GEO playbooks by industry
Industry-specific GEO starts with a real question, not a generic page containing an industry keyword. A software buyer may need compatibility, security and pricing details; a patient may need eligibility, risks and clinician qualifications. Write the answer in the language and jurisdiction of the audience, state who it applies to, and link the source of any claim. Search accessibility, useful content and trustworthy references remain important even when the final answer appears in an AI interface.
Industry-specific GEO starts with a real question, not a generic page containing an industry keyword. A software buyer may need compatibility, security and pricing details; a patient may need eligibility, risks and clinician qualifications. Write the answer in the language and jurisdiction of the audience, state who it applies to, and link the source of any claim. Search accessibility, useful content and trustworthy references remain important even when the final answer appears in an AI interface.
B2B SaaS buyers have moved their early research into ChatGPT, Gemini, Claude, and Perplexity.
guidesShoppers now ask AI for product recommendations the way they used to read reviews.
guidesPatients are asking ChatGPT before they call your front desk.
guidesFinance is the highest-trust YMYL category in AI search.
guidesLegal queries almost always start with a question, not a brand.
guidesBuyers now research neighborhoods, schools, and agents through AI.
guidesProspective students compare programs through AI before they ever fill out a form.
guidesTravelers plan entire trips inside ChatGPT and Perplexity now.
guidesClients search for agencies the way they search for SaaS — via AI.
guidesDevelopers ask AI for tooling recommendations and copy code snippets that include vendor names.
guidesDonors vet causes through AI before they give.
guidesDiners ask AI for restaurants, menus, and dietary fit.
guides
Build around the decision your audience is making
Industry-specific GEO starts with a real question, not a generic page containing an industry keyword. A software buyer may need compatibility, security and pricing details; a patient may need eligibility, risks and clinician qualifications. Write the answer in the language and jurisdiction of the audience, state who it applies to, and link the source of any claim. Search accessibility, useful content and trustworthy references remain important even when the final answer appears in an AI interface.
Choose evidence appropriate to the risk
For healthcare, finance and legal topics, name the responsible reviewer and cite current primary guidance. Include the effective date and applicable region; do not present general information as individual professional advice. For products, keep specifications, availability and prices consistent with the visible offer. For education or travel, verify eligibility, schedules, accessibility and cancellation details. No schema type or publishing frequency substitutes for accurate underlying information.
A worked example: a software integration question
For “Does this service work with our CRM?”, a useful page identifies supported versions, required permissions, setup steps, limitations and who owns support. A short comparison table can distinguish native integration, API integration and unsupported combinations. Link the actual documentation rather than inventing benchmark results. If the integration changes, revise the answer and dated limitations together; adding more general GEO paragraphs does not help the buyer.
Measure visibility without inventing industry benchmarks
Build a fixed set of relevant questions for each market and language. Record the engine, date, response, correct mention and cited URL. Monitor referral visits and business outcomes separately because many AI mentions produce no identifiable click. A before-and-after difference is an observation, not proof that schema or llms.txt caused it. There is no universal citation lift, market-share figure or guaranteed time to result applicable to every industry.
| Check | Evidence to retain | Action |
|---|---|---|
| Healthcare | Current guidance, reviewer credentials, region | Verify safety claims before publication |
| Finance and legal | Effective date, regulation, scope | Separate facts from advice |
| Commerce | Live price, availability, product specification | Sync visible facts and matching structured data |
| Software | Versioned documentation and tested steps | Explain prerequisites and failure cases |
| Local services | Actual service area, hours and contact details | Remove unsupported location claims |
Implementation checklist
- Choose questions specific to the buying or service decision.
- State the language, region and eligibility clearly.
- Attach primary sources to claims that affect a decision.
- Use structured data only for information visible on the page.
- Distinguish search crawling from model-training controls.
- Measure each audience with its own unchanged prompt set.
A repeatable workflow
- 1Establish a baseline
Save the page URL, date, language, target market and exact questions before editing. Record what the page actually says and what each tested answer cites; a mention without a source link is not a citation.
- 2Make one coherent change
Resolve the clearest failure first, then check the published page rather than only an editor preview. Keep an implementation log so unrelated redesigns, campaigns or product changes are not mistaken for the effect of this work.
- 3Repeat and compare
Repeat the same questions and technical checks after deployment. Keep engines and measurement conditions consistent, report sample size, and inspect answer accuracy alongside citations. A single response is not a stable ranking.
Frequently asked questions
Does this guarantee an AI citation?
No. A crawlable, accurate page can still be omitted. Retrieval, source selection and generated answers vary between products and requests; these checks improve the evidence available, not guarantee placement.
How do I tell whether an improvement worked?
Compare like-for-like checks and retain the underlying evidence. Track correct brand mentions, source-linked citations and qualified referral visits separately. Do not call a technical score a traffic forecast or attribute every change to one edit.
Related hubs
SEO, AEO and GEO overlap. SEO includes making pages accessible, relevant and useful for search; AEO emphasizes answering the question clearly; GEO concerns visibility and accurate representation in generated answers. They are not mutually exclusive replacements. Start with the business question: do you need more qualified visits, fewer misunderstood product answers, or a clearer understanding of citations? Choose measurements that match the task rather than declaring one discipline universally superior.
llms.txt is a proposed Markdown convention for presenting a concise site overview and curated links. It is not a robots policy, licensing agreement, authentication control or universal AI indexing requirement. An H1 site name, a useful summary and organized Markdown links help readers understand the site. The proposal does not mandate a section literally called Docs or a universal 150-character summary. Adoption differs by consumer; do not claim that every major AI crawler reads it.
A search assistant can retrieve sources at answer time, use an index or answer from model knowledge without browsing. Its crawler and training controls may be separate. Test the actual feature and question you care about rather than assuming one user-agent rule controls the whole product. The engine guides here help organize that investigation; they are not claims that the vendors publish identical ranking rules.
Local AI visibility depends on accurate business facts and useful answers for the area you actually serve. A city keyword alone is not a reason to publish another page. State genuine service coverage, contact options, hours and location-specific limitations. Do not invent an office, address, local partnership, market-share statistic or citation benchmark to make a template look more substantial.
AI-search terms often describe different layers of a system. Crawling retrieves a page; indexing organizes available information; retrieval selects material for a question; generation produces an answer. A citation is an attribution in that answer, not proof of all preceding steps. Definitions are useful when they help you locate a problem, choose an appropriate check and avoid claiming more than the evidence shows.
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