Article
Write pages that AI answers can actually quote
A practical guide to writing GEO content with facts, comparisons, statistics, citations, and useful structure instead of stuffing keywords or pretending schema alone will save you.
Most GEO advice sounds either too mystical or too small.
On one side, people talk as if there is a secret way to make ChatGPT love your brand. On the other side, people say “just do good SEO” and stop there.
I think the useful middle is this: write pages that answer engines can quote without doing too much work.
That sounds basic, but many product pages are terrible source material. They are written for conversion, not citation. They say the product is powerful, flexible, scalable, modern, and easy to use. A human may understand the vibe. A retrieval system gets very little.
If an AI answer needs to compare five tools, your page should give it specific facts to use.
start with the buyer’s question
Do not start with the keyword. Start with the question behind the keyword.
“Best LLM observability tool” is not one question. It hides several:
- Which tools support tracing?
- Which tools support evaluations?
- Which tools work with OpenTelemetry?
- Which tools are open source?
- Which tools are better for startups?
- Which tools are better for enterprise teams?
- Which tools have hosted dashboards?
- Which tools integrate with LangChain, OpenAI, Vercel AI SDK, or custom pipelines?
- Which tools are expensive at scale?
A page that answers only the head term will feel thin. A page that covers the hidden questions has a better chance of being useful when the engine fans out the query.
I would build content around the cluster instead of the phrase alone.
write with quotable facts
Answer engines need material. Give them material.
Bad:
Our platform helps teams monitor AI applications with a flexible, reliable workflow.
Better:
The platform records traces, prompts, model responses, latency, token usage, cost, user feedback, and evaluation results in one timeline. It supports OpenAI, Anthropic, LangChain, LlamaIndex, and custom HTTP integrations.
The second version is not prettier. It is more useful.
For GEO content, useful beats elegant. I want concrete nouns, numbers, supported integrations, limits, tradeoffs, and examples.
If you have data, use it. If you do not have data, do not invent it. This market already has enough fake confidence.
Primary data
Academic papers, large datasets, official docs, and studies where the method is visible.
Use for claims.Industry reporting
Funding news, interviews, media reporting, and vendor data repeated by credible outlets.
Use for market direction.Vendor posts
Agency case studies, marketing reports, and self-published experiments.
Use as leads, not proof.Good source material includes:
- pricing limits and plan differences
- supported integrations
- benchmark methodology
- migration steps
- customer segments
- deployment options
- security and compliance details
- known tradeoffs
- screenshots or product flows
- docs that explain edge cases
- comparison tables with honest criteria
The “GEO: Generative Engine Optimization” paper is often quoted for the “up to 40 percent” visibility improvement claim. I would be careful with that number because the experiment has limits and some follow-up criticism is fair. Still, the tactics that showed stronger results are directionally sensible: adding citations, adding statistics, and adding quotations.
That does not mean “sprinkle fake stats.” It means pages with evidence give the model better material.
build comparison pages that do not embarrass you
Comparison pages are useful because buyers ask comparison questions.
They are also easy to make gross.
The lazy version is:
Competitor is old and limited. We are modern and flexible.
Nobody needs that page. It does not help a buyer, and I doubt it helps an answer engine much either.
A better comparison page admits where each product is strong.
For a developer tool, I would include:
- primary use case
- best fit team size
- hosted vs self-hosted support
- open source status
- SDK and framework support
- pricing model
- data retention
- observability depth
- security features
- migration difficulty
- when not to choose this product
That last line matters. “When not to choose us” sounds scary, but it makes the page more credible. It also gives the engine clearer boundaries. If a product is not good for enterprise procurement yet, saying so may lose a bad-fit lead and win trust with everyone else.
cover the boring support pages
I suspect a lot of GEO work will look like boring documentation cleanup.
Does the docs site explain what the product is? Do integration pages have enough detail? Do changelog entries use product names and feature names clearly? Do tutorials answer real implementation questions? Does the pricing page explain limits in normal words?
AI answers often cite pages that are useful, not pages that are trying hardest to sell.
For developer products, docs may be more important than the marketing site. A model trying to answer how do I connect {product} to LangChain is not looking for your homepage. It wants the integration guide.
The same logic applies outside developer tools. If buyers ask implementation questions, your implementation pages need to exist.
make source trails visible
If you cite a number, link the source. If you quote a customer, name the context. If you claim a benchmark, explain the setup. If you compare tools, say when the comparison was last updated. This is not only a GEO trick. It is close to the plain old advice in Google’s helpful content guidance: make pages useful to people first, and do not hide the evidence behind the claim.
This is good for humans. It is also good for machines.
I would rather publish a smaller page with honest citations than a giant “ultimate guide” full of unsourced claims. The web has too many ultimate guides already. Most are not ultimate. Many are barely guides.
avoid the GEO cargo cult
Some tactics are probably hygiene, not strategy.
Schema is useful. Clean HTML is useful. Fast pages are useful. Clear headings are useful. llms.txt may become useful in some contexts. But none of these fix a page that says nothing.
A page with structured data and no facts is still empty.
A page written in Markdown and stuffed with vague claims is still vague.
A page that lists competitors but gives no criteria is still not a good comparison page.
The practical test is simple:
If an answer engine wanted to recommend your product, what exact sentence would it use?
If you cannot find that sentence on your own site or in a trusted third-party source, you have work to do.
a simple content checklist
Before publishing a GEO-focused page, I would check:
- Does it answer one real buyer question?
- Does it cover the follow-up questions around that decision?
- Does it include specific facts rather than adjectives alone?
- Does it name integrations, limits, use cases, and tradeoffs?
- Does it cite sources for statistics and benchmarks?
- Does it include a short, accurate product description that a model could reuse?
- Does it explain who should not use the product?
- Does it link to docs, comparisons, pricing, and relevant third-party proof?
- Does it avoid fake certainty?
That is not glamorous. It is not a hack.
But the more I read about GEO, the more I think the winning content will be aggressively useful and a little less self-flattering than normal marketing pages.
That is probably a good thing.