GEO: How to Get Your Business Recommended by ChatGPT and AI Search

You cannot force ChatGPT or another AI search tool to recommend your business. You can make the business easier to discover, understand, verify, and cite—and that is the practical work of generative engine optimization.

GEO is not a secret schema tag or a new file you add to a website. In practical terms, generative engine optimization for business is the discipline of improving how a brand and its expertise appear in answers generated from search indexes, live web retrieval, business data, and supporting sources. Good GEO combines technical access, clear facts, useful content, conventional SEO, and evidence beyond your own website.

For a local business, the opportunity is straightforward. When someone asks an AI tool for “a GTA realtor who understands investment properties” or “how to choose a basement contractor in Vaughan,” you want your site and reputation to contain reliable information that could support the answer. There are no guaranteed placements. There is, however, plenty of work that improves your eligibility.

What is generative engine optimization?

Generative engine optimization is the process of improving a source’s visibility and usefulness within AI-generated answers. The term was formalized in the research paper “GEO: Generative Engine Optimization”, later published at KDD 2024, which studied methods for increasing the visibility of source content in generative-engine responses.

Traditional SEO usually focuses on whether a page is crawled, indexed, and shown for a query, followed by how often searchers click it. GEO asks related but different questions:

• Can an answer engine retrieve the page or the underlying facts?

• Does the page contain a clear answer to the specific question?

• Are important claims supported by evidence?

• Is the business described consistently across credible sources?

• Does the answer cite, mention, or meaningfully use the source?

• Does that visibility lead to qualified visits, branded searches, or inquiries?

The difference should not be exaggerated. Google says the same SEO fundamentals remain relevant for AI Overviews and AI Mode, and that no additional technical requirement or special schema is needed (Google Search Central). Our view is simple: GEO sits on top of strong SEO; it does not replace it.

That matters for business owners because “AI optimization” is already attracting dubious promises. Be cautious if someone guarantees a recommendation, sells an `llms.txt` file as the whole strategy, or claims keyword repetition will make a language model trust you. The major platforms use different systems, sources, and retrieval methods. They change quickly. A durable plan improves the quality and consistency of the business’s public evidence instead of betting everything on one trick.

How does ChatGPT find and cite business information?

ChatGPT search can use information from the public web and may provide citations and links to relevant sources. OpenAI says any public website can appear in ChatGPT search and advises publishers not to block OAI-SearchBot if they want content to be discoverable for summaries and snippets (OpenAI Help Center).

That guidance establishes a necessary condition, not a ranking formula. Allowing a crawler does not mean a site will be selected. ChatGPT search may also work with third-party search providers, and the system can rewrite a user’s request into more targeted searches before composing an answer (OpenAI Help Center).

For a business, this creates several ways information can enter the answer:

1. The business’s own website provides a clear, accessible page.

2. Search indexes surface that page for a related subquery.

3. Trusted third-party pages mention or review the company.

4. Business listings and maps provide location, category, hours, or contact data.

5. A current article answers a question well enough to become supporting evidence.

The exact mix varies by prompt and product. A request for nearby restaurants may lean heavily on structured local data. A question about renovation planning may use articles, municipal guidance, and contractor pages. A request to compare agencies may use service pages, case studies, reviews, and independent lists.

This is why a business needs more than a home-page slogan. An answer engine cannot infer a precise specialty from “we make your vision real.” It works with the information available. Clear service descriptions, location coverage, named expertise, and well-supported articles give it better raw material.

What technical work makes a site eligible for AI search?

The technical priority is to make important pages crawlable, indexable, fast, and available as real text. If a bot or search engine cannot access the content, every later GEO tactic is built on sand.

Start with `robots.txt`. OpenAI distinguishes OAI-SearchBot, used for search discovery, from GPTBot, which publishers can block on pages they want excluded from potential training (OpenAI’s publisher FAQ). That distinction matters: a business can make a deliberate decision about search visibility and training rather than treating every OpenAI user agent as the same thing.

Then check the rest of the retrieval path:

• Important pages return a normal `200` response without a login or bot challenge.

• Canonical tags identify the preferred version of each page.

• The XML sitemap includes current, indexable URLs.

• Core services are reachable through normal internal links.

• Main facts appear in HTML text, not only inside images, video, or scripts.

• Titles and descriptions accurately summarize each page.

• LocalBusiness or Organization structured data matches what a visitor can see.

• Google Business Profile and Bing Places details are current.

• Mobile visitors can read the page and complete a form without friction.

Google specifically recommends crawl access, internal links, good page experience, textual content, accurate structured data, and current Business Profile information for its AI features. It also states that sites do not need a special AI text file or new machine-readable markup (Google Search Central).

Microsoft takes a similar foundations-first view. Bing recommends sitemaps for comprehensive discovery and IndexNow for promptly notifying participating engines when URLs are added, updated, or removed (Bing Webmaster Blog).

What content is easiest for an AI answer to use?

The easiest content to use is specific, well-structured, self-contained, and supported by credible evidence. A strong section gives the direct answer first, then explains the conditions, examples, and source behind it.

This is not about writing in a robotic style. It is about removing avoidable ambiguity. Compare these two openings:

“There are many factors to consider when embarking on the exciting journey of choosing a contractor.”

“Before hiring a basement contractor, confirm who is responsible for permits, how change orders are priced, and what the payment schedule covers.”

The second version is useful immediately. A person can act on it. A search system can identify its topic. An answer engine can extract a clear point without wading through filler.

Question-led pages work well because they mirror how people prompt AI tools. Each question should have a concise answer in its first one or two sentences, followed by depth. Add concrete examples, definitions, dates, geographic context, and limitations where relevant. Cite original sources for regulations, platform rules, market data, and statistics.

Original experience also matters. A realtor can explain what repeatedly confuses first-time sellers in York Region. A contractor can show how two apparently similar quotes differ. A business owner can document an actual process, including the trade-offs. That kind of detail is harder to replace with a generic summary and more useful whether the reader arrives from ChatGPT, Google, LinkedIn, or a referral.

Torred’s content and website services are built around that connection: publish material a real prospect can use, then give the prospect a clear path into the service it supports.

How can a local business build the trust AI systems need?

A local business builds trust by making important facts consistent and earning corroboration from sources it does not control. Your website is the claim; your broader digital footprint is part of the evidence.

Start with entity consistency. Use the same business name, core service description, phone number, address or service area, and website across your main profiles. Keep hours current. Make sure team members, credentials, and locations are described accurately. If an old directory lists a previous address or an abandoned profile carries a different brand name, correct it where possible.

Then build legitimate third-party signals:

• Ask real customers for honest reviews without telling them what rating to give.

• Maintain relevant professional, trade, chamber, and industry profiles.

• Earn local media or association coverage through genuinely useful work.

• Contribute expertise to credible publications, podcasts, and community resources.

• Encourage partners to use accurate descriptions when they mention the business.

• Publish case studies that can be verified and avoid results claims you cannot substantiate.

Reviews are especially important in local decisions. BrightLocal’s 2026 U.S. research found that the most or best reviews were among the top reasons consumers selected a local business, behind only clear and complete information in the reported ranking (BrightLocal). Treat that as directional evidence rather than a Canadian market estimate.

The principle is broader than any single AI model: consistent facts reduce confusion, while independent confirmation reduces the risk of taking a business’s self-description at face value. The industry-specific marketing systems Torred supports combine owned assets, content, and lead generation because trust is rarely created on one page alone.

Can schema markup or an llms.txt file make a business rank in AI answers?

No. Schema markup and emerging text-file conventions can support clarity or access in some contexts, but neither can make an AI system recommend a business. Google explicitly says no special schema.org markup or AI text file is required for its AI search features (Google Search Central).

Structured data is still useful when it accurately labels information already visible on the page. LocalBusiness markup can identify business details such as hours and departments, and Organization markup can clarify brand information. The value is precision, not magic. Incorrect or exaggerated markup can create conflicts instead of authority.

The `llms.txt` proposal is often described as a simple index or guide for language models. It may be harmless to provide, but no major platform guarantee says that adding it will produce visibility. It should sit far below proven priorities such as crawl access, indexation, internal linking, current business profiles, useful pages, and external credibility.

The same caution applies to FAQ schema. You can still organize a page around real questions because that helps readers and retrieval systems. Do not assume adding FAQ markup creates an AI recommendation or a Google rich result. Structure the visible content well first; mark it up only when the markup is accurate and supported.

A sensible rule is this: if a tactic makes the website clearer and more accessible to both people and machines, it may be worth doing. If its only justification is that someone claims to have reverse-engineered a hidden AI ranking factor, demand evidence before spending money.

How should a business measure GEO performance?

A business should measure GEO through visibility, citations, qualified visits, branded demand, and conversions—not citation count alone. A mention that never reaches the right buyer can be interesting without being commercially valuable.

Measurement is improving. In 2026, Microsoft introduced an AI Performance public preview in Bing Webmaster Tools that reports how publisher URLs are cited across Microsoft Copilot, AI-generated Bing summaries, and select integrations (Bing Webmaster Blog). OpenAI says publishers can track ChatGPT referrals because outbound links include a `utm_source=chatgpt.com` parameter (OpenAI Help Center).

Build a simple monthly view:

• Referral sessions from ChatGPT and other identifiable AI sources.

• Landing pages receiving those visits.

• Form submissions, calls, or booked meetings from AI referrals.

• Branded-search growth and direct traffic trends.

• Whether priority prompts mention or cite the business, checked consistently.

• Citation share among a defined set of relevant questions.

• Pages cited and the claims for which they are used.

• Search index coverage, crawl errors, and content freshness.

Prompt tracking needs discipline. Results can vary by location, personalization, time, and model. Use the same small set of commercially relevant prompts, record the date and platform, and look for patterns rather than treating one favourable screenshot as proof.

Finally, connect the work to business outcomes. If an article becomes a cited source but attracts no relevant attention, decide whether it supports authority in another way or needs a stronger next step. GEO should improve the path from question to confidence to contact. It is not a trophy hunt for AI mentions.

What should a 90-day GEO plan include?

A 90-day GEO plan should fix access first, strengthen the business entity second, and publish a small number of high-quality answer pages third. The goal is to establish a trustworthy foundation and a repeatable measurement baseline—not to promise instant recommendations.

Days 1–30: make the business legible

• Audit robots rules for Googlebot, Bingbot, and OAI-SearchBot.

• Confirm important pages are indexable and present in sitemaps.

• Standardize business name, services, locations, and contact details.

• Update Google Business Profile, Bing Places, and major industry profiles.

• Add or correct visible organization and local-business information.

• Set analytics to identify AI referral traffic and conversions.

Days 31–60: build answer-worthy pages

• Interview the owner or subject-matter expert about recurring buyer questions.

• Choose five questions with commercial relevance and weak existing answers.

• Publish direct, source-backed pages with concrete local context.

• Link each article to the right service and industry page.

• Refresh the core pages those articles support.

Days 61–90: earn and evaluate evidence

• Ask recent customers for honest reviews through a consistent process.

• Correct major third-party listing conflicts.

• Pursue a few credible local or industry mentions.

• Test priority prompts across selected answer engines.

• Review referral quality, citations, branded searches, and inquiries.

• Update pages where facts, answers, or sourcing remain weak.

For realtors building local authority or contractors competing on trust, this sequence is more defensible than chasing hacks. It improves the same assets buyers use even when AI is not involved.

Book a Strategy Call to map a practical SEO and GEO foundation for your business without invented guarantees.

Sources

• OpenAI Help Center: Publishers and Developers FAQ

• OpenAI Help Center: ChatGPT Search

• Google Search Central: AI features and your website

• Microsoft Bing Webmaster Blog: Introducing AI Performance in Bing Webmaster Tools

• Microsoft Bing Webmaster Blog: Keeping Content Discoverable with Sitemaps in AI-Powered Search

• Aggarwal et al.: GEO—Generative Engine Optimization

• BrightLocal: What makes consumers choose your business?