Answer Engine Optimization: How to Get Cited by ChatGPT, Perplexity & AI Overviews
This is a deep dive from our roundup of 25 AI prompts and workflows that speed up SEO turnaround time. Here we focus on the fastest-growing surface in search: getting cited inside AI answers.
Ranking is no longer the whole game. When ChatGPT, Perplexity, and Google’s AI Overviews answer a question, they quote a handful of sources — and if you’re not one of them, the click never happens. Citation is the new click. The four workflows below are how practitioners are earning those citations and measuring whether it’s working.
Rewrite the intro to lead with the answer
Abram Ninoyan’s highest-leverage move is restructuring pages that rank but don’t get cited. The problem is usually the same: the answer is buried in paragraph three, after an obligatory intro. His prompt:
“List the 5 questions a user might have that this page answers. For each, write a 2-sentence opening that answers it directly and could stand alone as a cited excerpt.”
He picks the best fit and drops it in as the new opening. What used to take 45+ minutes per page now takes under 10. The remaining bottleneck is judgment — deciding which single question each page should own.
Score buyer questions across every engine
Sairam Sivakumar runs ten fixed buyer questions per company across ChatGPT, Claude, Perplexity and Google AI Overviews, and scores every answer twice — once for whether the company is named, once for which domains got cited as evidence. The critical design choice: never ask an engine to rate a vendor (that produces flattery). Ask the question a buyer would actually type, then score whatever comes back. That turns a day of reading answers into a scored dataset he can track month over month.
Get onto the “best X” lists AI quotes back
Borja Obeso points out that what AI assistants quote back is overwhelmingly “best X” list pages — so getting added to those lists is a distribution problem worth automating. His three-stage workflow: pure SERP search builds ~1,264 candidate list pages; the model then filters each one (title, URL and meta description only) with a single yes/no instruction and a reason under ten words, leaving ~33 realistic targets; a final pass extracts each page’s stated ranking criteria so the pitch references what the writer said they cared about. The whole trick is triage, not generation — one decision per call, a forced output shape, and a hard cap on reasoning length.
Find the prompts where you’re invisible
Joe Della built GroundScore.ai for his own agency to close the gap between where buyers ask and where you appear. It surfaces what people ask about your business in AI prompts, shows where you’re mentioned in AI answers, generates content around the prompts where you’re not cited, and flags where competitors show up in spaces you don’t. It’s a way of making AEO measurable rather than anecdotal.
The takeaway
AEO (also called generative engine optimization, or GEO) rewards a different shape of content than classic SEO. Answers need to sit in sentence one and stand alone as a quotable excerpt; you need to know which “best X” lists the engines pull from; and you need to measure citations, not just rankings. The mechanics of how to structure those pages — schema, entities, and a consolidated JSON-LD graph — are covered in our technical SEO automation guide.
Read the full collection: 25 AI Prompts and Workflows That Speed Up SEO Turnaround Time »
Related deep dives: AI for SEO research & planning · Technical SEO automation
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