain influence (13%) and the share of citations in answers mentioning the brand (8%).

1. View the top-cited domains list to see which websites AI engines trust. Check each domain’s influence score. The influence score indicates the overall trust AI engines have in the domain.
   1. In my example, we can see petcare.com has 8% influence on AI for Chewy-related topics. This should be a source for Chewy to target for partnerships and content marketing.
2. Scroll down to the top-cited URLs to see specific pages being cited for your core topic.
   1. In my example analysis, none of Chewy’s own pages appeared in the top ten for the pet supplies topic. Instead, the list included articles from petdaily.org, peta.org, and various independent blogs.
   2. This means Chewy’s content was being used but not considered citation‑worthy.

This underscores the need to build authoritative pages and strengthen off‑site signals so AI engines have trustworthy Chewy URLs to cite.

The small share of citations to Chewy indicates that AI systems rely on third‑party sources to justify their answers. Chewy should publish data‑rich pages and secure more off‑site mentions to become a preferred citation.

5.5. Check sentiment distribution

1.  Go to the Sentiment Analysis tool.
2. Check your mentions sentiment distribution.
   1. In my brand sentiment analysis, I found that Chewy had 197 mentions during the period, with 18% positive, 82% neutral, and no negative sentiment. This is a good situation, overall.
3. Compare your brand sentiment scores with your competitors to get the whole perspective.
   1. It’s possible to have topics in which negative or positive sentiment is common.
   2. Always compare your scores to your competitors on each topic to understand the full scope of audience sentiment.
      1. When I compared Chewy’s sentiment scores with competitors, I saw its scores (0.11–0.22) were lower than brands like Kong and Earthbath (0.82–0.96) on a few topics:

Sentiment signals how AI engines might present your brand.

These signals are critical. If they are negative, or just “not good enough”, it doesn’t matter if you’re mentioned or cited in AI. In real life, a bad sentiment mention can be worse than no mention at all. Sentiment management is a crucial part of AI visibility management.

While neutral is acceptable, increasing positive sentiment through helpful content and customer advocacy may improve the tone of AI answers and brand perception.

5.6. Analyze AI traffic impact

1. Switch to the AI Traffic module and set the date range.
   1. For Chewy, I set the date range to Jun 2025-Nov 2025 (six months).
   2. The traffic data across all AI models showed that Chewy received 641.1K visits from chatbots, which is about 7% of its referral traffic and down 6% from the previous period.

2. Record the traffic split.
   2. For Chewy, ChatGPT delivered 89.87% of AI visits, Perplexity 6.53%, and Gemini 3.1%.
   3. As expected, ChatGPT dominates, but Perplexity’s growth here is quite noticeable.
   4. Chewy should analyze Perplexity traffic patterns and invest in resources to optimize and increase it.

3. Review the Top landing pages list. This connects visibility data to traffic data.
   3. The top page was the homepage (22.46% of AI traffic), followed by an authentication page, various product pages, and blog articles.
   4. Most pages received traffic from ChatGPT only, but some pages received AI traffic from Perplexity as well:

This information shows how AI citations convert into real visits.

The homepage’s high share suggests users click through after reading brand names in answers. Chewy should ensure its homepage and key pages deliver a strong first impression and clear conversion pathways.

The lack of diversification in AI traffic sources can be an opportunity for Chewy. Analyzing Perplexity’s traffic patterns and optimizing other website pages can yield traffic from Perplexity and additional AI engines.

6. AEO checklists and frameworks you can reuse

To keep things actionable for my team, I use simple checklists and frameworks. These ensure we don’t miss anything in our analysis and our answer engine optimization process.

Analyze your visibility using the FIFI framework and the PROMPT checklist. Then implement your findings into your content using the 4P framework, and roll out your 30-90-60 AEO roadmap.

6.1. The PROMPT checklist for AI Brand Visibility

When reviewing prompts and citations in Similarweb, I score them using PROMPT:

1. Popularity: How often does this prompt occur?
2. Relevance: Is it high intent for my business?
3. Ownership: Is my brand mentioned or absent?
4. Mentions landscape: Which competitors and domains show up?
5. Page types: Are the cited sources brand sites, docs, blogs, or UGC?
6. Trust: Do high‑trust sources dominate the citations?

This scoring helps prioritize which questions to tackle first.

6.2. The 4 Ps of AEO content

For any question, check that your content is:

1. Precise: It begins with a direct answer of 40-80 words.
2. Proven: It cites sources, data, or real examples.
3. Parsed easily: It uses clear headings, bullet lists, and, where appropriate, tables.
4. Positioned: It sits in a topic hub with internal links and a defined entity context.

7. Putting it together: 30, 90, and 180-day AEO roadmap

Here is a practical timeline to turn insights into results.

First 30 days: Baseline and quick wins

1. Set up AI Brand Visibility campaigns for your brand across key engines and topics.
2. Export prompts and categorize them into definition, how‑to, and comparison clusters.
3. Add answer blocks and FAQ sections to existing high‑traffic pages.
4. Implement FAQ schema on relevant pages.

90 days: Content build and first experiments

1. Publish at least one pillar page per key topic.
2. Publish supporting Q&A pages answering the top 10-20 prompts.
3. Run a small digital PR campaign around a data story (perhaps a summary of AI visibility trends in the pet industry).
4. Use the AI Brand Visibility tool to check if citations and visibility improve for target topics.

180 days: Scale and integrate

1. Incorporate AEO sections into every content brief (prompts, answer blocks, schema requirements).
2. Schedule quarterly AI prompt and citation audits in Similarweb.
3. Integrate AI visibility metrics into your marketing dashboards and KPIs.

Successful brands will be those that adjust their metrics and track visibility and influence inside AI search. AEO is how you operationalize that philosophy.

Closing thoughts

As a search professional, I view AEO less as a buzzword and more as a practical addition to SEO, and a response to how people gather information. Studies from Similarweb, SparkToro, and others all point in the same direction: fewer clicks, more answers in the interface, and higher stakes for brand visibility.

The analysis I did with Chewy shows that even a well‑known brand can be underrepresented in AI answers.

By analyzing real prompts, designing answer‑first content, strengthening topical authority, building off‑site signals, and measuring AI visibility, you can turn AEO from an abstract idea into a repeatable program that complements your SEO strategy.

For brands willing to adapt, this is not a threat, but an opportunity to own the conversation where it happens.

FAQ

What is answer engine optimization?

Answer engine optimization (AEO) is the practice of making your brand and content easy for AI systems to understand, trust, and cite when they answer user questions.

How is AEO different from SEO?

SEO aims to get your pages ranked in traditional search results so people click to your site. AEO aims to get your brand and content used directly in AI answers across many engines. SEO measures rankings and organic traffic; AEO measures citations, share of voice in AI tools, and visibility for strategic prompts.

Which answer engines should I optimize for?

A comprehensive AEO strategy spans multiple platforms. Google’s Search Generative Experience dominates factual and local questions, ChatGPT excels at conversational and multi‑part queries, Bing Copilot blends citations with conversational answers, and emerging platforms like Perplexity and Claude serve niche audiences. Optimizing for all increases your brand’s reach.

What is GEO or LLM optimization, and how does it relate to AEO?

Generative engine optimization (GEO) and large language model (LLM) optimization focus on improving visibility inside any generative AI system that aggregates and summarizes content. AEO is a practical slice of GEO that focuses on optimizing for answer experiences (AI summaries, chat responses, and voice responses), delivering direct responses rather than lists of links.

What types of content perform best in answer engines?

Question‑based content that mirrors natural language performs best. Use headings phrased as questions, followed by a concise 40–60‑word answer and deeper details. Comprehensive guides, FAQ sections with schema, step‑by‑step how‑to articles, and expert insights earn higher citation rates.

How do I implement structured data for AEO?

Implement Schema.org markup to clarify your content. Essential types include FAQPage for Q&A pairs, HowTo for step‑wise guides, Article for core content, Organization for credibility, and LocalBusiness for location‑based queries. Validate your markup with Google’s Rich Results Test, so that answer engines interpret it correctly.

What are common AEO implementation mistakes?

Keyword stuffing and shallow, surface‑level content hurt AEO. Broken or incomplete structured data prevents AI systems from understanding your pages. Consistency matters: keep your information accurate across channels, avoid overly promotional language, and aim for comprehensive topic coverage rather than isolated pages.

How do I measure success in AEO?

There are three layers: AI visibility and citations for key topics and prompts, traffic and conversions influenced by AI, and classic SEO metrics like organic traffic and branded search volume. Together, they show your brand’s influence across search and AI ecosystems.

Will AEO replace traditional SEO?

No. AEO builds on SEO rather than replacing it. All SEO fundamentals still matter. You still need technically sound, crawlable sites and strong topical authority. What changes is where you aim: from ranking in one engine to being cited in many generative engines. Brands that win treat SEO, AEO, and GEO as one integrated discovery strategy.