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Free playbook · PDF

How to show up in ChatGPT, Gemini and Perplexity for local and 'near me' questions

A playbook for multi-location brands and local agencies: what each AI engine documents about its local data, a location data consistency scorecard, location page and FAQ templates, review rules, LocalBusiness markup, a city and 'near me' prompt set, governance and a 90-day plan.

  • Per-engine map of documented local data sources
  • Location data consistency scorecard across GBP, Apple, Bing and Yelp
  • Location page and FAQ template with LocalBusiness markup checklist
  • City and 'near me' prompt set with placeholders
  • Central-versus-local ownership matrix and a 90-day plan

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The short answer

AI assistants answer local questions from a mix of web search results, map and listing data, and review platforms. To show up, keep every location's name, address, phone, hours and categories identical across Google Business Profile, Apple Business Connect, Bing Places and Yelp, publish a real page per location, earn steady genuine reviews, and test city prompts.

For multi-location brands, franchises, healthcare groups, retailers, hospitality and local SEO agencies

What you will learn

  1. Chapter 1

    Where AI assistants get local answers

    • Local AI answers combine web search results, map and listing data, and reviews, and a location can fail on any of the three.
    • Google documents that Gemini uses public Google Maps information and advises keeping Business Profile information current for its AI features.
    • OpenAI documents that ChatGPT uses location, third-party search providers and third-party business listing providers, and Yelp says its reviews now power part of ChatGPT's local experience.
    • Where a vendor does not document its local data source, test it rather than relying on third-party claims.
    • The safest strategy is identical core facts on every major platform, so every engine reads the same truth.

  2. Chapter 2

    One source of truth for every location

    • Keep one master record per location, owned centrally, and copy every listing from it.
    • Google's guidelines require chains to use the real-world name, consistent naming and a shared primary category, with one profile per location.
    • Apple Business Connect, Bing Places and Yelp each reach surfaces that Google does not, and each needs the same facts.
    • A mismatched fact is worse than a missing one, because it gives an engine two versions to choose between.
    • Closures, moves and duplicates need written procedures, because they commonly cause lasting errors.

  3. Chapter 3

    Location pages, FAQs and structured data

    • Each real location needs a crawlable page with facts only that location has, linked from its listings.
    • Pages for towns where you have no location, or pages that differ only by town name, add risk without adding answers.
    • Local FAQs should come from staff questions, reviews and your prompt set, and must agree with the listings.
    • Google's LocalBusiness markup requires name and address and recommends geo, hours, phone, url and priceRange; generate it from the master record.
    • Structured data must match what the page visibly shows.

  4. Chapter 4

    Reviews: volume, recency, themes and response

    • Reviews supply both the evidence of quality and the words an assistant uses to connect a location to a need.
    • Measure volume, recency, themes and response for each location, and compare locations with each other rather than with outside benchmarks.
    • The FTC rule bans fake, bought and sentiment-conditioned reviews; Google bans incentives and selective solicitation; Yelp asks businesses not to request reviews at all.
    • Replies are a place to add or correct facts, calmly and once.
    • Review themes should feed operations, location page content and the prompt set every quarter.

  5. Chapter 5

    City and 'near me' prompts, measured by location

    • Local prompts follow a few patterns: best in city, near me, neighbourhood, attribute, need, audience, comparison and branded local.
    • Sample cities and locations that represent the estate and the places that matter commercially, and run the set on a fixed schedule.
    • Write the city into most prompts, because engines infer location and a 'near me' prompt run from head office tests head office.
    • Record whether the correct branch is named, whether its facts are right, and every source cited.
    • Report visibility, wrong-branch rate and fact accuracy per location before rolling up to region and brand.

  6. Chapter 6

    Governance for many locations, and a 90-day plan

    • Split ownership by type of fact: identity and the master record are central, local knowledge flows in through one change route.
    • Franchisors and agencies should keep owner access to every listing in the brand's own accounts.
    • Every change follows the same path: request, master record, every platform, location page, verify, recheck.
    • A 90-day plan fixes data first, then pages and markup, then reviews and governance, and measures before and after.
    • Report changes in inputs alongside changes in answers, since no engine commits to a timeline.

7 worksheets inside

The chapters explain the method. The worksheets are what you fill in to run it: print them, or copy the tables into a document of your own.

  • W1Location data consistency scorecard
  • W2Location page and FAQ template
  • W3Review health and theme sheet
  • W4City and 'near me' prompt set
  • W5Ownership and change-route matrix
  • W6Location visibility scorecard
  • W790-day plan tracker
Get the playbook

Questions

How does ChatGPT find local businesses?
OpenAI says ChatGPT uses an approximate location, usually from your IP address, to find local results, sometimes searches through partner search providers, and may share location with third-party providers of nearby business listings. Restaurant availability can come from OpenTable, Resy or Yelp, and Yelp says its ratings and reviews now power part of ChatGPT's local experience. OpenAI does not publish a full list of its local data sources.
How do I get my local business to show up in ChatGPT?
Allow OAI-SearchBot to crawl your site, which OpenAI says is required for inclusion in ChatGPT search, and publish a specific page for each location. Keep your name, address, phone, hours and categories identical across Google Business Profile, Apple Business Connect, Bing Places and Yelp. Earn steady, genuine reviews within each platform's rules, then test city prompts to see which sources ChatGPT cites.
Does Google Business Profile affect Gemini and AI Overviews?
Google's Gemini help says Gemini uses public Google Maps information such as addresses, ratings and opening hours to answer place questions, and Google's guidance for AI features in Search advises keeping Business Profile information up to date. A complete, accurate profile per location is the most direct lever Google documents for its AI surfaces.
Is local SEO for AI different from normal local SEO?
The foundations are the same: accurate listings, good location pages and genuine reviews. The differences are that assistants draw on more platforms than Google alone, quote reviews and pages in their own words, and give one answer rather than a list of links. That makes consistency across Apple, Bing and Yelp, and specific local facts on your pages, more important.
How do multi-location brands manage AI visibility across hundreds of locations?
Keep one master record per location, owned centrally, and publish every listing and location page from it. Split ownership by type of fact, route every change through one process, and report visibility per location rather than as one brand number. Test a representative sample of cities on a fixed schedule rather than every town at once.
Can I ask customers for reviews to improve AI visibility?
It depends on the platform. The FTC's rule allows general requests without sentiment conditions, and Google allows asking but bans incentives and selectively asking happy customers. Yelp says businesses should not ask customers for reviews at all. Never buy reviews, offer incentives for them, or let staff review their own location.
How do I test 'near me' prompts accurately?
Engines infer location, often from the IP address, so a 'near me' prompt run from head office tests head office's area. Write the city or neighbourhood into most prompts so results are comparable, and run a few true 'near me' prompts from the location itself. Record signed-in state, memory settings, location sharing and any VPN.
Do I need LocalBusiness schema to appear in AI answers?
Google says no special schema is needed to appear in AI Overviews or AI Mode, but its LocalBusiness markup can make a business eligible for knowledge panels and carousels in Search and Maps. It requires name and address and recommends coordinates, hours, phone and URL. Generate it from the same master record as your listings, and make sure it matches the visible page.
Is Local and Multi-Location AI Visibility free?
Yes. Give a first name and a work email and the download starts at once. We also email you the link, and one person from the Noma team follows up a day later; reply and say so if you would rather not hear from us.
Why do you ask for a work email?
The playbooks are written for teams at companies, and a work address tells us which company is reading, so a follow-up can be about your brand rather than generic. Personal and temporary inboxes are not accepted.
What format is it?
A PDF of 42 A4 pages, laid out to print, with worksheets you can fill in by hand or copy into a document of your own.

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Updated 20 October 2026 · Written by the Noma team · All resources