01
On-page signals
Schema markup, FAQ blocks, page structure, crawl access, and entity consistency. Necessary but not sufficient — AI engines weight these less than traditional search does.
solutions · answer engine optimization
Answer engine optimization (AEO) is how brands earn citations in ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. It’s the AI-search successor to traditional SEO — and the brands that start now will own the citations buyers see in 2026 and beyond.
Answer engine optimization (AEO) is the practice of structuring your brand and content so that AI engines cite you when buyers ask category questions. Where SEO competes for ranked positions on a search-results page, AEO competes for the citation slot inside an AI-generated answer.
The signals overlap with traditional SEO — authority, structured data, content depth — but AEO weights surfaces SEO ignores. Reddit threads. YouTube transcripts. G2 reviews. Q&A archive answers. Those surfaces drive a disproportionate share of AI citations across every major engine.
You’ll see this called generative engine optimization (GEO) in academic papers and trade press. It’s the same thing. Throughout this page we use AEO — the term most teams have adopted — but the concept is identical.
35%
of US consumers use AI for product discovery vs 13.6% who use traditional search.
Similarweb, Jan 2026
-61%
drop in organic CTR on informational queries when an AI Overview appears.
Seer Interactive, Sep 2025
62%
of Google AI Overview citations now come from pages outside the organic top 10. Ranking no longer guarantees the citation.
Ahrefs, 2026
The buyer journey has moved. Discovery and evaluation are already happening in AI engines; final-purchase intent is at near-parity. If your brand isn’t cited where buyers are asking, a competitor is taking that citation slot. See the full state of AI search →
Effective answer engine optimization works on all four pillars in parallel. Most tools cover one or two; a complete AEO program needs all of them.
01
Schema markup, FAQ blocks, page structure, crawl access, and entity consistency. Necessary but not sufficient — AI engines weight these less than traditional search does.
02
Reddit threads, YouTube content, G2 reviews, Q&A archive answers, niche industry forums. Reddit alone appears in ~40% of all AI citations across the major engines.
03
Domain authority, link-prospect specificity, and which media outlets cite you. Each engine has a distinct authority bias — per-engine citation studies show Claude leaning toward legacy journalism, Perplexity toward research sources, and Gemini toward professional networks.
04
What gets measured gets fixed. Knowing which prompt × engine cells you win, lose, or tie tells you where to invest. Without tracking, AEO is guesswork.
An AI SEO platform turns AEO from guesswork into a measurable, repeatable process. The four-pillar workflow below is how LLMRanks does it — same loop on every tier, credit-based pricing, all six engines available.
step 01
Crawl every page, render the way AI bots do, score AI-readiness against a 23K-word knowledge base. Add engines to the audit scan when you want broader visibility coverage.
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step 02
Every AI-readiness, schema, content, internal-linking, and cannibalization issue surfaces as a what / why / how card sourced from the SEO Brain.
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step 03
Articles built to be cited by AI search. Brand-grounded, AEO-structured, schema-matched, and ready to publish.
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step 04
Reddit threads, YouTube videos, and news pieces feeding your category — with verified contacts and Gmail-SMTP send. No data brokers.
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Each engine has a different citation pattern. See the full citation index →
Answer engine optimization (AEO) is the practice of structuring your brand and content so that AI engines like ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews cite you when buyers ask category questions. It's the AI-search successor to traditional SEO: instead of competing for blue links, you compete for the citation slot inside an AI-generated answer.
Traditional SEO optimizes for ranked positions on a search-results page. AEO optimizes for the sources an AI engine pulls into its answer. The signals overlap (authority, structured data, content depth) but AEO weights surfaces SEO ignores — Reddit threads, YouTube transcripts, G2 reviews, Q&A archives — because those are where AI engines disproportionately source their answers.
Answer engine optimization (AEO) and generative engine optimization (GEO) are used interchangeably in the category. GEO is the term you'll see in academic papers and trade press; AEO is the term most marketing teams have adopted. Both describe the same thing: making your brand findable inside AI-generated answers.
Any brand whose buyers ask AI engines about their category before buying. That's now the majority of buyers — 35% of US consumers use AI for product discovery vs 13.6% who use traditional search (Similarweb, January 2026). If you sell B2B SaaS, e-commerce, professional services, or anything researched online, your prospects are already asking AI about you or your competitors.
We track your brand across all six major AI engines (ChatGPT, Claude, Gemini, Perplexity, AI Overviews, Grok), identify the prompts where you're absent and why, and give you the specific fix list - articles built to be cited by LLMs, off-site outreach to Reddit / YouTube / news sources already feeding AI, crawl-blocker removal, and on-page hygiene. Audits can include the engines you choose, with the credit cost shown before you run them.
LLMRanks pricing starts at $69/mo Solo (1,000 monthly credits), $129/mo Business (2,000 credits), or $449/mo Agency (8,000 credits, multi-brand). 40% off when you pay annually. Top-up packs (1k/$69, 5k/$325, 20k/$1,200, 50k/$2,750) never expire. Article credits scale with selected length and generated images, and each action shows its estimate before you run it.
from $69/mo · 40% off annual
Audit, diagnose, generate, and run outreach — all on one credit balance. Three engines included on every plan, with Claude, Perplexity & Grok as add-ons. Cancel anytime.