How AI Recommends Local Businesses and How to Optimise Yours for LLMs?

A customer in your city opens ChatGPT and types: “What’s the best plumber near me?” or “Which local accountant is trusted in Brisbane?” If your business isn’t part of the answer, you’re invisible to a growing segment of buyers who have already moved on from the ten blue links.

AI assistants are rapidly becoming the first stop for local business discovery. Google’s AI Overviews now appear in up to 84% of local search queries in some categories. Perplexity, ChatGPT with browsing, and Apple Intelligence are surfacing business recommendations based not on who paid for an ad, but on who the AI has been trained to trust.

Understanding how that trust is built, and how to earn it, is the new frontier of local marketing. This guide breaks it all down.

How LLMs Actually Decide Which Local Businesses to Recommend

Understanding how AI recommends local businesses starts with understanding what the model is actually working from. LLMs don’t have a real-time GPS or a live business directory. What they have is a vast, compressed memory of the web: every review site, local news article, directory listing, forum thread, and social mention that existed when the model was trained, plus (for retrieval-augmented systems like Perplexity and SearchGPT) the ability to query live search indexes.

When someone asks for a local business recommendation, the AI runs a pattern-matching process across that memory and surfaces businesses that:

• Appear frequently and positively across multiple independent sources: review platforms, local blogs, forum mentions, social media
• Have consistent, accurate information across the web: name, address, phone number (NAP) consistency is a strong trust signal
• Are associated with specific, relevant keywords: “emergency plumber,” “family dentist,” “best Italian restaurant”
• Have demonstrated expertise signals: published articles, expert quotes in local media, how-to guides
• Have strong Google Business Profile signals, for RAG systems that draw from live search results, your GBP is a direct input

In short: LLMs recommend the businesses that the internet has collectively decided are trustworthy and relevant. Your job is to make that case as clearly and consistently as possible across every channel that matters.

1. Nail Your Google Business Profile: It Feeds AI Directly

For any LLM using retrieval-augmented generation (RAG), which includes SearchGPT, Google’s AI Overviews, and Perplexity’s local results, your Google Business Profile (GBP) is live input data. When someone asks “best coffee shop in Fitzroy,” the AI may literally be reading your GBP listing as part of its response generation.

This means GBP optimisation is now doubly important: it drives traditional local SEO and AI recommendation visibility.

GBP Optimisation Checklist for LLM Visibility

• Complete every field: hours, services, service area, attributes (wheelchair accessible, outdoor seating, etc.), website, phone
• Write a keyword-rich business description in natural language that answers “what do you do, who do you serve, and why should someone choose you?”
• Add a full services/products list with descriptions, these become extractable facts for AI systems
• Upload fresh photos regularly: AI systems and search algorithms both weight recency
• Post weekly GBP updates: active profiles signal a legitimate, maintained business
• Enable messaging and Q&A, and pre-populate the Q&A section with the questions your customers most commonly ask

Think of your GBP as a structured data feed that AI systems consume directly. The more complete and accurate it is, the more confidently an LLM can include you in a recommendation.

2. Build NAP Consistency Across Every Directory

NAP stands for Name, Address, Phone Number, the three core identifiers LLMs and search engines use to verify that a business is real, local, and consistent. When your NAP varies across different platforms (e.g., “VYRO Web” on Google but “VYRO Web Pty Ltd” on Yelp, or different phone numbers on different directories), AI systems struggle to resolve a single confident identity for your business.

This ambiguity leads to one outcome: the AI recommends a competitor whose identity is clearer.

Audit your NAP across the following and correct any inconsistencies:

• Google Business Profile
• Apple Maps / Apple Business Connect
• Bing Places
• Yelp, TripAdvisor, True Local (Australia)
• Yellow Pages, White Pages
• Facebook Business Page
• Your own website’s contact page and footer
• Industry-specific directories (e.g., HiPages for tradies, HealthEngine for medical)

Claim and verify every listing. Don’t just correct the ones you know about. Use a tool like BrightLocal or Semrush’s Listing Management to find and fix every instance of your business information across the web.

3. Generate Review Volume and Recency: Especially Detailed Reviews

Reviews are perhaps the single biggest signal LLMs use to assess local business quality. But it’s not just the star rating that matters, it’s the content of reviews. When your customers write detailed reviews mentioning specific services, staff members, locations, and outcomes, they’re creating keyword-rich, trust-building content that AI systems can read and cite.

A review that says “Great service, highly recommend” does almost nothing for LLM visibility. A review that says “I called VYRO Web for an emergency fix on my eCommerce site on a Saturday and they had it resolved within 3 hours, their SEO work doubled our organic traffic in 4 months” is the kind of specific, credible content that AI systems extract and reference.

How to Generate High-Quality Reviews

• Ask at the moment of peak satisfaction: right after a successful project, delivery, or appointment, not weeks later
• Give customers a direct link to your Google review page, friction kills conversion
• Provide subtle guidance without dictating: “Feel free to mention the specific service we helped you with and the outcome you noticed” is perfectly legitimate
• Respond to every review, including negative ones. AI systems pick up on response patterns as evidence of professionalism and active management
• Diversify your review platforms: Google is most important, but Yelp, Facebook, and industry-specific platforms all feed into the AI recommendation ecosystem

Aim for a steady cadence of new reviews, ten reviews a month spread across the year is far more powerful than a burst of fifty followed by silence.

4. Create Locally-Specific, Expert Content

One of the most effective, and most neglected, LLM optimisation tactics for local businesses is publishing genuinely useful, locally-specific content. LLMs are far more likely to recommend a business that has demonstrated knowledge of its local area and industry than one that has no content footprint beyond its product/service listing.

Consider the difference between two electricians. One has a website with a homepage, services page, and contact form. The other has all of that, plus blog posts like “Why Melbourne Homes Built Before 1980 Need an Electrical Safety Audit,” “The Real Cost of Solar Panel Installation in Victoria in 2025,” and “What to Do If Your Safety Switch Keeps Tripping.” When someone asks an AI “do I need an electrician or can I fix this myself,” which business do you think surfaces?

To build this content footprint:

• Write 1-2 blog posts per month that answer the questions your local customers actually ask
• Create location-specific service pages (e.g., “Plumber in Parramatta,” “Accountant for Small Businesses in Adelaide”), but make sure each has unique, useful content, not just swapped city names
• Publish a FAQ page that covers the 10 most common questions you hear from local customers
• Create a “local guide” piece for your area: e.g., “The Complete Guide to Strata Management Rules in NSW” if you’re a strata manager

This content becomes training signal for LLMs and retrieval data for RAG systems. It tells the AI: this business genuinely knows their stuff.

5. Get Mentioned in Local Media and Authoritative Local Sources

Third-party mentions in credible local sources carry enormous weight in how LLMs assess business authority. A single mention in a local newspaper, a feature in a regional business magazine, or a quote in an industry publication is worth dozens of directory listings from an AI trust perspective.

Why? Because LLMs are trained heavily on editorial content. A journalist citing your business in a news article is a much stronger signal than your own website claiming you’re the best, and AI systems are smart enough to know the difference between first-person claims and independent editorial endorsement.

Tactics for Earning Local Media Mentions

• Reach out to local journalists with a story angle, a business milestone, a community initiative, a local trend you can comment on as an expert
• Use HARO (Help a Reporter Out) and similar platforms to respond to journalists seeking expert sources in your niche
• Sponsor or participate in local events that generate coverage: charity events, business awards, community programs
• Contribute opinion pieces or expert columns to local business publications or industry blogs
• Get listed on “best of” local guides published by local media, tourism boards, or community organisations

Each of these activities creates a web of external, credible mentions that AI systems interpret as social proof of your business’s legitimacy and quality.

6. Add LocalBusiness Schema to Your Website

Schema markup is structured data embedded in your website’s code that tells AI systems and search engines exactly who you are, what you do, and where you operate. For local businesses, LocalBusiness Schema (and its more specific subtypes like Plumber, Dentist, Restaurant, AccountingService) is the most direct way to feed AI systems accurate, machine-readable information about your business.

At minimum, your LocalBusiness schema should include:

• name, url, telephone, email
• address with full streetAddress, addressLocality, addressRegion, and postalCode
• geo coordinates (latitude and longitude)
• openingHoursSpecification for each day of the week
• priceRange: even a rough indicator ($, $$, $$$) helps AI systems answer “affordable” vs “premium” queries
• aggregateRating: pulled from your reviews if using a plugin, or manually coded
• areaServed: the specific suburbs, cities, or regions you serve
• sameAs: links to your Google Business Profile, Facebook page, and other verified profiles

The sameAs array is particularly important for LLM confidence. When an AI can verify that your website, GBP, Facebook page, and LinkedIn profile all point to the same entity, it dramatically increases the confidence with which it will recommend you.

7. Optimise for Voice and Conversational Search Patterns

LLM-powered assistants, including Siri (powered by Apple Intelligence), Google Assistant, and Amazon Alexa: process queries in natural, conversational language. “Hey Siri, find me a good Italian restaurant near me that’s open on Sundays and takes bookings” is the kind of multi-condition query that AI systems are handling millions of times a day.

Your content and listing data need to answer these conversational queries. This means:

• Write your service descriptions in first-person, conversational language, “We serve families and small businesses in the inner west of Sydney, with same-day appointments available Monday to Saturday”
• Answer “near me” intent explicitly: name the specific suburbs and postcodes you serve, not just the city
• Address time-based queries: “open late,” “available on weekends,” “emergency callouts” should all appear in your content if applicable
• Include condition-based answers: “We accept Medicare,” “We offer payment plans,” “No job too small”, these specific conditions appear in customer queries

The goal is to pre-answer the specific questions AI assistants are likely to be asked about businesses like yours, so the AI can confidently match your business to those queries.

Your LLM Local Business Optimisation Action Plan

If you’re starting from scratch, here’s the prioritised sequence of actions that will make the biggest difference:

• ✅ Week 1: Audit and fully complete your Google Business Profile: every field, fresh photos, Q&A pre-populated
• ✅ Week 1-2: Fix NAP consistency across all major directories and your own website
• ✅ Week 2: Add LocalBusiness schema with sameAs, areaServed, openingHours, and aggregateRating to your website
• ✅ Ongoing: Run a review generation campaign. Aim for 4-8 new detailed reviews per month
• ✅ Month 1-2: Publish 3-5 locally-specific, expert content pieces targeting the questions your customers ask
• ✅ Month 2-3: Launch a local PR effort: one media mention or guest expert piece per month
• ✅ Ongoing: Monitor your business’s presence in AI responses monthly across ChatGPT, Perplexity, and Google AI Overviews

Frequently Asked Questions

How does ChatGPT know which local businesses to recommend?

ChatGPT (when using browsing or SearchGPT) draws on Bing’s search index to find local business information. It synthesises data from your Google Business Profile signals (via search), review platforms, directory listings, and any editorial mentions online. Businesses with consistent NAP data, high review volume, strong GBP profiles, and local content coverage are recommended most frequently.

Does my Google Business Profile affect AI recommendations?

Yes, significantly. For AI systems that use retrieval-augmented generation (RAG), including Google’s AI Overviews, Perplexity, and SearchGPT, your Google Business Profile is live input data. An incomplete or outdated GBP is one of the fastest ways to be excluded from AI-generated local recommendations.

What is NAP consistency and why does it matter for AI?

NAP stands for Name, Address, Phone Number, the core identifiers used to verify a local business’s identity. When these details are inconsistent across different platforms, AI systems struggle to confidently resolve a single identity for your business and are less likely to recommend it. Consistent NAP data across all directories signals a legitimate, well-maintained business.

How long does it take to appear in AI local recommendations?

For RAG-based systems (Perplexity, Google AI Overviews, SearchGPT), improvements to your GBP and schema markup can show results within 2-6 weeks as these systems re-crawl your information. Broader LLM training data changes take longer: 3-6 months: as they depend on the accumulation of reviews, media mentions, and directory citations across the web.

Do I need a local SEO agency to optimise for AI recommendations?

Many of the foundational steps: GBP optimisation, NAP consistency, review generation, can be done in-house. However, the more competitive and technical work: LocalBusiness schema implementation, local digital PR, topical content strategy, and ongoing monitoring: is where a specialist agency adds significant value, particularly if you’re in a competitive local market.

Be the Business AI Recommends: Not the One It Overlooks

The shift from “Google my business” to “Ask AI about businesses near me” is already happening. The customers using AI assistants to find local services aren’t a niche segment anymore, they’re your next clients, patients, customers, and contracts.

The businesses that act now: cleaning up their data, building their review profiles, creating local content, and earning credible third-party mentions, will have a compounding advantage over competitors who wait until AI-driven local discovery becomes impossible to ignore.

The good news is that most of this work is achievable without a massive budget. It takes consistency, local knowledge, and a clear strategy, exactly what great local businesses are built on.

If you want help getting your local business visible in AI recommendations, our Local SEO service is designed for exactly this. Or start with a free audit to see where your business stands today.

Related reading

• eCommerce LLM Optimisation: Get Recommended by AI
• Local SEO Sydney: 2026 Map Pack Playbook for SMBs
• SEO for Australian Local Businesses: Win More Customers