Split visual: classic Google search results on the left, an AI answer card with source citations on the right

    SEO vs. AEO – aren't they the same thing?

    18. Juni 20268 min readDeep Dive
    Till Freitag

    TL;DR:SEO gets you into Google rankings; AEO makes you a cited source in AI answers from ChatGPT, Perplexity & co. They share a technical foundation (semantic HTML, schema, crawlability) but not content strategy: SEO wants clicks, AEO wants citations. To win real reach in 2026, optimize for both — with different levers."

    Till Freitag

    Short answer: No, SEO and AEO are not the same thing. They share a technical foundation, but they have different goals, different winners, and different levers. If you only do SEO, you'll lose reach over the next 24 months. If you only do AEO, you have no conversion path.

    What the acronyms actually mean

    SEOSearch Engine Optimization. The classic game for ~25 years: rank in Google's top 10 so users click your link and land on your site.

    AEOAnswer Engine Optimization. The new game: get cited as a source in the answer of an AI search — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Bing Copilot. The user gets the answer inside the AI, not on your site.

    Some call it GEO (Generative Engine Optimization) or LLMO (LLM Optimization). All variants of the same thing. We stick with AEO here because it's become the most common term.

    Why the question "isn't it the same thing?" makes sense

    On the surface, it looks the same:

    • Both need crawlable content (no empty JavaScript)
    • Both benefit from structured data (Schema.org, JSON-LD)
    • Both reward clear information architecture (H1/H2, lists, semantic HTML)
    • Both live on authority (who links to / cites you?)

    If you already do good SEO, you have a head start on AEO. But "head start" doesn't mean "done."

    Where SEO and AEO diverge

    DimensionSEOAEO
    Success metricRanking, clicks, CTRMentions, citations, source listings in AI answers
    User behaviorUser clicks link, lands on pageUser stays in chat, gets answer directly
    Winning formatListicles, how-tos, pillar pages, long-tailClear definitions, comparison tables, step-by-step, FAQ blocks
    Optimization goal"Be the best result for keyword X""Be the most reliable source for statement Y"
    MeasurabilitySearch Console, Sistrix, SemrushManual, prompt testing — no standard tool yet
    BacklinksAnchor texts, domain authorityMentions often suffice — no link required
    Update frequencyAlgorithm updates every few monthsModel updates weekly, training-data cutoffs

    In other words: SEO is a distribution game (get users to your site). AEO is a representation game (be inside the answer).

    The decisive difference: zero-click

    In SEO, the winner gets the click. In AEO, the click is usually irrelevant — or doesn't happen at all. Perplexity shows you the answer with source bubbles on the side. ChatGPT sometimes cites sources, sometimes doesn't. Google AI Overviews places a compact summary above the organic results.

    The hard consequence: if your strategy is "more clicks from Google," you'll lose traffic in the next 24 months. Not because your SEO got worse — but because more and more queries end inside an AI that may cite your page but no one has to click it anymore.

    In our own Serponado contest sprint we track both in parallel: classic ranking and whether the pillar page shows up as a source in Perplexity/ChatGPT answers. These are two different battles.

    What AEO does differently (four levers)

    1. Direct answers in the first 100 words

    SEO tolerates long intros and storytelling. AEO wants the answer to be in the text immediately. If someone asks "What is AEO?", the first two sentences of your article should contain a clean definition that an LLM can extract 1:1. Just like further up in this article.

    In practice: TLDR block on top, clear definition right under the first heading, FAQ blocks with short answers.

    2. Fact structure instead of prose only

    LLMs love lists, tables, comparisons, step-by-step instructions. What humans find tedious to write is exactly what builds well into a generated answer. Rule of thumb: every 200–300 words, drop a list, table, or code block.

    3. Clear authorship & freshness

    ChatGPT and Perplexity weigh sources partly by reputation and freshness. That means:

    • Author box with name, photo, bio, links to LinkedIn / personal site
    • datePublished and dateModified in JSON-LD schema
    • Real updates — don't just bump the date, actually change the content

    4. Schema markup that AIs read

    Classic SEO schema (Article, BreadcrumbList, Organization) helps AEO too. But two schemas are AEO gold:

    • FAQPage – LLMs extract Q&A blocks directly
    • HowTo – step-by-step guides get reused as structured answers

    We use this in every pillar article — including this one (see FAQ below).

    What SEO and AEO have in common (and why you don't have to throw anything out)

    The good news: clean SEO covers ~70% of your AEO homework:

    • Crawlability — without it, neither Googlebot nor GPTBot gets to your page
    • Server-side rendering / SSG — see our Playwright SSG tutorial
    • Semantic HTML<article>, <section>, <h1> to <h6>, <table>
    • Clean internal linking — pillar + cluster works for both
    • JSON-LD schemas — Article, BreadcrumbList, FAQPage

    That's the shared foundation. Without it, you lose both games.

    Practical: how to start today

    If you're doing SEO and want to layer AEO on top, the three smallest concrete steps:

    1. Add a TLDR block on top of every important article. One paragraph, three to four sentences, answers the main question. That's exactly what an LLM picks up.

    2. Build a FAQ section at the bottom with 4–8 Q&A pairs — and render it as FAQPage JSON-LD. Helps Google rich snippets and makes you an extractable source for AI answers.

    3. Check that GPTBot and PerplexityBot are allowed to crawl. In robots.txt:

    User-agent: GPTBot
    Allow: /
    
    User-agent: PerplexityBot
    Allow: /
    
    User-agent: ClaudeBot
    Allow: /

    Blocking these out of an "AI is stealing my content" reflex actively excludes you from the next 5 years of discoverability. That's a strategic decision, not a technical one — but it has consequences.

    What we see on our own site

    Since spring 2026, we track how our content gets cited in ChatGPT and Perplexity. Three patterns:

    • Comparison tables (e.g., "X vs. Y") get pulled as a source disproportionately often
    • Definition articles with clear etymology (like our Serponado pillar) often surface as "according to source X, this means…"
    • How-tos with concrete code examples get reused in step-by-step form

    Classic long-tail content ("The 27 best tips for…") performs noticeably weaker in AEO than in SEO. Anyone who played the listicle game for the last 10 years has to rethink.

    What we do for clients in practice

    In our SEO sprints, every pillar article is now built AEO-first: TLDR on top, FAQ at the bottom, FAQPage schema, comparison tables wherever possible. Classic SEO (keyword targeting, internal linking, backlinks) runs around it.

    Result: the same page ranks in Google and surfaces as a Perplexity source. With marginally more effort than pure SEO.

    Common misconceptions

    "AEO replaces SEO." No. They run in parallel. Google itself is integrating AI answers into the regular SERPs — AI Overviews are both at the same time.

    "AEO is just a marketing buzzword." Half true. The term is new, optimizing for structured extractable answers is not. But the discipline has shifted enough that it deserves its own name.

    "If I optimize for ChatGPT, my SEO bleeds." No. Technical levers overlap 70%. The additional 30% (TLDR, FAQ, clear definitions) doesn't hurt classic rankings — quite the opposite.

    "I can't measure AEO success." Limited. You can manually prompt-test whether your page surfaces as a source. Tools like Otterly.ai, Profound, or Peec.ai are working on AEO rank tracking but aren't as reliable yet as Sistrix is for SEO.

    What you do differently starting today

    1. Every new article gets a TLDR block on top.
    2. Every pillar article gets a FAQ section with FAQPage schema.
    3. robots.txt allows GPTBot, PerplexityBot, ClaudeBot.
    4. Comparison tables, lists, how-tos instead of pure prose.
    5. Author box with clear identity on every article.

    This isn't a big bang. It's a shift in how you write — and an add-on in your schema. Do it consistently and you'll build a lead in both disciplines over the next 12 months.


    FAQ — short version

    Is AEO just SEO under a new name? No. SEO wants clicks to your site, AEO wants citations in AI answers. The technical foundation (crawlability, schema, semantic HTML) is shared, the content strategy isn't.

    Which AI tools should I track? ChatGPT (incl. Search), Perplexity, Google AI Overviews, Claude, Gemini, Bing Copilot. Perplexity and AI Overviews are most citation-driven right now and therefore most important for AEO measurement.

    Do I need new tools for AEO? Not yet, strictly. Sistrix, Semrush, Search Console cover the SEO half. For AEO you prompt-test manually or try early tools like Otterly.ai or Peec.ai — no standard has emerged yet.

    Do I lose traffic when AIs cite my content? Some click traffic, yes. In return you gain brand awareness and trust signals that feed back into SEO and direct traffic. Being cited regularly in ChatGPT answers gets you Googled more.

    How is AEO different from GEO and LLMO? Practically not at all — three names for the same concept. AEO dominates the DACH region, GEO is more common in the US, LLMO is rarer.

    Which schema matters most for AEO? FAQPage and HowTo. Both deliver AIs directly extractable Q&A or step structures. Article and BreadcrumbList are standard and should be in place anyway.


    Want to set up SEO and AEO in parallel — as an ongoing process, not a one-off audit? We offer sprint-based SEO services that bake AEO in from day 1. → See Serponado SEO as a service

    TeilenLinkedInWhatsAppE-Mail

    Related Articles

    Lovable app with structured HTML, visible to Google, ChatGPT and Perplexity
    May 13, 20267 min

    Lovable SEO/AEO: Every App Discoverable by Google and ChatGPT From Day 1

    Lovable ships server-side rendering, pre-rendering for existing apps, Semrush directly in the builder chat, and an on-de

    Read more
    GPTBot, ClaudeBot and PerplexityBot reading static HTML from an edge server – log evidence visualization
    May 17, 20265 min

    GPTBot, ClaudeBot, PerplexityBot: What AI Crawlers Really See With Prerendering

    We analyzed three months of edge logs: who actually crawls, who executes JavaScript, and who relies entirely on the HTML

    Read more
    Why We Switched from ChatGPT to Claude – and What We Learned About LLMs Along the Way
    February 20, 20265 min

    Why We Switched from ChatGPT to Claude – and What We Learned About LLMs Along the Way

    We worked with ChatGPT for 18 months – then switched to Claude. Here's our honest comparison of all major LLMs and why C

    Read more
    Domain Authority gauge with backlink network and score visualization
    May 20, 20264 min

    Domain Authority & Domain Rank: What the Number Really Means – and What to Watch For

    Authority Score, Domain Rank, DR, DA – every SEO suite has its own number. What it actually measures, why it matters, an

    Read more
    Prerendering pipeline visualization: SPA, Playwright, Schema.org and edge deploy
    April 29, 20263 min

    Prerendering: How to Turn a React SPA Into a Google-Friendly Site

    React SPAs are invisible to crawlers. Prerendering fixes that – without Next.js, without an SSR server. How our Playwrig

    Read more
    Stylized number 5 made of orange ribbons and gears – cover for Claude Sonnet 5
    June 30, 20263 min

    Claude Sonnet 5: Agentic AI Goes Mainstream

    Anthropic ships Claude Sonnet 5 – a Sonnet model that gets close to Opus 4.8 performance at a fraction of the price. Thi

    Read more
    AI Benchmarks Explained: Arena, SWE-Bench, AutomationBench & Co.
    June 26, 20266 min

    AI Benchmarks Explained: Arena, SWE-Bench, AutomationBench & Co.

    How do AI benchmarks actually work – from LMArena to SWE-Bench to Zapier's AutomationBench? A tour of Elo rankings, stat

    Read more
    GLM-5.2 vs. Kimi K2.7 Code – split-screen illustration with Z-letter mark and crescent moon symbol
    June 21, 20267 min

    GLM-5.2 vs. Kimi K2.7 Code: Two Open-Weight Releases in One Week – Two Very Different Bets

    Within four days in June 2026, Z.ai (GLM-5.2) and Moonshot AI (Kimi K2.7 Code) shipped their next-generation open-weight

    Read more
    Gemma 4 12B Coder running locally on a developer laptop – code symbols streaming from a 12B chip
    June 15, 20264 min

    Gemma 4 12B Coder: Local Code Generation Becomes the Default

    Google ships the Gemma 4 12B Coder — the specialized coding variant of the Gemma 4 stack. 12B parameters in GGUF format,

    Read more