Does staying tightly on topic help AI choose my page?

Staying on topic is the best-supported content factor in the GEO research, with one large caveat about where it was measured.

A critical survey of 45 GEO studies (arXiv:2607.14035, July 2026) concluded that "topical relevance and context position are the most reproducible levers." A separate 252,000-trial factorial study (arXiv:2605.25517) found that "topical relevance and list position are the biggest drivers of being cited first." C-SEO Bench, a NeurIPS 2025 benchmark, found most citation-rewriting tactics ineffective and often harmful, with position in the context doing the heavy lifting.

The logic is plain. An engine holding a few candidate pages has to pick the ones that answer the question. The page that is genuinely about that question has the best chance. Tricks layered on top do not travel well: the same survey says "generic heuristics transfer poorly" and "citation-oriented rewrites can impair retrieval."

What it means for you: topic focus helps once your page is a candidate. It is not a route into the candidate set. See topical relevance defined for the term itself.

AI answers pass through four stages: what the model already knows, whether a crawler can access your page, whether the page is retrieved for a query, and which retrieved pages get cited. The relevance findings all sit in the last stage.

• The 252,000-trial study never called a live search engine. It used a synthetic corpus of 100 e-commerce blogs with two candidate pages per trial. Its authors work for a vendor that ships a GEO checklist.
• The 45-study survey is single-author, not peer-reviewed, and has no primary data of its own.
• C-SEO Bench simulated its "SEO" condition by moving a document to the top of the model's context, which no publisher can do.

Two interested sources agreeing is corroboration, not replication. The finding is moderate in strength, not settled. Our digest of the 252,000-trial factorial covers the design in detail, and how AI search picks sources explains each stage.

Relevance here means the page is about what the person asked. It does not mean repeating the phrase or listing every variant.

The original GEO paper (arXiv:2311.09735) found keyword stuffing decreased its Position-Adjusted Word Count metric, scoring 17.8 against a 19.5 baseline. Google's guide to generative AI features says you "don't have to worry that you don't have enough 'long-tail' keywords or haven't captured every variation of how someone might seek content like yours."

Say you run a dental clinic in Austin and someone asks what a crown costs without insurance. A relevant page states the price range, what changes it, and how long the work takes. A page that repeats "Austin dental crown cost" ten times adds words, not fit. Formatting does not substitute either: the factorial found formatting-only edits had little impact, as covered in do headings and bullet lists help AI quote my pages.

Relevance is judged against a query you never see. OpenAI's help page says ChatGPT search rewrites a prompt into one or more targeted queries. Google may fan out a question into several related searches, and the Gemini API generates its own queries. As of October 2026, no engine exposes those queries in an API.

So you cannot optimise for an exact retrieval query. You can only cover the real question well.

Relevance also cannot override the gates before it:

• Content that only appears after JavaScript runs may be invisible to non-Google AI crawlers.
• A robots.txt block on OAI-SearchBot or PerplexityBot removes eligibility for that engine.
• A firewall or CDN can turn away a crawler that robots.txt allows.

Brand prominence is another factor nobody controls in the short term. Large, well-known sources dominate citations across studies. Relevance on one page is a different idea from topic authority, and spinning up many thin pages does not widen it, as publishing more content explains.

1. Confirm access first. Check that your key facts are in the raw HTML before JavaScript runs, and that robots.txt lets each search crawler in.
2. Give each buyer question a page that answers it. Lead with the direct answer, then the conditions and specifics.
3. State specific facts plainly. A price, a number or a one-line definition gives an engine a sentence it can quote.
4. Cut padding and keyword repetition. They did not help in the studies and stuffing hurt.
5. Check where engines go instead of you. When they cite other sites, being named on those pages is the associated route in. Finding the pages AI engines cite walks through it.

To see where you stand today, the free checker on this site shows whether AI engines name you for up to three buyer questions. No change here guarantees a citation. These are the parts you control.

Is topical relevance the same as using the right keywords? No. Relevance means the page answers the question someone is asking. Keyword coverage means repeating terms and variants. The original GEO paper found keyword stuffing lowered visibility on its own metric, and Google says you need not chase every long-tail variant. Write for the question, use the words your buyers use naturally, and stop there.

Can a highly relevant page still be ignored by AI? Yes. Relevance was measured on pages already in the model's context. If a crawler cannot fetch or render your page, or a firewall blocks it, the page never becomes a candidate. Retrieval is also per query and at the engine's discretion, so some answers run with no search at all. Relevance only helps after those steps succeed.

Should I narrow my whole site to one topic? The evidence does not test site-wide focus. The relevance findings are about a single page matching a single question among a few candidates. Keep each page tightly on its question. Whether a narrower site helps beyond that is unmeasured, and site-level authority scores are not something any engine publishes.

Does rewriting a page with AI make it more relevant? Not reliably. The 45-study survey warns that citation-oriented rewrites can impair retrieval, and C-SEO Bench found most rewriting methods ineffective or harmful. If a rewrite makes the page answer the question more directly, that is an editorial improvement. Rewriting to sound quotable or AI-friendly has no credible evidence behind it.