What is Answer Engine Optimization (AEO)?

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by AEO Checker Team

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10 min read

AEO is an emerging discipline focused on optimizing your content to be used as answers by voice assistants, AI chatbots, and LLMs. In this article, we define AEO (also known as Generative Engine Optimization, GEO), where it comes from, and how it differs from traditional SEO.

From Search Engines to “Answer Engines”

The way people search is changing dramatically. Traditional search engines returned a list of links for you to click and explore. Now, increasingly, people expect direct answers thanks to voice assistants (Alexa, Siri) and AI chatbots that respond with a single answer or conversation. Gartner even predicts that “by 2026, traditional search engine volume will drop 25%, with search marketing losing market share to AI chatbots and virtual agents”. We’re already seeing this: in 2024, an estimated 60% of Google searches ended without a click to any website, as users either got their answer from the results page itself or abandoned the query. Google’s own generative AI results (called AI Overviews, or AIO) and featured snippets mean users often find what they need without additional clicks.

This shift has given rise to the concept of “Answer Engines”. Instead of acting purely as navigation tools, platforms like ChatGPT, Bing Chat, Google’s SGE (now AI Overviews), and voice assistants act as answer providers. They attempt to understand your question and provide a direct, concise answer, often synthesized from multiple sources.

The term Answer Engine Optimization (AEO) was popularized to describe optimizing for this new reality. Digital marketing thought leader Jason Barnard is credited with coining “Answer Engine Optimization” in 2018, foreseeing that as voice search and direct answers grew, marketers would need to move beyond classic SEO. Back then, AEO was often discussed in context of voice assistants (e.g. getting your content to be the one Alexa reads) and featured snippets (the answer box at the top of Google). Now in the mid-2020s, AEO has expanded to encompass all AI-driven search experiences, sometimes under other names like Generative Engine Optimization (GEO), Large Language Model Optimization (LLMO), Large Language Model SEO (LLM SEO), or even AI SEO. But regardless of the name, the goal is the same: to make your content the preferred one for user questions.

How AEO Differs from Traditional SEO

It helps to contrast AEO with SEO:

  • Traditional SEO is about improving your website’s ranking on a search engine results page (SERP) for various keywords, so that users click through to your site. Success is often measured in clicks and traffic. You optimize meta tags, build backlinks, target keywords, etc., to move from rank #8 to #1, for example. The user then chooses your link and gets the answer on your page.

  • Answer Engine Optimization is about improving your content’s visibility as a direct answer on search platforms, even if the user never clicks through. Success is measured in being featured or cited as the answer. The focus shifts to answering questions outright, in formats easily digestible by machines (and by humans at a glance). Instead of solely driving the user to your site, you want your site’s information to reach the user wherever they are asking the question (Google snippet, voice reply, chatbot answer, etc.).

AEO means optimizing for zero-click answers and conversational queries. It’s not replacing SEO so much as complementing it. You still need SEO best practices (good content, technical health, authority), but you frame content in a way that machines can extract the direct answer.

Here are key differences and overlaps:

  • Queries & Keywords: SEO often targets short, broad keywords. AEO targets natural language questions and long-tail queries (“what are the best running shoes for marathon training?”). Tools like AnswerThePublic or Google’s People Also Ask are great for discovering actual questions users ask. Think in FAQs, not just keywords. In fact, identifying the right questions is step one in AEO.
  • Content Format: In SEO you might write a long article hoping parts of it rank. In AEO, you structure content so that a specific snippet can be pulled out. This means concise answers (often 40-60 words) to common questions, ideally placed at the top of your page or under a clear heading. Bullet points, numbered lists, tables which help featured snippet extraction. For voice answers, content should read conversationally and get to the point quickly (since the assistant might only read 1-2 sentences).
  • Technical Aids: Both SEO and AEO benefit from schema markup (structured data). For AEO, adding FAQ schema, HowTo schema, etc., gives search engines explicit Q&A pairs and step-by-step instructions. This can increase your chances of being used in an answer or voice response. Featured snippets themselves can be influenced by schema and proper HTML structure (e.g. <h2> headings for questions, <ul> for list answers).
  • User Intent Focus: AEO forces you to deeply consider user intent, especially informational intent. If someone asks “How do I fix error X?”, your content should directly address that with a solution. Traditional SEO might have enticed the user with a clickbait title to then find the answer; AEO tries to deliver value immediately. Google’s generative AI will even synthesize multiple sources to answer complex queries, so your content needs to stand out as accurate and authoritative to be included.
  • Metrics of Success: In SEO, you monitor rankings and organic traffic. In AEO, you might monitor “answer presence” such as is your content appearing in featured snippets? Are voice assistants frequently citing your site? Are AI chat tools like Bing/ChatGPT (with Browse) referencing your info? These are harder to measure, but one can use tools (or even manually test queries) to see where their content is the answer. Brand mentions and visibility become as important as click-throughs. It’s a paradigm shift: instead of just bringing users to your content, you bring your content to users wherever they ask.

How Do AI Search Engines Choose Answers?

Google’s AI Overviews (SGE/AIO)

Google’s Search Generative Experience uses an LLM (like an advanced Google Bard) to answer queries directly on the results page. It first processes the query and gathers relevant information from its index (likely the top-ranked pages, relevant snippets, and Knowledge Graph. It then synthesizes an answer, and finally it cites a handful of sources by linking to them. Studies show that AIO results often pull content from pages that already rank well (top 10 or so), but not always. The overlap between AIO citations and traditional organic results was only ~20-26% in one analysis. This means sometimes the AI might surface a source that wasn’t ranking #1 because the content directly addressed the question. In either case, Google’s AI looks for clear, authoritative passages it can stitch into an answer. For example, if your page has a concise definition of a term, the AI might quote it. If multiple sources agree on a fact, the AI is more likely to use those facts. Ensuring your content is factually correct, well-structured, and tagged with schema can improve its chances. Also, Google favors authoritative domains with strong E-E-A-T (experience, expertise, authority, trustworthiness) signals make it more likely your content is chosen.

ChatGPT (OpenAI) and Bing Chat

ChatGPT mainly relied on its trained knowledge and whatever plugins or limited web access it had to answer. With the introduction of Browse modes and plugins, ChatGPT can now fetch info from the live web. Bing Chat, which is powered by GPT-4, always had web access through Bing’s index. These AI chatbots use a technique called Retrieval-Augmented Generation (RAG). They perform a search for the user query, retrieve top relevant pages, and then use the content of those pages to compose an answer. Bing Chat will show footnote numbers that link to sources. How do they choose which content to cite? Likely factors include: relevancy of the page to the query (SEO still matters here), presence of the exact answer or keywords in the page (especially in a concise form), and site authority. If your content directly answers the query in one paragraph, a chatbot can easily quote that line. If the answer is buried across several pages, the AI might miss it. That’s why AEO encourages creating content that’s easy for AI to parse (short sentences, direct answers near the top, etc..). There is also an element of semantic search: these models vectorize text and match the meaning of the question to the meaning of text in your content. So, answering comprehensively (covering related terms and contexts around a question) can help the AI understand that your page is a good match.

Voice Assistants (Alexa, Siri, Google Assistant)

These were the original “answer engines.” Typically, when you ask Alexa something, it either pulls from a trusted source (e.g. Wikipedia for factual queries) or from featured snippets for web queries. Google Assistant often reads out the featured snippet answer for web queries. So the selection mechanism is basically: win the featured snippet, win the voice answer. Alexa had deals with certain content providers for some queries (e.g. using Yelp for local business info), but for general Q&A, optimizing much like you would for a featured snippet or concise answer was key. That remains true: if voice search is part of your audience’s behavior, ensure your content is the one-liner answer that voice AI would pick. For instance, a page titled “How to Boil an Egg” should have a step-by-step or a quick summary “To boil an egg: Place eggs in boiling water for 9-12 minutes, then cool in ice water.”.

Best Practices for AEO (Answer-Focused Content Optimisation)

AEO might sound abstract, but it boils down to excellent content creation with an answer-oriented mindset. Here are concrete steps and tips to implement AEO:

  1. Research Actual Questions: Use tools and SERP features to find what questions your audience is asking. For example:

    • AnswerThePublic, AlsoAsked: Enter your keyword and get a visualization of common questions (who, what, how, why) people search.
    • People Also Ask (PAA): On Google, these expandable question suggestions reveal popular queries. Can you answer those on your site?
    • Forum and Community Snippets: Check Reddit, Quora, Stack Exchange for recurring questions in your niche. These indicate gaps that your content could fill with authoritative answers.
    • Internal Search and Customer Queries: What are people searching for on your site or asking your support team? If those questions aren’t answered publicly, consider adding content for them.

  2. Structure Content for Snippets and Voice: Once you have the questions, create content that directly answers them in a concise block. Some techniques:

    • FAQ Sections: Incorporate a FAQ on key pages or a dedicated FAQ page. Each question (marked up with <h2> or <h3> and possibly FAQ schema) followed by a brief answer increases chances of snippet inclusion. Google can then feature that Q&A in search or use it in an AI overview.
    • Paragraph answer + details: Start your article or section with a one-paragraph answer to the main question, then elaborate. This way the AI or snippet can grab the first part for a quick answer, and users who click get the full detail.
    • Lists and Steps: For “How-to” queries, use numbered lists for steps, or bullet points for list-type answers (“Top 5 tips…”). Featured snippet algorithms love well-formatted lists (e.g., “1. Do X… 2. Do Y…”). Voice assistants also prefer step-by-step responses for procedural questions.
    • Tables for Data: If the answer involves data, a simple HTML table can sometimes get featured, and it’s also easy for AI to parse.

  3. Leverage Structured Data (Schema): Implement schema markup relevant to answers:

    • FAQPage schema: Wrap your question & answer pairs in the JSON-LD schema. This can directly make your FAQs appear in Google’s results in an expanded format, and it’s a strong hint to the AI about the question-answer relationship.
    • HowTo schema: For step-by-step guides. Google may use this to provide instructions via Assistant or visual results.
    • Speakable schema (for news/content): There’s a schema for voice assistants indicating which parts of a page are suitable to be spoken out loud. If you publish news or articles, this could help Alexa/Assistant read your snippets.
    • Article/Organization schema with Author info: E-E-A-T is important; having clear schema for your organization, author, and the content’s type can bolster credibility.
    • Structured data essentially gives machine-readable context that this text is an answer to this question, which is gold for answer engines.

  4. Optimize for E-E-A-T (Experience, Expertise, Authority, Trust): Both Google’s algorithms and AI models prioritize content that appears trustworthy and authoritative. To optimize for that:

    • Authoritativeness: Get cited by others, have strong backlinks, and mention credentials. E.g., if a doctor writes a medical FAQ on your site, include their bio/credentials (and use schema for Person/Author). An AI scanning the page may note the expertise and prefer that answer.
    • Trustworthiness: Keep content up-to-date and accurate. Review facts regularly. If multiple sources have similar answers but yours is outdated or contains a slight error, the AI might skip yours. Also, for sensitive topics, having disclaimers or references to sources can help.
    • Experience & Perspective: Interestingly, AI can also be drawn to unique insights or phrasing. If you have actual experience or a unique case study in your answer, it might stand out. A human touch can signal to algorithms that your content has firsthand knowledge, which is part of the E-E-A-T guidelines.

  5. Monitor and Adapt:

    • Use our free AEO checker tool to see how your visible your brand is to AI chatbots and see personalised suggestions.
    • Use analytics: While you can’t directly see “answer impressions” easily, you might notice changes in organic traffic patterns. For instance, you could have stable ranking but fewer clicks maybe because Google is answering more queries directly. If so, ensure you are the one being used in those direct answers. Tools like Google Search Console’s “performance”, or Google Analytics where you can view the source of incoming traffic such as ChatGPT or Gemini.

  6. Write for Humans (and AI): Ultimately, optimizing for answers still means providing value. Your content should be genuinely helpful and well-written. AI models actually gauge content quality similar to humans. They can sense coherence, completeness, and tone. So don’t overly gimmick your text just to appease an algorithm. Write clearly, use the question in the answer, and cover related follow-up questions (which often appear in chats as follow-ups). A conversational yet informative tone works well, since it aligns with how AI like ChatGPT attempts to answer in a conversational way.

The New Industry of AEO

AEO is becoming a recognized field, sometimes under the banner of “AI Search Optimization” or Generative Engine Optimisation (GEO). Businesses are hiring consultants specifically to audit their content for answer-friendliness. For example, how well does your brand’s information surface when someone asks an AI assistant about a product category you’re in? This is the kind of question AEO experts aim to solve.

One could argue AEO is just good SEO writing combined with structured data as many principles of SEO remain paramount. The difference is in mindset and focus: AEO is laser-focused on the answer layer of search. It assumes the first point of contact with your audience might be an AI-delivered answer, not your homepage.

Jason Barnard’s early advocacy of AEO in 2018 was visionary. He noted voice search as a catalyst; today we see AI chat as another. Industry thought leaders like Alan D. Antin (Gartner) are echoing this, with quotes like “Generative AI solutions are becoming substitute answer engines”, forcing companies to rethink how they approach content writing. Content marketing strategies now must consider distribution beyond the click. It’s not just about ranking #1 on Google, but also about being referenced by ChatGPT, by Google’s AI overview, Gemini, Perplexity etc..

Embrace the Answer Mindset

AEO is a response to real user behavior shifts. Users want answers, not links, especially on mobile and voice interfaces. By aligning your content strategy with that reality, you’re future-proofing your SEO for the AI era. This doesn’t mean abandoning traditional SEO, but rather augment it. Continue to optimize for rankings, but also optimize for rich results and AI citations.

To get started, identify a few key questions in your domain and apply the best practices above. And very importantly, track the outcomes over time.

Remember that every time an AI or search engine uses your content to answer someone’s question, it’s a chance to build trust with an audience that might not have otherwise discovered you. It positions you as an authority. And as AI-driven search grows, Answer Engine Optimization will be as crucial as Search Engine Optimization for maintaining your digital presence. Start thinking: “If an AI had to answer this question, would it choose my content?” and let that guide your content creation. In the age of answer engines, the best answer wins.

What is Answer Engine Optimization (AEO)? | AEOChecker.ai