AEO
Be the answer AI assistants and AI Overviews quote.
Learn More“Who builds websites in Plano?” gets asked to ChatGPT and Claude now, and the answer is a short list of names. GEO is the work of making sure yours is on it — on your site and everywhere else the model learned about you.
Generative engine optimization is the practice of increasing how often AI systems mention or recommend a business in generated answers. It combines on-site structure with off-site signals — reviews, directory listings, consistent business information, third-party mentions and press — because models draw on far more than your own website.
There is a specific kind of query that decides revenue: the recommendation request. Not “what is answer engine optimization” but “who should I hire to do it in Plano”. The output is not a page of links, it is a handful of names, usually with a sentence of justification each. Being on that list is a different problem from ranking, and it has a different solution.
Models build their picture of you from everything they can find: your site, your Google Business Profile, your reviews, directories, the places you are mentioned, and how consistently all of it agrees. Contradiction is the enemy — three different phone numbers across four listings, a service you stopped offering still described in two directories, a business name written four ways. Inconsistency makes you a fuzzy entity, and fuzzy entities do not get recommended.
So GEO work splits in two. On-site, you give the model unambiguous, well-marked-up statements about who you are, where you work and what you do. Off-site, you make the rest of the web agree with that — and give it something worth repeating.
The real “who should I hire” questions in your category and city, run against ChatGPT, Claude, Perplexity and Google AI Overviews to record who gets named today and why.
Name, address, phone, hours, services and description made identical across your site, Google Business Profile and every directory that carries you. Boring, and it is the single biggest lever.
Review volume, recency and — most usefully — content. Reviews that mention the specific service and the specific city give a model a reason to recommend you for that query.
The listings that actually matter for DFW businesses, claimed, completed and kept in agreement, including the industry-specific ones models lean on in your category.
Being written about elsewhere — local press, partners, suppliers, industry roundups, community sponsorships. Independent corroboration is what separates a claim from a fact.
Organization and LocalBusiness schema that explicitly links your site to your profiles, so a model can connect every mention of you to one entity instead of three.
Original data, specific numbers, named processes and real case studies. Models repeat what is specific; generic claims are indistinguishable from every competitor's.
Repeat testing of the same recommendation queries over time, so you can see whether you are appearing more often and what you are being described as.
AEO is about being quoted when someone asks a question. GEO is about being named when someone asks for a recommendation. Related, but the levers differ.
| AEO | GEO | |
|---|---|---|
| Query type | “What is X” or “how do I X” | “Who should I hire for X in Plano” |
| The win | Your passage is quoted | Your business is named |
| Main lever | On-page structure and schema | Off-site signals and consistency |
| Evidence used | Your page content | Reviews, listings, mentions, press |
| Controlled by you | Almost entirely | Partly — the rest is earned |
| Timeline | 30–90 days | 90+ days, compounding |
Your recommendation queries run across the major assistants and recorded — who is named, in what order, and what each is credited with.
Every place your business appears online, checked for agreement. The list of contradictions is usually longer than owners expect.
Listings corrected, profiles completed, and Organization schema with sameAs links published so the connections are explicit.
Review approach, directory presence and third-party mentions, sequenced by what moves fastest in your category.
The pages, numbers and case studies that give a model something specific to say about you rather than a generic description.
The same queries re-run on a schedule, so progress is observed rather than assumed.
This is for businesses that win on reputation and get chosen from a short list — local services, professional services, healthcare, trades, agencies and B2B vendors in considered categories.
It is also for businesses whose competitors are already being named by assistants. That lead compounds, because mentions beget mentions, and closing it later costs more than closing it now.
If your business information is inconsistent across the web, GEO starts there, and the first phase is cleanup rather than anything clever.
GEO is the practice of increasing how often generative AI systems mention or recommend your business in their answers. It combines on-site structure and schema with off-site signals — reviews, directory listings, consistent business information and third-party mentions — because models draw on far more than your own website.
AEO is about being quoted as the answer to an informational question, and the levers are mostly on your own pages. GEO is about being named when someone asks for a recommendation, and the levers are mostly off-site: reviews, listings, mentions and consistency. Most businesses need both.
No, and nobody can. Model outputs vary by phrasing, user and date. What can be done is to improve every input the model relies on — consistency, reviews, corroboration and specificity — and to measure whether you are named more often over time. That measurement is part of the work.
Entity cleanup can take effect quickly once listings are corrected and re-crawled. Meaningful movement in recommendation answers generally takes 90 days or more, because the off-site signals that drive it accumulate rather than switch on.
Yes, and the content matters as much as the rating. A review that names the specific service and the specific city gives a model a concrete reason to recommend you for that query, which a five-star review saying “great job” does not.
Often better. There is less competition for the entity space in a smaller market, so consistent information and a modest number of specific reviews can make you the obvious name in answers for that area.
Be the answer AI assistants and AI Overviews quote.
Learn MoreTechnical and local SEO for Plano and DFW businesses.
Learn MoreHow the two differ, and why they are one investment.
Learn MoreStart with the free audit of your site's structure and entity signals. If you would rather we test the recommendation queries in your category first, ask and we will run them.
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