You asked ChatGPT for the best version of your service in one of your cities, and a competitor came back. Or your brand came back, attached to the wrong branch. That stings, and it is one of the most fixable problems in multi-location AEO.
This guide hands you a repeatable system. One clean identity record per location, accurate Google and Yelp profiles, a review program that stays inside the rules, and a measurement loop that tells you which branch AI names and which source it shows. Let's start with the part most guides skip.
Get honest about what reviews can and cannot do
You control more here than you think. You just do not control the thing everyone obsesses over.
Four words are worth separating first.
- A mention names your brand or branch with no linked source.
- A citation exposes a link or source panel pointing at a page or listing.
- A recommendation suggests your business, and it can happen with no citation at all.
- Branch resolution means the answer landed on the right physical location, not the parent brand or another store.
Now the Google Business reviews AI question. Google says local results are based mainly on relevance, distance, and prominence, that prominence can include how many reviews you have, and that more reviews and positive ratings can help local ranking. Complete, accurate information is more likely to show, and nobody can pay for a better local ranking.
Those are statements about local Search and Maps. They are not a formula for AI Overviews, AI Mode, ChatGPT, or Perplexity.
Yelp AI citations are the clearest evidence that these profiles get pulled into AI answers at all. BrightLocal's July 2025 study ran 20 searches across 10 industry niches on Google AI Mode, Gemini, Perplexity, and ChatGPT Search. Yelp showed up as a source in roughly a third of searches, and Perplexity used Yelp in every industry tested. The study logged sources the systems listed, whether or not each shaped the answer, so read it as direction rather than a rule.
No platform publishes a review count that guarantees a citation, a rating that guarantees a recommendation, or a weighting for recency, sentiment, or response rate. That is the real shape of the AI recommendations local reviews question, and it is why testing beats theorizing.
So the honest goal is not "make AI cite our Yelp page." It is to make every branch easy to identify, accurate everywhere it appears, genuinely reviewed, and measured. That is the whole of local review profiles AI search work, and it is very doable.
Step 1: Build one canonical record for every location
Build the inventory before you edit anything. It is boring, and it makes later steps cheap. Give each branch a permanent key, then fill a row per location:
| Field | What to keep branch-specific |
|---|---|
| Branch key | A permanent internal ID, never a campaign name |
| Public name | The real-world name on the signage, no keyword padding |
| Address | Full street address, suite, and the correct map pin |
| Phone | The direct local number where one exists |
| Website | The specific location page, not the homepage |
| Category | The narrowest accurate primary category |
| Hours | Regular, holiday, and temporary hours |
| Service area | Only where you travel to customers |
| Services and attributes | Only what that branch really offers |
| Profile IDs | Google profile, Yelp page, other listings |
Add coordinates, claim status, and a response owner, then cross-check each row against the signage, the location page, the Google profile, the Yelp page, and any other listing customers use.
Google's guidance is useful discipline here. Your information should reflect how the business is represented in the real world, the address or service area must be accurate, categories should be the fewest needed, and duplicate profiles cause display problems in Maps and Search. Running 10 or more locations? Google offers bulk management through a business group and a spreadsheet upload, with errors corrected before verification.
How you know it is done: every location has one row, one Google identity, one Yelp page (or a documented reason it has none), one location page, and a named owner. No two branches share an address, phone, or URL by accident.
Where people go wrong: padding a public name with a city or "best" phrase, spinning up a second profile because the first is hard to access, or pointing every branch at the homepage.
Pro tip: push the branch key into every internal workflow. Review exports, profile audits, prompt tests, and location pages become joinable, and you stop matching records on a fuzzy branch name.
Step 2: Map the local prompts each branch should win
You cannot improve what you never asked. Build a prompt matrix per branch, not one list for the whole brand, covering these intent families:
| Intent family | Prompt pattern |
|---|---|
| Near me | [service] near me, from that branch's area |
| City or neighborhood | best [service] in [city] |
| Open or available | [service] open on [day] |
| Attribute | [service] with [parking, access, or language] |
| Specific fact | Does [branch] offer [service]? |
| Experience | Which [service] has strong reviews for [need]? |
Lock the location into the wording first. Then run a true near-me version from a controlled search location, because distance is a real local factor and ChatGPT can use general IP-based location, or precise device location when a user opts in to share it.
Record the prompt, date, search location, engine, answer, branch named, and whether the source shown was a Google profile, a Yelp page, or your location page.
One search is not a result. Local answers move with distance, wording, hours, and freshness.
This is where a tracking layer earns its keep. DeepSmith's AI Visibility module stores these questions in Prompts, and Discover Prompts generates a starter set from your product, persona, and buyer-stage context. You get per-prompt mention rate, citation rate, and answer history instead of a screenshot folder. Engine coverage follows your plan: Pro tracks ChatGPT, Grow adds Perplexity, Scale adds Gemini, Enterprise covers all ten.
How you know it is done: every priority branch has prompts across discovery, factual lookup, availability, experience, and near-me intent, with a baseline answer and source list saved.
Where people go wrong: tracking only branded queries, testing all 40 branches from one head-office chair, and logging "we appeared" without recording which branch and which source.
Step 3: Make every Google Business Profile unambiguous
Your Google Business reviews AI work starts with the profile underneath the reviews. If the profile is fuzzy, the reviews attach to a fuzzy entity.
For every branch, in order:
- Claim and verify the profile. Verification tells Google you are authorized to represent it.
- Confirm the real-world business name, the full address and map pin, or the service area if you travel to customers.
- Set the fewest categories that describe the core business.
- Add regular hours plus special and holiday hours.
- Add the local phone, attributes, photos, and description.
- Point the website field at the location page, not the homepage.
- Check profile status after edits, because Google reviews changes before they go live.
- Hunt for duplicate or suspended profiles and document each resolution.
Treat the profile as the branch's public source of truth, not as ad copy.
How you know it is done: someone who has never visited can identify the exact branch from the name, address, pin, phone, hours, category, and location page.
Where people go wrong: letting one polished corporate profile substitute for branch profiles, stacking every category you might qualify for, and forgetting a temporary closure that later shows up in an AI answer as fact.
Step 4: Claim and shape the Yelp page for each branch
Yelp pages represent individual locations, so a single brand page cannot stand in for 30 branches. Claim and audit each one, and watch these specifics:
- A normal location page needs a full address. Providers without one can use a ZIP code or service area, and Yelp discourages publishing a residential address unless you want it public.
- The phone field is not built for extensions, and Yelp advises against national call-center numbers.
- The website field should lead to your own site, not a directory or social profile. With no website, Yelp says leave it blank.
- One login can claim pages for up to nine businesses or locations, per Yelp's April 2025 multi-location guide. Larger portfolios should use Yelp's multi-location support path rather than improvise an account structure.
Then audit category, hours, description, services, and photos against your branch record.
Understand Yelp's recommendation software before you plan anything around review volume. It evaluates every review against hundreds of signals covering quality, reliability, and user activity, then recommends the ones it considers helpful. Reviews that are not recommended stay reachable through a link, but they do not count toward the star rating or review count, and no Yelp employee can override that.
That single fact kills the "just get more reviews" plan. Volume generated the wrong way may never touch your public rating.
How you know it is done: every branch has a claimed page with a correct address or service area, a direct local phone, the right branch URL, and branch-specific hours and photos.
Where people go wrong: reusing one address, phone, or photo set across locations, dropping a directory link in the website field, and arguing with a not-recommended review.
Step 5: Run a review and response program that stays inside the rules
This is where multi-location teams get nervous. The rules are clear once you separate the platforms.
Asking on Google
Google gives you a review link and QR code workflow inside the Business Profile. Share it after a genuine experience and keep the ask neutral. Offering free or discounted goods or services in exchange for posting, changing, or removing a review is prohibited.
Do not gate. Sending happy customers to Google while routing unhappy ones to a private form is sentiment selection, and it is exactly what regulators now name.
Asking on Yelp
You do not. Yelp's rule is that businesses must not ask for reviews and must not offer incentives, and its software is designed to spot reviews it believes were solicited.
The permitted path is organic: deliver a service worth talking about, respond genuinely, keep the page easy to find, and keep information accurate so customers recognize it.
Responding
Give every branch a response owner and one service standard.
On Google, verify the business first, then reply from the review area. Google checks replies for policy compliance, an approved reply appears publicly as a business response, and the reviewer is notified and can still change what they wrote.
On Yelp, a claimed page can reply with a public Comment or a Direct Message, and Yelp suggests starting with a Comment. If your account manages several pages, select the correct location first.
Keep the structure safe: thank the customer without repeating private details, acknowledge the experience, state the correction, invite an offline conversation, and never argue about motives.
Common mistake: the campaign that says "happy with us? leave us five stars." It may spike volume for a week. It also selects for sentiment, risks platform action, and runs into the FTC's rule on fake reviews and testimonials, which covers incentives tied to sentiment, insider reviews, and suppressing negative feedback. Treat that as a guardrail, not legal advice, and check the rules where you operate.
How you know it is done: each branch has a neutral Google ask, no gating, no Yelp solicitation, a named response owner, and a log showing why any review was flagged. "It was negative" is never the reason.
Step 6: Give every branch an owned page that agrees with its profiles
Profiles are borrowed ground. Your location page is the one source you fully control.
Build or audit one page per branch, with the essentials near the top in plain language: branch name, full address and map context, direct phone, regular and special hours, the services available there, real attributes like parking or accessibility, and a way to contact it.
Then mark it up properly. Google's structured data guidance says to define each location as a LocalBusiness type, use the most specific subtype available, include name and address as required properties, and consider properties like geo, telephone, and url, with a working URL for that location.
One caution worth taping to your monitor: schema is not a way to import a Google or Yelp rating onto your own site.
Supporting content helps too: a service explainer, a local FAQ, a page that answers what your branch gets asked. That is where DeepSmith's Content Studio fits. The Writer turns a planned idea into a researched, brand-grounded article with SEO and AEO formatting, links, metadata, and a cover image, and Deep IQ keeps your approved facts, services, personas, and voice in one place so 30 location pieces do not drift into 30 brands. It does not verify profiles or manage listings. That stays with your local team.
How you know it is done: a human and a crawler identify the same branch from the page's name, address, phone, URL, and structured data, and every external profile points at that page.
Where people go wrong: one "our locations" page with no branch URLs, LocalBusiness markup copied across sites with the wrong coordinates, and rewriting a review into brand copy and presenting it as a quote.
Step 7: Measure the answer and the source, location by location
Now you find out whether any of it worked. This loop is the spine of multi-location AEO, and it works per location, never per brand. Track these fields:
| Measurement | The question it answers |
|---|---|
| Mention rate | How often does the engine name the brand or branch? |
| Citation rate | How often does it link an owned page or show a source? |
| Branch resolution | Is the named branch the one the query meant? |
| Source type | Google, Yelp, your page, another directory, or something else? |
| Factual accuracy | Are address, hours, services, and attributes right? |
| Share of voice | Which competitor branch wins the same prompt? |
| Failure reason | Identity, distance, relevance, or a missing page? |
Two rules keep this honest. A mention without a link is not a citation, and a Yelp link does not prove every review on that page shaped the answer.
Save the prompt, location, engine, answer, source panel, and timestamp every time, so you compare like with like. Re-test after any material change to a profile or page.
DeepSmith's AI Visibility views map onto this directly. Overview gives you mention rate, citation rate, share of voice, trends, and the sources cited most. Prompts holds the tracked questions and answer history. Pages shows which owned pages get cited and which prompts drive them. Competitor Citations shows who is winning and on which pages. Read it against your plan's engine coverage.
How you know it is done: for every priority branch you can answer four questions. Were we mentioned? Was it the right branch? Was the source the one we intended? And who won when we did not?
Step 8: Fix the failure you actually saw, then retest
Do not guess. Let the observed failure choose the fix.
| What you saw | First fix to test | What not to do |
|---|---|---|
| AI picks the wrong branch | Reconcile name, address, phone, pin, category, and local URL; clear duplicates | Do not add a city keyword to the name |
| AI names the brand, no branch | Add branch facts and a real location page, then test near-me wording | Do not expect a homepage to resolve a location |
| AI cites a stale page | Fix the link and structured data, update hours and services | Do not add unsupported review schema |
| AI lists a service you lack | Correct the profile, page, and category, then find the operational source | Do not ask reviewers to insert keywords |
| Real negative themes surface | Fix the experience, respond well, keep collecting genuine feedback | Do not gate, threaten, or buy removal |
| A Yelp review is not recommended | Stop any solicitation and let organic activity run | Do not request a replacement review |
| A competitor is cited instead | Compare their branch facts, local page, and source coverage | Do not accuse them of fake reviews |
When the gap is real and the fix is content, DeepSmith's Opportunity Agents turn it into ideas with the evidence attached: getting cited for a tracked prompt, converting mentions into citations, and fixing how AI describes you. Content Map shows where competitors cover topics you have nothing on, and Autowrite moves the idea into a scheduled build.
None of that changes a rating, a review, or a listing. It produces the evidence around them.
How you know it is done: every fix ties back to a documented failure, the record and the live profile are updated, the prompt is retested, and the result is logged as improved, unchanged, or unresolved. Unresolved stays unresolved in the report.
What to do next
Do not start with all 60 locations. Pick five priority branches, finish the inventory, clean their two profile ecosystems, set the review and response rules, and run the same prompt set twice a month. That is a local review profiles AI search program you can actually sustain.
Everything above is the AI recommendations local reviews loop, run on purpose instead of by accident. Your next improvement should come from a recorded failure mode, never a guess about review counts.
If measurement is the missing half, automate that before you scale the manual half. DeepSmith tracks how AI engines answer your buyers' questions, shows which sources and pages earn the citations, and produces the on-brand content that closes the gaps, in one platform. Start a 7-day free trial and baseline your locations before you change anything else.
You are closer than this list makes it look. Most of it is one careful afternoon per branch.
