Most local businesses don't have a GEO strategy. They have scattered tactics: maybe they've claimed their Google Business Profile, maybe they ask for reviews sometimes, maybe they have a website that hasn't been updated in two years.
That's not a strategy. That's leaving money on the table while your competitors figure out how to get AI assistants to recommend them instead of you.
Important
If you only do three things: standardize your citations, ask every customer for reviews through a consistent process, and implement schema markup. Everything else is optimization on top of these fundamentals.
Here's what actually works.
Start with the foundation: your digital identity
Before you worry about AI recommendations, you need a clean digital footprint. AI systems cross-reference your business information across dozens of sources. If your business name is "Smith Plumbing" on Google but "Smith's Plumbing LLC" on Yelp and "Smith Plumbing Services" on your website, you have a problem.
"Inconsistency tells AI systems that your business information is unreliable. And unreliable businesses don't get recommended."
Run an audit. Search your business name across Google, Yelp, Facebook, BBB, Apple Maps, Bing Places, and any industry directories relevant to your trade. Make a list of everywhere you're mentioned. Then standardize everything: same name, same address format, same phone number, everywhere.
This sounds tedious because it is. But it's foundational. Skip this step and everything else you do will be undermined by conflicting signals.
Build your evidence layer
AI systems make recommendations based on evidence. The question they're answering is: "What proof exists that this business is good at what they do?"
Your job is to create that proof in formats AI can read.
Reviews are the primary evidence. We've covered this elsewhere, but it bears repeating: review volume, velocity, and quality are the biggest GEO signals for local businesses. If you're not collecting reviews systematically, nothing else matters. See how Sierra Cooling grew from 20 to 350+ reviews per month with a systematic review program.
Structured data is the secondary evidence. Your website needs schema markup that gives crawlers a clean version of what you do, where you operate, and what you're known for. LocalBusiness schema, Service schema, FAQ schema, and sameAs links create that clarity.
Third-party mentions are supporting evidence. Press coverage, directory listings, association memberships, awards. Every credible mention of your business adds to your entity profile. AI systems aggregate these signals to determine authority.
Pro Tip
Think of your evidence layer like a resume. Reviews are your work experience, structured data is your credentials, and third-party mentions are your references.
The technical layer most businesses skip
Here's where service businesses usually fall short: technical implementation.
Schema markup goes on your website. It's code that structures your business information in a format AI can parse directly. LocalBusiness schema tells AI your name, address, phone, hours, services, and service area. FAQ schema marks up your frequently asked questions. sameAs links connect your site to verified profiles across the web.
"If your website developer doesn't know what JSON-LD is, you need a different developer. This is baseline GEO work."
Beyond schema, an llms.txt file can help. It is an emerging Markdown proposal for giving AI tools a concise guide to your business, your key pages, and your preferred source material. Not every AI system reads it, so treat it as a complement to robots.txt, sitemap.xml, schema, and visible page content. For a complete guide to implementing it, see What is LLMs.txt and Why Your Business Needs One.
Your website content matters too. AI systems pull information from your site to populate their understanding of your business. Clear, specific service descriptions. Geographic coverage. Team information. Pricing transparency where appropriate. The more concrete information you provide, the better equipped AI is to recommend you accurately.
The review engine
This is where most of the work happens on an ongoing basis.
You need a systematic way to collect reviews from satisfied customers. The businesses winning at GEO aren't hoping customers remember to leave reviews. They're building review requests into their service process.
For field service businesses, that means capturing reviews at the point of service. When a technician finishes a job and the customer is happy, that's the moment. NFC badges work. QR codes work. The method matters less than the consistency.
For retail or hospitality, it means training staff to make the ask. "If you had a good experience, we'd really appreciate a review." Signage helps. Follow-up texts help. But nothing replaces a direct, personal request from the person who just delivered great service.
Pro Tip
At Cheers, we recommend tracking review conversion rate by location and team. Treat benchmarks as diagnostic signals, not quotas. If one branch is far below the rest, inspect the process and coach the ask.
Respond to everything
Every review gets a response. Positive reviews get thanked. Negative reviews get acknowledged and addressed. This isn't about appeasing angry customers, though that's a nice side effect. It's about building a response corpus that AI systems read.
Your responses are part of your digital footprint. They demonstrate engagement, customer care, and professionalism. A business with 500 reviews and 500 thoughtful responses looks better to AI than a business with 500 reviews and silence.
Important
Don't use templates. AI systems can detect templated responses, and they undermine the signal you're trying to send. Vary your language. Reference specific details from each review.
Monitor and iterate
GEO isn't a one-time project. It's an ongoing process. The businesses that dominate AI recommendations are the ones that treat this as a continuous operation.
Track your review velocity monthly. Watch for trends. If velocity drops, diagnose why.
Monitor your mentions across platforms. Set up Google Alerts for your business name. Know when you're being talked about.
Test AI recommendations periodically. Ask ChatGPT and Gemini for businesses in your category and location. See where you rank. See who's above you and try to figure out why.
"The competitive field is shifting. Businesses that were absent from AI answers six months ago can surge ahead with the right strategy."
The compounding advantage
The good news about GEO is that early movers have a massive advantage. AI systems build persistent knowledge about businesses. Once you've established yourself as an authority in your category, maintaining that position is easier than building it from scratch.
Every review, every response, every citation adds to your profile. Over time, these compound. The business with 3,000 reviews and a consistent track record will be harder to displace than the business with 300.
Start now. The sooner you build your GEO foundation, the harder it becomes for competitors to catch up.
Further Reading
- LocalBusiness Schema Documentation. Schema.org's official specification for local business structured data
- Google's Structured Data Guide. Google's documentation on implementing LocalBusiness schema
- The llms.txt Specification. Original proposal and format documentation for llms.txt
- Apple Business Connect. Apple's platform for managing your presence on Apple Maps and Siri
Amadeus Peterson is the CTO of Cheers, the local search platform for service businesses.