Strategy

Only 1.2% of Local Businesses Appeared in ChatGPT Recommendations

A 2026 study of nearly 350,000 locations found 1.2% ChatGPT recommendation coverage. See what it measured and how to audit your own markets.

Dylan Allen-Arnegård, CEO & Co-Founder, Cheers8 min readPublished February 24, 2026Updated July 10, 2026

Visibility gap

Find the missing proof

A branch can be easy to find in search yet still lack the public evidence needed for a confident recommendation.

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Cited

Cited-source coverage

Ask ChatGPT for the best HVAC company in your city. It gives you one name, maybe two. Ask Gemini. Same thing. Now ask yourself: why that business and not yours?

The answer starts with how the study defined and measured coverage.

Data from SOCi's 2026 Local Visibility Index, which analyzed nearly 350,000 locations across 2,751 multi-location brands, reported recommendation coverage of 1.2% for ChatGPT, 11% for Gemini, and 7.4% for Perplexity in its sample. For comparison, the study reported 35.9% visibility in Google's local 3-pack. If you need to benchmark one location before building a full scorecard, start with What Is a Good AI Visibility Score for a Local Business?.

That is a large measured coverage gap inside this study. It does not mean ChatGPT can recommend only 1.2% of all local businesses, and it does not explain the ranking mechanism behind each answer.

Important

Read these percentages as coverage within SOCi's query set, brand sample, and methodology. AI answers can return one business, several businesses, or no local recommendation at all.

Plumber tightening a P-trap under a sink — AI visibility breaks when a strong local business has too little machine-readable proof.

The shortlist math

Google shows you options. Here are three plumbers. Pick one. The user makes the decision.

AI answers often compress the visible shortlist, although the number of businesses varies by prompt and product. The customer may still verify sources, read reviews, visit websites, or run another search.

This changes what teams need to measure. A local 3-pack displays three businesses, while an AI answer may name one business, several businesses, or none. Visibility in one format does not guarantee a mention in the other. Multi-location teams should measure that by market, prompt, and source, using a workflow like How to Audit AI Search Visibility Across Locations.

And AI search is growing fast. ChatGPT hit 800 million weekly active users by October 2025, up from around 400 million in early 2025. Google reported at I/O 2026 that AI Mode has passed 1 billion monthly users, with queries more than doubling every quarter since launch.

These products are large enough to measure alongside traditional local search.

What the study does and does not explain

The study measures which brands appeared. It does not publish the internal decision rules used by ChatGPT, Gemini, or Perplexity. Operators can still audit four observable areas:

Cited sources. Record the exact pages used in the answer and whether they accurately describe the business.

Public business facts. Correct wrong phone numbers, addresses, hours, service areas, and branch relationships across the sources customers and crawlers can reach.

Customer evidence. Maintain a policy-compliant review program and useful proof of real work. Do not treat review count, wording, or recency as a known AI ranking factor.

Prompt coverage. Test the services and markets that matter, because one brand-level prompt can hide branch-level misses.

What to compare among businesses that appear

Do not infer causation from the winners alone. Compare the businesses that appear with those that do not across observable artifacts, then verify each suspected gap.

Review coverage. Compare legitimate review presence by location and platform, including whether the profile reflects current services. Treat correlations as audit leads, not proof of a ranking factor.

Location clarity. Check whether the branch page, profiles, and applicable structured data agree on the location, services, and contact path.

Fact accuracy. Prioritize wrong or outdated facts over harmless formatting differences.

Independent sources. Record whether relevant local reporting, trade associations, directories, or community discussions appear in the cited results. Do not manufacture mentions.

Useful media. Photos and videos can help customers inspect real work. If YouTube or another media source appears in the answer, document it; do not assume adding video will cause a recommendation.

Pro Tip

Treat a citation as evidence about the source used for that answer, not as proof of a ranking factor or a guaranteed click.

The earned media factor

This is the part most businesses miss completely.

Owned-page and listing cleanup matter, but third-party pages also appear in some answers. The weight of those sources varies and is not publicly documented.

Independent sources such as Reddit, YouTube, news outlets, industry publications, and review platforms may appear in citations. Yext reported that 86% of citations in its sample came from brand-managed sources, which includes profiles a business can maintain but does not own.

YouTube is worth checking when videos appear in your category's answers. An Adweek analysis reported a 16% YouTube share in the source set it studied, but that figure is not a local-business ranking weight.

Reddit can also appear in cited answers. Treat genuine customer discussion as public feedback, not as a channel to seed recommendations.

Independent mentions cannot be purchased in the same way as an owned profile update. Treat them as earned evidence, not as an optimization shortcut.

Next step

Is AI recommending your business?

Find out how visible you are across ChatGPT, Gemini, Perplexity, and AI Overviews.

Check Your Visibility

Or book a demo

The multimodal edge

Businesses that rely on text-only web presence are leaving visibility on the table.

Photos, videos, detailed service pages, and applicable structured data can make a site more useful to customers and easier to inspect. Public evidence does not show that adding each format automatically raises recommendation confidence.

Use media when it documents real work, explains a service, or answers a buyer's question. Do not create it only to satisfy an assumed ranking signal.

What the study means for multi-location teams

Do not multiply the study's 1.2% coverage rate across your own location count. The useful next step is a location-level baseline using the services, markets, prompts, and providers that matter to your business.

Dallas and Houston can produce different answers because they have different branch pages, profiles, reviews, competitors, and service facts. Measure each market instead of relying only on the parent-brand result.

If 40 of your 100 locations have conflicting public facts, incomplete service pages, or profiles that no longer match the real branch, that is 40 separate audit targets. It is not proof that an AI product will exclude those locations, but it is enough reason to correct customer-facing errors and retest the relevant prompts.

Centralized ownership helps keep those public facts and workflows current. Hello Sugar used a centralized review process across its franchise network, but that review growth should not be presented as proof of a universal AI recommendation effect.

A 90-day audit and cleanup plan

Days 1-30: Foundation.

Audit every location's review profile. Count reviews, check recency, read the actual content.
Run a citation consistency check across Google, Yelp, BBB, and your top industry directories. Document every inconsistency.
Implement or fix LocalBusiness schema markup on every location page. Use specific subtypes (Plumber, BeautySalon, etc.).
Set up AI monitoring: ask ChatGPT and Gemini about your business category in every market you serve. Document what they say.
Use the Cheers AI Visibility Grader to get a focused one-profile baseline across ChatGPT, Gemini, and Perplexity in about 1-3 minutes.

Days 31-60: Velocity.

Launch a systematic review collection program and monitor new reviews per location per month. Focus on consistency, detail, and compliant customer asks rather than only stars.
Fix material source errors first: wrong phone numbers, old addresses, conflicting hours, incorrect services, and duplicate profiles.
Add photos or video where they document real local work or answer a buyer's question.
Update thin or inaccurate service and location pages. Do not create a page for every keyword variation.

Days 61-90: Amplification.

Make accurate information available to relevant local news, industry publications, associations, and communities when there is a real story or resource to share.
Add applicable schema only when it matches visible content and the page's actual entity relationships.
Re-test AI recommendations. Track changes from your Day 1 baseline.
Record which source and answer changed. Do not attribute the movement to one tactic without enough repeated evidence.

Pro Tip

Track your AI visibility monthly. Ask the same questions across ChatGPT, Gemini, and Perplexity for every market you serve. This becomes your GEO scorecard.