Ask ChatGPT for the best HVAC company in Las Vegas, and it may give you a short list. Ask Gemini for a good waxing salon in Dallas, and it may recommend one. These AI assistants synthesize signals from across the web and make a judgment call about who deserves to be mentioned.
Generative Engine Optimization is the practice of influencing that judgment call. It's about making sure that when an AI is asked about businesses like yours, your name comes up.
Pro Tip
GEO is about being the business that AI recommends, not just the one that ranks on Google.
For a local service operator, this is not an abstract marketing trend. It is a practical evidence problem. A 40-location HVAC brand needs every market to show the same business facts, fresh reviews, clear service pages, and proof that technicians actually solve customer problems. A single strong homepage cannot carry weak location pages.
The shift that changed everything
For 20 years, local marketing meant one thing: rank on Google. Get into the map pack. Show up for the right keywords. The game was about positioning. If you showed up in the top three results, you won.
That game isn't over, but there's a new one running alongside it. When someone asks an AI assistant "Who's the best plumber near me?", there may be no map pack and no list of ten blue links. There may be one answer, or a very short list. The AI narrows the field before the customer ever visits a results page.
"In AI recommendations, being absent from the answer can matter more than being lower in a ranking."
This is generative search. If you're not in that answer, you may never enter that customer's consideration set.
How AI decides who to recommend
AI assistants do not all rely on one universal local business database. Some responses come from training data, some come from live or recent web retrieval, and some are tied to the search product's own local data layer. When someone asks about a local service, the answer is usually influenced by evidence like:
Review signals. AI systems read volume, recency, and the actual language in reviews alongside the star rating. A business with many recent, specific reviews has stronger evidence than one with a thin or stale profile.
Citation consistency. AI systems cross-reference your business information across Google, Yelp, BBB, industry directories, and anywhere else you're mentioned. If your name, address, or phone number varies, you look less trustworthy. Consistency signals legitimacy.
Structured data. Schema markup, JSON-LD, and other machine-readable formats help AI systems understand what you do, where you operate, and what you're known for. This is now a baseline technical layer.
Fresh content. Websites that haven't been updated in years signal abandonment. Active content, recent blog posts, and current information all contribute to whether an AI considers you relevant.
Third-party mentions. Press coverage, directory listings, and backlinks from authoritative sources all feed the AI's understanding of your reputation. These are the citations that build your entity in the AI's knowledge graph.
Important
Review depth, velocity, and sentiment are among the strongest local signals, but they work best when citations, website content, and structured data agree.
For a deeper breakdown of where ChatGPT-style systems may retrieve local business facts, see What Sources Does ChatGPT Use to Give Recommendations?. For Google's current advice, see How Local Businesses Can Show Up in Google AI Search.
Why traditional SEO isn't enough
SEO taught us to optimize for keywords. Write content targeting "best HVAC company in Phoenix" and hope to rank for that search. The problem is that AI doesn't work the same way.
When someone asks an AI assistant for a recommendation, the AI isn't matching keywords. It's making an inference. It's asking itself: based on everything I know about this business, are they the right answer to this question?
That inference is based on reputation signals that SEO largely ignores. You can have excellent on-page SEO and still be absent from AI recommendations if you have weak reviews, inconsistent citations, or no structured data.
"SEO is about ranking. GEO is about being the answer."
The review problem
Here's the uncomfortable truth: most businesses don't have the review profile they need for GEO. The average service business collects maybe 20-50 reviews a month, often from customers who had problems rather than customers who were satisfied.
AI systems are trained to recognize this pattern. They know that angry customers leave reviews unprompted, while happy customers usually don't. So they weight review volume and sentiment together. A business with thousands of positive reviews isn't just more popular. It's more statistically credible.
This is why review velocity matters so much for GEO. It's not about gaming the system. It's about creating an accurate signal of your actual customer satisfaction. If 95% of your customers are happy, your online presence should reflect that. For a full breakdown of what AI cares about in reviews, see Reviews That Move AI Rankings.
What this means for your business
If AI assistants are already recommending your competitors, you have a visibility problem that SEO alone won't solve. You need to build the signals that AI systems use to evaluate trustworthiness.
That means getting serious about review collection. Not as a nice-to-have, but as a core business function. It means cleaning up your citations so your business information is consistent everywhere. It means implementing structured data so AI systems can parse your business correctly. If your team needs the technical layer, start with What Is JSON-LD?. If you need the review layer, read Reviews That Move AI Rankings. You can also check where one profile stands with the free AI Visibility Grader.
Pro Tip
The businesses that figure out GEO early will have more evidence in market before competitors catch up. Reviews, citations, third-party mentions, and structured content build over time.
The businesses that figure this out early will have more evidence in market before competitors catch up. Once you're established as an authority in your category, maintaining that position is easier than building it from scratch.
GEO isn't a fad. It's becoming a new layer of local discovery. The question isn't whether to invest in it. It's how quickly you can build the evidence customers and AI systems already use.
Sources
- Google AI Search optimization guide. Google's current guidance on useful content, crawlability, page experience, structured data, and AI Search
- How Does ChatGPT Conduct Local Searches?. Search Engine Land's reporting on ChatGPT's local recommendation mechanics
- Local Consumer Review Survey 2026. BrightLocal's current research on how consumers use reviews
- LocalBusiness Schema Documentation. Schema.org's official structured data specification
- Google Business Profile Help. Google's official resource for business listing management
Dylan Allen-Arnegård is the CEO of Cheers, the local search platform for service businesses.