Fundamentals
What Is Answer Engine Optimization?
Answer Engine Optimization (AEO) is the practice of structuring your website, content, and digital presence so AI-powered search engines can accurately understand, verify, and cite your business. When someone asks ChatGPT, Gemini, Perplexity, or Claude a question about your industry, AEO determines whether your business appears in the answer.
That is the short version. Here is the rest, including the scoring framework we use to measure it.
Why this exists now
For twenty years, the game was Google rankings. You optimized for keywords, earned backlinks, climbed the results page, and got clicks. That model still works, but a parallel system is growing fast.
According to Gartner's 2025 predictions, traditional search engine volume is expected to drop 25% by 2026. When someone asks ChatGPT "best accountant in Brooklyn" or Gemini "who does commercial roof coatings near me," the model returns a direct recommendation. Not a list of links. If your business is not in that recommendation, no amount of Google ranking helps with that specific user.
We track this shift using canonry, the open-source, agent-first operating system for AEO. It runs agents that ask AI models the same queries your customers would ask and records whether they mention a specific business. In one dataset (66 checks across 11 keywords for a local service business), branded queries got cited 82-90% of the time, while informational queries where the business had no content got cited 0% of the time. The gap is not gradual. It is binary.
How AEO differs from SEO
| SEO | AEO | |
|---|---|---|
| Goal | Rank in search results | Get cited in AI answers |
| Output | Blue links, snippets | Direct recommendation by name |
| Key signals | Backlinks, keywords, page speed | Structured data, entity clarity, extractability |
| Measurement | Rankings, clicks, impressions | Citation presence, competitor mentions, answer text |
| Update cycle | Continuous crawling | Model re-indexing (less predictable) |
The critical difference: in SEO, you compete for position on a results page. In AEO, you compete for inclusion in a single generated answer. There is no "page two." You are either mentioned or you are not.
The 16 factors: how we actually measure AEO
Our free onsite technical audit scores any webpage across 16 onsite technical signals and returns a normalized score out of 100 with per-factor breakdowns. The signals are a practical readiness model, not proof that a page will be cited.
Here are the current default signals. Their raw weights sum to 111 and are normalized in the overall score:
| Factor | Raw weight | What it measures |
|---|---|---|
| Structured Data (JSON-LD) | 12 | Schema markup types, property depth, entity connections |
| Content Depth | 10 | Word count, heading hierarchy, paragraph structure, lists |
| E-E-A-T Signals | 8 | Author attribution, credentials, team pages, expertise claims |
| FAQ Content | 8 | Question-answer pairs, FAQPage schema, question-based headings |
| Citations & Authority | 8 | External references, source links, credibility markers |
| Schema Completeness | 8 | Coverage of required and recommended properties per schema type |
| Entity Consistency | 7 | NAP consistency, sameAs links, cross-platform entity verification |
| Content Freshness | 7 | Publish dates, update dates, recency signals |
| Content Extractability | 6 | Content-to-markup ratio, semantic HTML, page builder overhead |
| Definition Blocks | 6 | Opening definitions, "X is Y" statements, extractable descriptions |
| Named Entities | 6 | Business names, people, locations, specific services mentioned |
| Snippet Eligibility | 6 | Direct-answer formatting, lists, tables, and concise answer blocks |
| AI Access Files | 5 | llms.txt, sitemap, and related access files |
| Schema Validity | 5 | JSON-LD parseability and valid schema fields |
| Technical SEO | 5 | Canonicals, indexability, metadata, headings, and image alt text |
| AI Crawler Access | 4 | Robots.txt rules for relevant crawlers |
Real scores: optimized vs unoptimized
Here is a point-in-time comparison from an earlier monitored dataset. It illustrates the diagnostic categories, not the current package's factor values:
| Factor | Site A (90/100, gets cited) | Site B (48/100, never cited) |
|---|---|---|
| Structured Data | 100 (A+) | 42 (F) |
| AI Access Files | 100 (A+) | 56 (F) |
| Schema Completeness | 100 (A+) | 55 (F) |
| Entity Consistency | 86 (B) | 42 (F) |
| Content Extractability | 65 (D) | 45 (F) |
| Definition Blocks | 70 (C-) | 0 (F) |
| E-E-A-T Signals | 80 (B-) | 25 (F) |
Site A gets cited on 5 of 11 tracked keywords across 66 canonry monitoring runs. Site B gets cited on 0 of 23 keywords. Both are real sites tracked with canonry over two weeks.
The takeaway: even Site A has room to improve (65 on extractability, 70 on definition blocks). Perfect scores are not required for citation, but the floor is higher than most businesses expect.
The three layers of AEO
1. Technical signals
The structured data and crawlability layer:
- JSON-LD schema for LocalBusiness, Service, FAQPage, Person. See our schema guide for implementation details.
- llms.txt as an emerging machine-readable site summary. Support differs by provider, so it complements rather than replaces crawlable HTML and a sitemap.
- Robots.txt aligned with the current crawler guidance for the providers you want to allow.
- Clean HTML with semantic headings and minimal JavaScript rendering dependencies.
2. Content signals
Formatting for extraction:
- Definition blocks. Clear "X is Y" statements near the top of key pages. Site B scores 0/100 here because no page opens with a definition. They are a straightforward way to make a core fact easier to extract.
- Question headings. H2s phrased as questions matching how users query AI.
- Direct answers. First sentence under each heading answers the question. Then elaborate.
- Factual density. Concrete, sourced facts over vague claims. This makes a page easier to verify and quote.
3. Authority signals
Confidence builders for AI models:
- Entity consistency across website, Google Business Profile, directories, and social media. BrightLocal's research covers why inconsistency erodes trust.
- Reviews and ratings on Google, Yelp, and industry platforms.
- E-E-A-T signals. Author attribution, credentials, expertise/authoritativeness/trust signals.
How to measure your AEO
Run your site through the free audit to get a score on all 16 factors, specific findings, and prioritized recommendations. You can review the full technical methodology before acting on the score.
For ongoing monitoring, canonry tracks whether AI models actually cite you for your target queries. The audit tells you what to fix. Canonry tells you if it worked.
The free audit is the quick way to establish the baseline before monitoring.
Where to start
- Audit your site. Get your baseline score across all 16 factors.
- Fix structured data first. It has the highest base weight in the current model.
- Add definition blocks. Make each key page's core proposition easy to extract.
- Publish llms.txt. Use it as a supplementary access file, alongside crawlable HTML and a sitemap.
- Start monitoring. Citation changes take weeks to appear. Start tracking now so you have data when they do.
The full methodology covers each step. The tools are free. The data is what matters.
FAQ
What is answer engine optimization?
Answer Engine Optimization (AEO) is the practice of structuring your website content, metadata, and digital presence so AI-powered search engines like ChatGPT, Gemini, Claude, and Perplexity can accurately understand, verify, and cite your business in their answers.
How is AEO different from SEO?
SEO optimizes for ranking in search results pages. AEO focuses on making a business easier for AI-powered search to understand and cite. SEO focuses on links and clicks; AEO adds structured data, entity clarity, and content extractability. Our audit assesses 16 onsite technical signals.
Do I still need SEO if I do AEO?
Yes. AEO builds on SEO fundamentals. In our monitoring data, sites with strong SEO foundations respond faster to AEO improvements. But SEO alone is not enough because AI models weight structured data and content formatting differently than Google's ranking algorithm.
Is AEO the same as GEO?
GEO (Generative Engine Optimization) is another term for the same practice. Some use AEO, some use GEO, some use AI SEO. They all refer to optimizing for AI-powered search systems.
Start with the free onsite technical audit.
Get a technical baseline, then work with Canonry Managed when you want strategy and execution from one team.