Answer Engine Optimization (AEO) is the practice of making a brand visible, cited, and recommended inside AI-generated answers — in ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Where traditional SEO optimizes for a ranked list of links, AEO optimizes for being the answer itself: the brand an AI names when a shopper asks what to buy. You will also see the terms Generative Engine Optimization (GEO) and LLM optimization — they describe the same practice.
Why this exists now
Over 100 million people search with AI every day, and for a growing share of shopping questions the AI’s response is the whole journey: the shopper asks, reads the answer, and acts. There is no page two and no list of ten blue links. A handful of brands get named; everyone else is invisible.
This creates a structural problem the old SEO playbook cannot address. AI engines don’t rank your pages — they synthesize answers from trust signals scattered across the open web: reviews, community discussions, press citations, video transcripts, and structured data. Most brands have never deliberately managed those signals.
How AEO differs from SEO
| SEO | AEO | |
|---|---|---|
| Optimizes for | A ranked list of links | Being named in a synthesized answer |
| Primary surfaces | Google, Bing results pages | ChatGPT, Perplexity, Gemini, AI Overviews |
| Key inputs | Keywords, backlinks, on-page factors | Reviews, citations, community presence, entities, quotable content |
| Outcome metric | Rankings and clicks | Mention rate, citation share, answer position |
| Failure mode | Page two of Google | Absent from the answer entirely |
The two overlap — AI engines crawl the same web, so technical fundamentals still matter — but SEO alone is no longer sufficient. The sources AI engines weight most heavily (Reddit threads, verified review platforms, YouTube transcripts, earned press) are largely outside a traditional SEO scope.
The signals that actually move AI answers
Research and cross-engine testing consistently point to five signal families:
- Reviews and reputation — depth, recency, and sentiment of real customer reviews on platforms AI trusts.
- Citations and digital PR — mentions in publications AI engines cite. Notably, the Princeton GEO study (KDD 2024) found that verbatim-quotable content outperforms plain attributed citations (+41% vs. +28% visibility lift), because a direct quote is a self-contained unit a model can reproduce.
- Community presence — authentic participation where your category is discussed. Perplexity in particular leans heavily on Reddit.
- Structure and entity signals — schema markup, entity consistency, and content written in self-contained answer blocks that a machine can parse and quote.
- Video with transcripts — YouTube is the one social platform whose content meaningfully feeds AI answers, because transcripts are crawlable text. Google AI Overviews correlate strongly with YouTube presence.
Different engines weigh these differently — Perplexity favors community sources and recency, Google AI Overviews correlate with YouTube, ChatGPT draws on Wikipedia and comparison content — which is why single-channel efforts underperform.
The opportunity for challenger brands
AI engines default to big, recognizable names — but only in an information vacuum. The same Princeton study found a fifth-ranked site could gain roughly 115% AI visibility through citation optimization. The recognition monopoly is fragile: modest, well-placed distinguishing signals let challengers break into answers that incumbents currently own by default. The gains disproportionately favor brands that move early, while most of their category ignores the channel.
How fast does AEO work?
Honest answer: it depends on the engine. Retrieval-augmented systems — Perplexity, search-enabled ChatGPT, Google AI Overviews — index new content within days, so early movement typically shows within the first 30 days. Deeper authority (citation depth, review volume, community trust) compounds over three to six months. Claims of instant AI rankings should be treated with suspicion, and base-model updates are infrequent and outside anyone’s control, so retrieval engines are the correct measurement channel.
Where to start
Before optimizing anything, find out what AI currently says about you: run the real questions your customers ask across the major engines and look at which brands get named, which sources are cited, and where you appear — or don’t. That audit is the strategy document. Lasso runs this audit free for consumer brands, with screenshots and findings in plain business language.