Ask ChatGPT for the best HVAC company in Las Vegas, and it'll give you a name. Ask Gemini for a good waxing salon in Dallas, and it'll recommend one. These AI assistants aren't guessing. They're synthesizing signals from across the web and making 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.
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's no map pack. There's no list of ten blue links. There's just an answer. One name, maybe two. The AI picks a winner and moves on.
"In AI recommendations, you're either the answer or you don't exist."
This is generative search. And if you're not in that answer, you don't exist to that customer.
How AI decides who to recommend
Large language models don't have secret databases of local businesses. They're trained on public web data, and they're constantly pulling fresh information through retrieval systems. When someone asks about a local service, the AI looks at:
Review signals. Not just star ratings, but volume, recency, and the actual language in those reviews. A business with 2,000 recent 5-star reviews mentioning specific services will get recommended over one with 50 old reviews, every time.
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 isn't optional anymore.
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
The #1 signal for AI recommendations is review volume and velocity. Everything else is secondary.
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 perfect on-page SEO and still be invisible to AI 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.
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.
Pro Tip
The businesses that figure out GEO early will have a compounding advantage. AI systems remember.
The businesses that figure this out early will have a compounding advantage. AI systems remember. 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 the new foundation of local discovery. The question isn't whether to invest in it. It's whether you can afford not to.
Further Reading
- How Does ChatGPT Conduct Local Searches? — Search Engine Land's deep dive into ChatGPT's local recommendation mechanics
- Local Consumer Review Survey 2025 — BrightLocal's annual research on how consumers use reviews
- LocalBusiness Schema Documentation — Schema.org's official structured data specification
- Google Business Profile Policies — Google's official guidelines for business listings
Dylan Allen is the CEO of Cheers, the GEO platform for local service businesses.