SEO / AEO / GEO12 min read
SEO, AEO, and GEO: One Practical Approach to Modern Search
Search did not disappear when answer engines arrived. Discovery expanded. The same business now needs to be crawlable, directly useful, and credible enough to be selected as a source.
By Dan Grams, Founder & Principal Consultant
My take
SEO earns discoverability in search indexes, AEO structures clear answers for answer surfaces, and GEO strengthens the evidence and entity signals that can help generative systems select and cite a source. They work best as one connected content system grounded in evidence.
What matters most
- Protect crawlability and indexability before adding new content formats.
- Answer the real question early, then support the answer with evidence and nuance.
- Make authorship, dates, entities, and primary sources unambiguous.
- Measure qualified discovery and conversions; readiness is not visibility.
Three labels, one discovery system
SEO is the foundation that helps a search engine crawl, understand, index, and rank a page. AEO makes important questions easy to identify and answer directly. GEO is the practice of making a source clear, supportable, and entity-rich enough to be useful in generative retrieval and synthesis.
The labels are helpful for diagnosing gaps. They are harmful when sold as three disconnected checklists. A technically perfect page with vague claims is weak. A brilliant answer that crawlers cannot fetch is invisible. A well-structured claim without evidence is hard to trust.
There is no magic AI-search tag
Google’s guidance for its AI search features points site owners back to established Search requirements rather than a new AI-only markup system. Structured data remains useful when it accurately represents visible content, but adding schema does not force a citation or an answer placement.
The practical work is less glamorous: clean status codes, intentional robots directives, canonical consistency, useful internal links, fast rendering, and content that resolves a real question better than the alternatives.
Write answer-first, not answer-only
Put the concise answer near the question. Then earn it with definitions, process, evidence, examples, limitations, and the conditions under which the answer changes. This serves a hurried reader and gives a retrieval system a coherent passage to work with.
Short does not automatically mean authoritative. The goal is a compact claim with enough surrounding proof that another system can safely reuse it.
- Use descriptive headings that mirror how buyers frame the problem.
- Distinguish facts, reported outcomes, estimates, and opinions.
- Link to primary sources near the claims they support.
- Keep ownership, author identity, publication date, and update date visible.
- Use stable URLs for services, entities, case studies, and definitions.
Crawler access needs role-level decisions
Not every bot from one provider performs the same job. Search indexing, user-requested retrieval, and model training can use different crawler identities and controls. A sound policy documents the business decision for each role rather than calling every bot ‘AI access.’
Robots rules express crawler preferences; they do not create visibility. Missing rules should not be misreported as a block, and allowing a crawler should never be scored as proof that a model can find or cite the company.
Measure outcomes in layers
Technical readiness can be audited from the outside. Actual visibility requires observation: search performance, referral analytics, assisted conversions, prompt sampling with a documented method, and first-party platform reporting when it is available.
Keep those layers separate. A readiness score can prioritize implementation. It cannot honestly tell you how often an answer engine recommends the brand.