Guides

How Do I Get AI to Recommend My Business?

A straightforward guide to the signals that drive AI recommendations for local businesses. No fluff, just what actually works.

Dylan Allen

CEO & Co-Founder

Dec 10, 2025
6 min read
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The AI Recommendation Checklist

What AI evaluates before recommending your business

Review VolumeCritical

1,000+ reviews signals statistical confidence

2,400 reviews

Review VelocityCritical

Consistent monthly flow, not bursts

127/month

Review SentimentHigh

Detailed, specific positive mentions

92% positive

Citation ConsistencyHigh

Same NAP across all directories

3 conflicts

Structured DataMedium

LocalBusiness schema, llms.txt

Implemented

AI Recommendation Readiness

Based on current signals

4/5

Fix citations to reach 5/5

Key: AI needs undeniable evidence before staking its credibility on a recommendation.

What You'll Learn

  • 1
    Understand what AI is looking for
  • 2
    Review volume is the biggest lever
  • 3
    Recency matters almost as much
  • 4
    Sentiment is the third leg
  • 5
    Clean up your citations

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 this business good enough to stake my credibility on?

"Unlike Google, which shows you options and lets you decide, AI puts its name behind the recommendation. 'I suggest you call Smith Plumbing' is an endorsement."

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 volume is the biggest lever

More than anything else, AI recommendations correlate with review volume. A business with 2,000 reviews will beat one with 200, almost every time.

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 more reviews. Make it a systematic part of your operations. Train your team to ask. Use technology that reduces friction. Track review velocity weekly.

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. Fifty reviews a month, every month, is better than 500 reviews once and then 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

Train customers on what to include: "If you have a moment to leave us a review, we'd especially appreciate hearing what stood out about your experience." This prompts richer, more detailed feedback.

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 tells them exactly 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. Add AggregateRating schema if you display reviews on your site. Use Service schema to describe what you offer.

Your web developer can implement this in an afternoon. Test with Google's Rich Results Test to make sure it's working.

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. The landscape shifts. Competitors improve. You need to track your AI visibility over time just like you'd track keyword rankings.

Important

The businesses that get recommended didn't get lucky. They built the signals that AI systems look for. You can too.

Further Reading

Dylan Allen is the CEO of Cheers, the GEO platform for local service businesses.

Frequently Asked Questions

Focus on three things: review volume (collect more reviews systematically), review recency (aim for continuous flow, not bursts), and citation consistency (standardize your business info across all platforms). AI systems look for strong reputation evidence before making recommendations.

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