5 AI Models, 4 Signals: What 120K Mentions Reveal About Multi-Location SEO

This station was sponsored by Uberall. The opinions expressed successful this article are the sponsor’s own.

How do I get my locations recommended by ChatGPT, Gemini, aliases Perplexity?

Do AI models prime section businesses the aforesaid measurement Google does?

Does reappraisal measurement aliases prima standing matter much for AI visibility?

We analyzed 120,000+ AI mentions crossed 3,793 locations and 5 models, from ChatGPT to Perplexity. Each exemplary has its ain personality, but they each reward the aforesaid signals, and marketplace stock isn’t 1 of them. Here’s what to attraction connected this month.

In This Report

1. 1. The Differences Between Each AI Model
2. 2. The 4 AI Mention Factors
3. 3. 3 Things to Do This Month
4. 4. Be a Local Role Model for All AI Models

The Differences Between Each AI Model

A specified twelvemonth ago, the verdict connected AI and section hunt was that it was beautiful beta-esque: Local results were still vague, missing images, and recommended places that weren’t moreover nearby.

Today, AI devices present much useful section results, much consumers usage them for section recommendations, and we cognize much astir wherever they propulsion business accusation from.

Beyond this, our caller in-house experiments astatine Uberall show america each exemplary has its ain proposal “personality.”

• Claude is the astir conservative. It favors section and organization businesses but mostly avoids naming circumstantial healthcare providers, apt reflecting be aware astir thing resembling aesculapian guidance.
• Gemini is the astir diverse, apt because it cross-references unrecorded Google Maps data. It surfaces 8× much unsocial restaurants than ChatGPT successful the aforesaid study.
• ChatGPT is consensus-driven and concentrated. It generates a short, sticky shortlist, but pinch the highest mirage rates crossed verticals.
• Grok it references cook qualifications and Instagram contented much than immoderate different model, and its responses publication for illustration long-form nutrient journalism: “must-try dishes,” cook names, cooking methods, and humanities context.
• Perplexity searches live, cites its sources, and generates the astir mentions per run. For businesses pinch beardown existent web presence, it’s the “easiest” exemplary to triumph on.

Multi-location brands person spent years learning Google’s “personality.” Now location are at least 5 much to fig out. Just for illustration marketers request to understand their customers, they request to understand what matters to each AI model.

Our Uberall information comes from 120,000+ AI mentions crossed 3,793 locations successful US cities from Chicago to New York, covering dentists, restaurants, market stores, hotels, and banks. Our soul GEO expert Katya Shishchenko looked for patterns accordant crossed industries and models; you’ve heard of ranking signals and factors, truthful let’s telephone these “AI mention factors.”

The 4 AI Mention Factors

I didn’t want to make an acronym, but since we’re personifying AI systems anyway, we mightiness arsenic good conscionable opportunity the models for illustration BARS:

• Business data.
• Authority.
• Review.
• Social.

Image created by Uberall, September 2026

This article lays retired what drives AI visibility crossed those 4 categories, earlier giving you the 3 things to attraction connected this month. None of it is exotic. It conscionable needs to beryllium done well, intentionally, and astatine scale.

Factor 1: Business Data

GBP completeness and richness, on pinch business age, find whether a section marque shows up successful LLM responses astatine all, not really often it appears erstwhile it’s mentionable.

Business property is evidently not influence-able, but the pursuing are, each pinch vertical-specific statistic from our study.

• A filled-out GBP description: This optimization tin mean a three-fold summation successful mention rates for market stores.
• Relevant attributes: Going from 6–10 attributes to 31–50 takes mention probability from 22% to 94% successful the edifice category.
• Photo count: It’s the azygous strongest predictor of edifice mention frequency. Top-mentioned restaurants mean 3 times much photos. Photo count is besides the only awesome successful dental that predicts some whether a believe gets mentioned and really often. And successful banking, it ranks among the 3 strongest predictors of AI mentions overall.
• Location count: More locations intends higher mention rates, reaching 100% astatine standard successful some market and dental categories.

Most of these factors get your brand’s ft successful the figurative doorway alternatively than determining really often you travel up successful AI conversations, but that makes them the correct spot to start.

Factor 2: Authority Signals

When we deliberation astir marque authority successful multi-location marketing, we typically deliberation of scale: endeavor brands, large footprints, large marketplace share. But crossed each 5 verticals, marque size (store count, believe count, deposit share, room supply) was a mediocre predictor of really often AI models urge a brand.

Size did power whether a marque sewage mentioned astatine each successful grocery, hotels, and banking, wherever chains use from signals LLMs picked up during training. For restaurants and dentists, independent brands tin and do outperform chains connected mention rates.

Aside from marque size, different authority signals find really prominently and consistently multi-location brands show up:

• Media mention frequency: Brands pinch 30+ news mentions saw a 15-fold wave summation successful banking and a 100% mention complaint successful grocery.
• Editorial database presence: Bankrate, Forbes Travel Guide, and Michelin mentions usability almost for illustration nonstop “ingestion” into LLM training data. Banks connected 3 aliases much editorial platforms spot a 13-fold mention increase; Michelin nickname shows up successful 94.5% of Perplexity’s edifice responses.
• Wikipedia presence: This is simply a reliable affirmative mention facet for hotels, market stores, and banks, though not for dentists.

Delivery level presence, connected Instacart, DoorDash, aliases Mercato, for example, does not power market stores’ AI visibility.

Earned media and editorial authority are still the agelong game. Our study simply reemphasized this, and the continued value of E-E-A-T. There’s nary faking aliases shortcutting your measurement onto a Michelin list, and that’s precisely what makes these signals truthful powerful erstwhile you’ve earned them.

Factor 3: Review Signals

Here’s the uncovering we deliberation is the large hit driblet of this article: Across each 5 verticals, reappraisal measurement predicts AI mentions. Star ratings are a weaker AI mention facet successful 4 of 5 business categories; wherever they do show up arsenic a signal, they’re ne'er the point driving visibility.

This is what our study recovered for 3 of the business types we analyzed:

• Dentists: No prima standing connected immoderate level reaches statistical significance.
• Grocery stores: Brands pinch higher reappraisal measurement but little ratings get mentioned 94.3% of the time, versus 60.6% for high-rated but low-volume brands.
• Banks: Higher aggregate ratings connected Yelp and TrustPilot really correlate negatively pinch mention frequency. That’s not because bad reviews help; it’s because the most-mentioned banks are the nationalist giants, and serving millions of customers intends accumulating complaints astatine scale.
• Hotels: The objection to the pattern. GBP prima ratings correlated much powerfully pinch AI mention probability and wave than reappraisal count.

When teams optimize their brand’s online visibility for reappraisal measurement (while, of course, not dropping their work standards), it matters wherever they cod and negociate their reviews. Which level matters astir depends connected the vertical.

While prima ratings aren’t ever a reliable AI mention factor, they still power the humans deciding which business to visit. My proposal is to optimize reappraisal measurement for the models, and support the standing for the people.

Factor 4: Social Signals

Instagram and Facebook are each mention factors, but they play different roles successful section AI visibility. Facebook gets brands into the generated response, Instagram gets them talked astir erstwhile they’re there.

Facebook followers heighten AI mention probability, meaning that business wins the mention successful the first place. For banks, follower count is the strongest societal AI mention facet overall, and dentist practices that get mentioned person almost 5 times the number of followers arsenic those that don’t.

Instagram beingness amplifies AI mention frequency. Restaurants pinch a beardown Instagram and Yelp beingness are mentioned almost 7 times much than those that don’t. For boutique hotels specifically, Instagram is the azygous strongest predictor of AI mentions, outperforming moreover GBP and editorial signals. And retrieve Grok’s persona from earlier; it references Instagram contented much than immoderate different model.

The takeaway is that regular activity and increasing your assemblage connected your societal profiles, crossed locations, is worthy the work.

3 Things to Do This Month

Based connected what we found, AI models consistently for illustration BARS, moreover if each exemplary “persona” ranks them somewhat otherwise by business type.

The brands showing up much consistently crossed AI models are regularly optimizing for each of these mention factors astatine scale, crossed each location, each profile, each reappraisal platform. It’s what we telephone Location Performance Optimization (I’ve spoken astir this astatine brightonSEO), and it’s really multi-location brands extremity relying connected marketplace stock and authority unsocial to show up successful section AI hunt results.

Our proposal fits connected a barroom napkin.

1. Complete Your GBP Profiles

Completing your GBP descriptions, attributes and categories astatine standard tin summation AI mention rates by 40 to 60 percent points successful immoderate verticals. And if your location profiles aren’t complete capable to get mentioned successful the first place, it doesn’t matter really galore reviews you’ve collected; there’s nary section business to amplify.

Our in-platform agentic AI UB-I keeps each location floor plan complete, fixes outdated ones aft quality review, and lists floor plan errors successful bid of hunt impact.

Screenshot of UB-I Agent Control Center Dashboard by Uberall, September 2026

2. Prioritize Review Volume Over Star Ratings

Across each 5 verticals and models, reappraisal measurement predicts AI mentions amended than ratings do. If your squad is spending astir of its power fixating connected a 4.3 rating, immoderate of that effort is amended spent gathering caller reviews crossed applicable platforms instead.

3. Increase Your GBP Photo Volume

Photo count is the number-one predictor of edifice mention frequency, the strongest awesome successful dental, and the 3rd astir important AI mention facet for banks.

Aim to upload 100+ value (and, ideally, location-specific) photos crossed your locations. For restaurants and hotels targeting top-tier AI positioning, purpose for 2,000+ photos.

A tip: Upload successful dependable increments alternatively than each astatine once. This signals an active, surviving business.

Be a Local Role Model for All AI Models

Local AI hunt isn’t successful its beta era anymore, and the optimizations teams should prioritize person go figure-out-able. Acronym-able, even.

The measurement multi-location brands turn their AI visibility is by gathering the models astatine the BARS: prioritizing semipermanent information correctness and coherence astatine scale, building authority that earns media and editorial mentions, consolidating societal impervious done reviews, and showcasing the acquisition of visiting them done photos.

Doing each of that crossed hundreds of locations is simply a batch of work, which is precisely why we built UB-I.

Image Credits

Featured Image: Image by Uberall. Used pinch permission.

In-Post Images: Images by Uberall. Used pinch permission.