This is the question every local business owner should be asking. When someone asks ChatGPT, Gemini, or Siri for a recommendation in your category, are you the answer?
If not, here's how to change that.
Understand what AI is looking for
AI systems making local recommendations are trying to answer a trust question: is there enough evidence to recommend this business confidently?
"Unlike classic search results, AI answers often narrow the field. 'I suggest you call Smith Plumbing' functions more like an endorsement than a ranked listing."
AI systems are cautious about these endorsements, which means they look for strong evidence before making them. That evidence comes from reputation signals you can influence.
Review depth is one of the strongest levers
Review volume matters because it gives AI systems more evidence to work with. But volume by itself is not enough. The strongest profiles combine volume, recency, platform diversity, detailed sentiment, and consistent responses.
Important
This isn't about gaming the system. AI systems interpret high review volume as statistical confidence. If 2,000 people have reviewed your business and 95% are positive, that's a reliable signal. If 200 people have reviewed and 95% are positive, there's more uncertainty.
Start collecting reviews through a consistent, compliant process. Ask every customer, make clear that reviews are optional, and never ask for a specific rating. Use technology that reduces friction. Track review velocity weekly. For a deeper look at what AI values in reviews, see Reviews That Move AI Rankings.
Recency matters almost as much
Old reviews don't count the same as new ones. AI systems know that businesses change over time. A company that was great in 2020 might not be great now.
Review recency is a signal of current quality. Businesses that are collecting fresh reviews consistently look more reliable than those with stale profiles.
Pro Tip
Aim for continuous review flow rather than bursts. A steady pattern is more credible than one spike followed by silence.
Sentiment is the third leg
Star ratings are crude, but AI systems go deeper. They analyze the actual language in reviews to understand sentiment.
Reviews that say "John was professional, on time, and explained everything clearly" tell the AI something specific. Reviews that just say "Great!" don't add much.
Pro Tip
Use neutral prompts that invite detail without steering the rating: "If you have a moment to leave us a review, we'd appreciate hearing what stood out about your experience."
Clean up your citations
AI systems cross-reference your business information across the web. If your name is "Smith Plumbing" on Google but "Smith's Plumbing LLC" on Yelp, that inconsistency creates uncertainty.
Audit your presence across Google, Yelp, Facebook, BBB, Apple Maps, Bing Places, and industry directories. Standardize your business name, address format, and phone number everywhere.
"This isn't glamorous work, but it's foundational. Inconsistent citations undermine everything else you do."
Add structured data to your website
AI systems that crawl websites look for machine-readable data. JSON-LD schema markup gives them a cleaner version of what your business is, where you operate, and what you're known for.
At minimum, implement LocalBusiness schema with your name, address, phone, hours, and service categories. Use Service schema to describe what you offer, FAQPage schema where you publish useful FAQs, and sameAs links to connect your verified profiles. Use Review or AggregateRating markup only when it fits current Google guidelines.
Your web developer can implement this in an afternoon. Test with Google's Rich Results Test to make sure it's working. For the full technical walkthrough, see What Is JSON-LD?.
Respond to reviews
Your review responses are part of your digital footprint. AI systems read them. A pattern of thoughtful, non-templated responses to both positive and negative reviews signals that you're engaged and customer-focused.
Respond to everything. Vary your language. Reference specific details from each review. For negative reviews, acknowledge the problem and offer resolution.
Monitor and test
Periodically ask ChatGPT and Gemini for businesses in your category and location. See if you're mentioned. See who's ahead of you.
This isn't a one-time check. Models, retrieval sources, and competitors change. You need to track your AI visibility over time just like you'd track keyword rankings. The AI Visibility Grader can give you a focused one-profile baseline in about 1-3 minutes.
Important
The businesses that get recommended usually have stronger evidence across reviews, citations, website content, and structured data. Build those signals deliberately.
Further Reading
- How to Rank in ChatGPT Local Search Results. Local Falcon's tactical guide to AI visibility
- ChatGPT Local Search Data Sources. Where ChatGPT pulls business information from
- Google Rich Results Test. Validate your schema markup implementation
- LocalBusiness Schema. Official documentation for structured data
Dylan Allen-Arnegård is the CEO of Cheers, the local search platform for service businesses.