Answer engine optimization (AEO) is the practice of getting your business named and cited inside the answers ChatGPT, Perplexity, Gemini and Google AI Overviews generate, rather than only ranked as a blue link. There are four acronyms for this discipline, AEO, GEO, GSEO, LLMO, and one playbook. The proliferation is a marketing artifact, and treating them as separate services with separate budgets is the most common way to overpay for this work.
What does differ, materially, is the engine. ChatGPT's search layer leans on Bing's index. Perplexity draws roughly 46.7% of its top citations from Reddit. Google AI Overviews fan a query out into dozens of background searches and cite at the sentence level. Those differences change what you fix first.
This guide covers the shared foundation, then the per-engine tuning, side by side. It is the hub for our AI search cluster: if you arrived with a specific symptom, such as your website not showing up in ChatGPT, each section below links to the deeper post.
What is answer engine optimization?
Answer engine optimization is structuring your content and your presence across the web so an AI system can find, trust and quote you when it writes an answer. Traditional SEO competes for a position in a list of links. AEO competes for a sentence inside the generated answer, which the user may read without clicking anything.
The unit of work shifts accordingly. SEO optimizes pages for keywords and backlinks. Answer engine optimization optimizes individual claims: a definition that stands alone, a number with a named source, a price or a service area stated in plain text. It also reaches off your site, because answer engines lean on review sites, directories and forums to confirm what you say about yourself. Roughly 80% of the work still overlaps with SEO, which is why the foundation below comes first.
The shared foundation (roughly 80% of the work)
Every answer engine retrieves from a search index and generates from what it retrieves. That single fact makes most of the work common across all of them.
- Be indexed and eligible. No index entry, no citation, there is no markup that substitutes. Roughly 94.8% of sites never appear in AI answers at all, so absence is the default rather than a penalty.
- One canonical host. Pick www or non-www, redirect permanently, and make canonical tags, sitemap and internal links agree.
- Render server-side. If content only appears after JavaScript executes, assume some agents never see it.
- Answer in extractable sentences. Lead each section with a direct one-to-two sentence answer that stands alone out of context. This is the highest-leverage writing change available and it costs nothing.
- Attach a statistic and a named source to every meaningful claim. Statistics increase AI visibility by about 22% and quotations by about 37%.
- Stay fresh. Around 85% of AI Overview citations come from content published within two years.
- Earn genuine third-party presence. Reddit is the single most-cited domain across every major engine. Manufacturing mentions is explicitly counterproductive. Google's guidance names it and its spam systems target it.
Do those seven and you are most of the way there on every engine simultaneously. The rest is tuning.
Engine by engine: what actually differs
| ChatGPT | Perplexity | Google AI Overviews | |
|---|---|---|---|
| Retrieval index | Bing | Own crawl + Bing layer | Google Search index |
| Correlation to rankings | ~87% match Bing top results; ~10% in Google top 10 | ~60% overlap Google top 10 | Built directly on core Search |
| Signature mechanic | Separate bots for training vs. search | ML reranker + freshness decay | Query fan-out, passage-level citation |
| Heaviest off-site source | Reddit, review sites, roundups | Reddit (~46.7%) | Reddit; LinkedIn for professional queries |
| Fix first | Bing Webmaster Tools indexation | Crawler access + third-party presence | Index coverage + adjacent-question depth |
| Speed to reflect changes | Slowest | Fastest | Moderate |
ChatGPT, the Bing problem
The single most common reason a site is invisible in ChatGPT has nothing to do with writing: it is not in Bing's index. You can dominate Google and be absent here.
Fastest diagnostic: search site:yourdomain.com in Bing. If your pages are missing, verify in Bing Webmaster Tools and submit your sitemap, it imports directly from Google Search Console, so it is roughly fifteen minutes of work and it is the highest-value unblocked fix for most sites.
Worth knowing: blocking crawlers matters far less than people assume. Sites blocking GPTBot were still cited 88.2% of the time across an analysis of 4 million citations, because citations frequently come from third parties describing you rather than from a crawl of your pages. Once Bing has you, the fixes that follow are in how to rank on ChatGPT.
Perplexity, the Reddit problem
Perplexity's citation mix is unusually weighted toward community sources: roughly 46.7% of its top citations come from Reddit.
The strategic consequence is uncomfortable but clear: your own website is a minority of the battle. If your category is discussed on Reddit and your brand never appears there, Perplexity has little to retrieve about you no matter how good your pages are. Perplexity also applies noticeable freshness decay, so cornerstone pages need updating on a schedule. Full breakdown in how to get cited by Perplexity AI.
Google AI Overviews, the eligibility problem
Here the gate is upstream of optimization. Only about 274,455 domains have ever appeared in an AI Overview, out of roughly 18.4 million indexed, about 1.5%.
Two mechanics change tactics once you are through the gate. Query fan-out means Google generates dozens of related background searches and assembles one answer, so AI Overviews routinely cite pages that do not rank for the original query. And citations are awarded at the passage level. Google stitches answers from sentence fragments, so the unit you optimize is the sentence, not the page. Details in how to show up in Google AI Overviews.
We audit all three engines together. Bing indexation for ChatGPT, third-party presence for Perplexity, eligibility and fan-out coverage for AI Overviews, and hand you a prompt panel showing exactly where competitors get named and you do not.
Citations vs mentions: what answer engine optimization actually measures
An AEO program needs two numbers, not one: how often your page is cited as a source, and how often your brand is named in the answer. They move independently, and both are unstable from run to run, so any single screenshot is close to meaningless.
AirOps' research puts numbers on the instability. Only about 30% of brands stay visible from one AI answer to the next, only about 28% of answers both mention and cite the same brand, and brands that earn both are 40% more likely to resurface across runs. The engines also disagree with each other: an r/SEO member who ran 3,837 API calls across four engines found "53% of pairwise provider comparisons showed statistically significant differences."
Practitioners in r/bigseo have started pushing past raw citation counts. One thread on AEO measurement proposed tracking recommendation share on commercial prompts, how each brand is framed, which third-party sources seem to drive the answer, and "whether the answer is consistent enough over repeated runs to be worth optimizing for." That last test is the one most dashboards skip.
The practical setup is a fixed panel of 20 to 40 buyer prompts, run logged out on a schedule, logged per engine. Our walkthrough on checking whether AI recommends your business covers the manual version, and the best AI visibility tools compares the paid ones. For a local business the same logic applies to the map layer: if your business is not showing up on Google at all, fix that before measuring anything in AI answers.
Why four acronyms exist
Worth being direct, because it saves money.
AEO, GEO, GSEO and LLMO emerged from different corners of the industry describing the same shift: search moving from returning links to generating answers. No engine implements an "AEO algorithm" distinct from a "GEO algorithm." Google's own guidance addresses AEO and GEO together and, notably, spends a section telling you which associated tactics you can ignore, llms.txt, content chunking, AI-specific rewriting, and structured data for generative features.
The practical filter: if a proposal prices AEO and GEO as separate line items, ask what a deliverable in one bucket does that the other does not. There usually is not an answer. Our seven tests for vetting a GEO agency covers the rest of that conversation.
A sequenced 30-day plan
Week 1, eligibility. Confirm indexation in Google and Bing. Fix canonical host consistency. Verify server-side rendering. Check robots.txt and any WAF bot filter above it. Nothing below matters until these pass.
Week 2, extractability. Take your five highest-intent pages and rewrite each section to open with a self-contained one-to-two sentence answer. Add a statistic with a named source to every meaningful claim. Strip narrative build-up.
Week 3, coverage. Map the 6–12 adjacent questions your core topics fan out into, and cover them as headings or sibling pages. This is what earns fan-out retrieval.
Week 4, presence and measurement. Identify where your category is genuinely discussed and participate honestly. Stand up a fixed panel of 20–40 buyer prompts and record a baseline across engines.
The honest summary
Answer engine optimization is competent technical SEO, plus writing that survives extraction, plus existing credibly where the engines already look. The acronym you use for it does not matter. The engine you are losing on does.
Start with generative engine optimization for the underlying theory, or GEO vs SEO if you are deciding how to split budget. Canadian businesses may also want the Canada-specific data. For a trade-specific worked example, ChatGPT visibility for landscapers shows how differently the same playbook lands when most prompts are design questions rather than hiring questions. And if you want the work done rather than explained, we run it as a generative engine optimization agency in Toronto.