How an independent business gets recommended by ChatGPT when chains start ahead

How far ahead chains start in AI answers

When someone asks ChatGPT for a gym or a hair salon in their city, the assistant answers with a short list of names. AIGROW Labs counted how many of those names belong to chain outlets and compared that with the businesses that actually exist around the same city.

The study read answers that ChatGPT, Claude and Gemini had already given for the November 2026 edition of the AIGROW AI Visibility Index. It took 200 local Index pages at random, 10 in each of 20 countries, covering 22 kinds of business in 88 cities, and 7,198 answers came back on them. Each business an assistant named was matched to OpenStreetMap, the open map drawn by volunteers, which also records whether a place carries a brand or belongs to a chain operator.

That is 1.87 times the expected share, with a 95% interval from 1.52 times to 2.50 times. Each assistant on its own did much the same: ChatGPT named 2.02 times the expected share of chains, Claude 2.10 times and Gemini 1.99 times. Compared within the same page, a chain outlet on the map was 2.51 times as likely to be named as an independent business.

A second sample of 713 pages, larger but not drawn at random and limited to businesses that list a website, gave 1.95 times.

Independents were still most of the businesses named: 692 of the 863. Most businesses on the map are independent too, so an independent can be named. It starts from behind, and how far behind depends on the trade.

Where chains start furthest ahead

The study found the gap in a few trades. The table shows the businesses the three assistants named on the random pages, the share of chain outlets among them, and the share the map around the same pages predicts.

Each kind of business rests on 9 or 10 pages, so a row shows a direction and its exact size is uncertain. In hair salons the ratio is large because chains are rare on the map: 5 chain salons among the 62 named are already 9.36 times the expected share. In car repair, a workshop tagged with the one car make it serves counts as a chain outlet, since it is usually a franchised dealer; without car repair pages chains get 1.75 times the expected share overall.

The larger sample of 713 pages points the same way. In gyms, 70.2% of the 346 businesses named were chain outlets, against 19.2% expected. In hair salons it was 25.4% of 169 against 4.3%, in real estate agencies 48.4% of 285 against 15.4%, and in dentists 12.0% of 191 against 4.7%.

If you run a restaurant or a hotel

Restaurants went the other way: 1.3% of the 223 restaurants named were chain outlets, against 2.6% expected. In the larger sample it was 4.3% of 897 against 4.5%. Hotels showed a small tilt on the random pages, 1.25 times, and none in the larger sample, 52.1% of 336 against 51.8%.

Your rivals in the answers are mostly other independents, and the steps below still apply.

What the study cannot say is why

The study counted businesses, not their size, footfall, reviews or web presence. A chain gym may simply be larger and better known, and the assistants may be reflecting that. The study measured how large the tilt is and left its cause open.

The steps below are the groundwork an independent controls; the study did not test them.

What an independent can do

These steps put complete, matching facts about your business wherever an assistant may look for them. Start with the first, because it shows where you stand before you change anything.

1. See what the assistants say now

Run the free AI scan on your business. It needs no account and takes about three minutes. It asks the models behind ChatGPT, Claude, Gemini and Grok through their APIs, without web search.

Then ask ChatGPT the question a customer would type, such as "a good gym near the station in your city", a few times. Write down the businesses it names and which of them are chain outlets. That list is your starting point, and the one to compare against later.

2. Be the same business everywhere

Use one name, one address and one phone number on your website, your Google Business Profile, Bing Places, Apple Business Connect and the directories of your trade. The free NAP consistency checker compares them for you.

In the study, 74.7% of the 22,859 specific names the assistants gave could not be tied to exactly one business on the map. Some businesses were missing from it, some names were spelled differently, and some did not exist. A business that goes by one name on its sign and another in a directory is harder for any program to tie together.

Check that your business is on OpenStreetMap with its real name, address and trade. The study notes that the map likely misses more independents than chains, because chain outlets are often added in bulk from brand lists. An owner may add or correct their own business, it costs nothing, and it is one more place where your facts are written the same way.

3. Say what you are on your own site

Add LocalBusiness markup to your home page and contact page, with the most specific type that fits your trade, such as ExerciseGym, HairSalon, RealEstateAgent, AutoRepair or VeterinaryCare. Give the address, the opening hours and the phone number exactly as they appear on your Google Business Profile, and list your profiles under sameAs. The free local business schema generator writes the code.

A short example for a gym:

{
  "@context": "https://schema.org",
  "@type": "ExerciseGym",
  "name": "Example Strength Studio",
  "url": "https://example.com",
  "telephone": "+1 555 0100",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "12 Example Street",
    "addressLocality": "Example City",
    "postalCode": "00000",
    "addressCountry": "US"
  },
  "openingHours": "Mo-Fr 06:00-22:00"
}

Then write down, in the words a customer would use, what you do that a chain outlet nearby does not: the classes you run, the hair types you specialise in, the car makes you know best, the neighbourhoods you sell in. An assistant can only name you for a need it can read about.

4. Give the assistants more than a name

Complete your Google Business Profile: the main category and any others that fit, your services, hours, photos and a plain description. Ask every customer for a review, and never offer anything in return or ask only the happy ones. Get listed in the directories and associations of your trade and your town, with the same facts each time.

Answer the questions customers ask before they call, each on a page of its own, such as whether you take walk-ins or what a first visit involves.

5. Check again, more than once

Assistants do not give the same answer every time. In the study, chains were named again and again across questions and runs: counting every time a business was named, not once, chains got 2.45 times the expected share. One answer is a sample.

Ask the same questions a few times before and after each change, and count.

Where AI Local Fix fits

The steps above take time, and most owners have little of it. AI Local Fix does the groundwork once, for one local business.

It claims, corrects or creates up to 15 listings on the directories assistants cite for your trade and country, completes your Google Business Profile and puts the same facts on Bing Places and Apple Business Connect. It adds LocalBusiness markup to up to 10 of your pages, writes 3 answer pages from the questions your customers ask, and prepares a reviews kit.

It also measures. Before the work starts, at day 30 and at day 90, it asks ChatGPT, Claude, Gemini and Grok 10 questions for your city that you approve, and counts how often they name you next to your 3 closest rivals. In a trade where chains lead the answers, those rivals can be the chain outlets down the road.

If the day 90 count names you no more often than the first, you can ask for a full refund within 14 days of the day 90 report. Nobody can promise a ranking in AI answers, and AI Local Fix does not.

What the study cannot tell you

• It measured how far the answers lean towards chains and left the cause open. A chain outlet may be larger or better known than the independents around it.
• OpenStreetMap is drawn by volunteers and likely misses more independents than chains; by how much was not measured.
• 74.7% of the specific names did not match one business on the map. Even if every one of them were an independent unless it carried a chain brand, chains would be at least 8.6% of the names, against 5.6% expected.
• Each kind of business and each country rests on 9 or 10 random pages, so a single row is a direction.
• All answers come from one edition of the Index, November 2026.
• AIGROW sells services that touch these findings, AI Local Fix among them. The study is a working paper, not peer reviewed, and its method, tables and limits are on the study page.