Roughly 45% of customers now ask AI tools to find local businesses, and AI has become the third-most-used source of local recommendations after Google and Facebook. But an analysis by SOCi of nearly 350,000 locations found ChatGPT recommended just 1.2% of them, against 35.9% appearing in Google's local 3-pack. Ranking locally in Google does not get you recommended by AI — the overlap between the two is only around 45%.
That gap is the opportunity. Here is what actually closes it.
Why local SEO does not transfer
The engines take different inputs:
| Engine | What it leans on | Recommendation rate |
|---|---|---|
| Google AI Overviews | Google Business Profile, organic ranking signals | Highest of the AI surfaces |
| Gemini | Google index and Knowledge Graph | ~11% of locations |
| Perplexity | Live retrieval from indexed web content | ~7.4% |
| ChatGPT / Copilot | Bing index plus third-party sources | ~1.2% |
Two consequences follow immediately. First, Bing matters again — ChatGPT search and Copilot are built on the Bing index, so Bing Places and Bing indexing are not optional if ChatGPT is where your customers ask. Second, your Google Business Profile is necessary but not sufficient. It carries Google's AI surfaces and almost nothing else.
The seven things that actually move local AI visibility
1. Claim and complete every profile, not just Google
Google Business Profile, Bing Places, Apple Business Connect. Complete means every field: hours, service area, categories, attributes, photos, and a description written in the words customers use rather than industry terms.
2. Make your NAP identical everywhere
Name, address, phone — byte-for-byte consistent across every directory, your website, and your profiles. Inconsistency is the single most common reason a model produces a vague, low-confidence answer about a business or skips it entirely.
3. Get reviews that describe specifics
Volume matters less than language. A model answering "best plumber for emergency callouts in [city]" is looking for reviews that contain the words "emergency" and "callout." Ask customers what problem you solved rather than for a star rating, and you will get text that maps onto real queries.
4. Publish pages that answer local questions directly
One page per real service-plus-area question, each opening with a self-contained 40–60 word answer. "Do you offer same-day service in [neighborhood]?" is a page. "Our Services" is not.
5. Add LocalBusiness schema
LocalBusiness, along with Service, FAQPage, and OpeningHoursSpecification. This is machine-readable context, and it is a large part of how models resolve which business a query refers to.
6. Earn third-party mentions in your area
Local press, neighborhood blogs, chamber listings, community roundups, "best in [city]" articles. AI recommends by consensus, and for local queries the consensus is assembled from exactly these sources.
7. Show up where locals actually discuss it
Most cities and many neighborhoods have an active subreddit, and "can anyone recommend a good [trade] in [city]" is one of the most common post types on them. Those threads rank in Google and are heavily cited by AI engines — Reddit is the single largest source in AI citations overall.
This is the lever local businesses almost never pull, and it is the cheapest one available. You do not need a marketing budget to answer a neighbor's question in your own city's subreddit. Our free subreddit finder will locate the local communities; the warm-up guide covers doing it without getting your account filtered.
What to measure
Build a prompt set the way a customer would phrase it, and run it monthly:
- "Best [service] in [city]"
- "[Service] near me open on Sundays"
- "Who should I call for [problem] in [neighborhood]?"
- "Is [your business] any good?"
- "[Your business] vs [local competitor]"
Run each across ChatGPT, Perplexity, Gemini, and Google AI Overviews, logged out, and record whether you are named, cited, or recommended. The scoring methodology is here, and our free AI visibility checker runs the live citation check for you.
The realistic sequence for a small team
- Month 1: Claim and complete Google, Bing, and Apple profiles. Fix NAP consistency everywhere. Add LocalBusiness schema.
- Month 2: Build a review-request habit that asks for specifics. Publish three or four pages answering real local questions.
- Month 3: Start participating in your city's subreddit and local forums. Pitch one local publication.
- Ongoing: Run the prompt set monthly. Track whether you moved from absent, to mentioned, to recommended.
Expect the Google surfaces to respond first, because they lean on signals you already control. ChatGPT is the slowest, because it needs third-party corroboration to accumulate — which is precisely why so few businesses are recommended there, and why getting in early is worth the effort.
Frequently Asked Questions
Why does my business rank in Google Maps but never get recommended by ChatGPT?
They use different inputs. Google's local pack leans on your Business Profile and proximity signals; ChatGPT leans on the Bing index and third-party sources. The overlap between businesses that do well in both is only around 45%.
Does Google Business Profile help with AI visibility?
For Google's own AI surfaces, substantially — AI Overviews and Gemini both lean on it. For ChatGPT and Perplexity it matters much less, which is why Bing Places and third-party mentions have to be part of the plan.
How long does it take to appear in AI recommendations?
Profile and schema work can show up in Google's AI surfaces within weeks. ChatGPT and Perplexity typically take longer because they depend on third-party sources accumulating — expect two to four months of consistent work.
Do reviews affect AI recommendations for local businesses?
Yes, and the wording matters more than the count. Models match the language in reviews to the language in queries, so reviews that name specific services and situations are far more useful than generic five-star ratings.