AEO vs SEO: what actually changes

AEO is not a replacement for SEO, it is what happens to SEO when the buyer asks ChatGPT or Perplexity instead of typing into a search box. The raw material is identical: a clear, well-structured page on your own site that genuinely answers a question. Google's ranker and an AI assistant are both reading that page; they just do different things with it.

The overlap is real. A page good enough to rank on page one is usually a page an answer engine is happy to read and repeat. So most of what a good SEO already does still counts. What changes is the scoreboard: a ranking puts you in front of the buyer and lets them choose, while an answer engine does the choosing for them and hands back a short list of names.

Same inputs, different finish line. Here is what each thing becomes when you move from optimising for a search ranking to optimising for an AI answer.

Notice that nothing in the AEO column tells you to abandon the SEO column. You are adding a second reader, the model, to a page you were already writing for a person.

If you already do SEO well, you are most of the way there. The fundamentals that earned rankings are the same fundamentals an answer engine rewards:

• Genuinely useful content that answers the question. The page that deserved to rank is the page a model is happy to read and repeat. This is still the biggest lever by a distance.
• Crawlability. A clean sitemap and a robots.txt that lets the crawlers in were always table stakes. The skill transfers directly, you just have new bots to allow (GPTBot, ClaudeBot, PerplexityBot, Google-Extended).
• Topical depth and clear structure. Headings that map to real questions, plain answers near the top, no burying the point. An SEO already writes this way; assistants reward it even more.
• Technical hygiene. Fast pages, sensible internal links, no broken canonical mess. None of that stops mattering.
• Owned profiles kept accurate. The instinct to claim and complete your G2, Trustpilot, LinkedIn, Crunchbase and Wikidata entries pays off the same way, accurate facts in places the model trusts.

The new work is mostly a change of aim rather than a change of craft. Four things matter that an SEO-only playbook either skips or treats as an afterthought:

1. 1

   Write to the question, in the format the question implies

   A 'best X for Y' query wants a guide that names the field and weighs the options, not a product brochure. Write the page so a model can lift a clear, correct answer straight out of it, with you named in the right place.

2. 2

   State your facts in structured data

   Schema.org JSON-LD, Organization and FAQPage, puts your facts in a form the model can read without guessing. Here, FAQPage is for the model to read, not for a Google rich snippet, and you never put a made-up or aggregated rating in your own markup.

3. 3

   Open the door to the AI crawlers specifically

   A robots.txt that allows GPTBot, ClaudeBot, PerplexityBot and Google-Extended is load-bearing: if the bots can't read you, nothing else counts. An llms.txt file is cheap hygiene that hints at your priority pages; adoption is still partial, so treat it as a bonus, not the main event.

4. 4

   Measure mentions, not rankings

   You stop asking 'what position am I?' and start asking 'when a buyer asks the assistant, am I named, and how often?' That means reading the actual answers across engines, repeatedly, because answers vary run to run.

There's also a timing difference worth knowing. Retrieval engines (Perplexity, and the web-search modes of ChatGPT and Gemini) reflect a new page within days of crawling it, so some wins are fast. A model's built-in training memory only shifts when it is retrained, so other wins build over time. Publish, then keep checking the answers.

The reason to care is what happens to the click. When Google shows an AI summary, people click through to a result on only 8% of visits, versus 15% without one (Pew Research Center, 2025). The link is no longer the prize the way it was, being the name in the answer is. That is the whole shift from SEO to AEO in a single number.

So the practical move is not to drop SEO. It's to take the pages you already have, point them at the questions buyers actually ask an assistant, make them readable by the models, and then watch whether the recommendation moves. MentionLM does the watching part, it asks the engines your buyers' questions and shows whether you get named, or a rival does instead.