business resources
Gemini vs ChatGPT Recommend Different Brands 58% of the Time: What Local Businesses Should Do About It
26 Oct 2026
A plumber in Peoria asks ChatGPT who to call. His rival across town asks Gemini the same question and gets a completely different shortlist. Neither list is wrong, exactly. They just don't match, and that mismatch is now a business problem.
The number behind it is blunt. A vendor study from Searchable put the overlap in recommended brands between the two assistants at 42% overlap across tens of thousands of questions. Flip that around and the engines disagree most of the time. For a national brand with a big footprint, that is an annoyance. For a regional operator, it can be the difference between being named and being invisible.
This piece breaks down why the split happens, why it hits state-level businesses harder than anyone, and what a sensible small firm can actually do about it.
Why two engines give two answers
It helps to stop thinking of ChatGPT and Gemini as search engines. They are answer engines, and each one assembles its answer from a different pile of evidence.
Gemini leans heavily on Google's own index, its Business Profiles, its maps data and its review ecosystem. ChatGPT pulls from a different mix of web sources, licensed content and whatever its retrieval layer fetches on the day. Claude and Perplexity add two more variations. Four engines, four slightly different worldviews.
Then there is the instability inside a single engine. Tech press testing has shown that the same prompt can return different product picks on different runs, which TechRepublic reported after comparing the two assistants side by side. So the disagreement is not only between engines. It is between Tuesday and Wednesday.
That is uncomfortable for anyone used to the old model, where ranking third on Google meant a predictable slice of clicks. There is no stable ranking to track. There is only a probability of being mentioned.
Why regional businesses feel it most
Big brands have a safety net. They appear in thousands of articles, forums, review pages and press releases, so almost any engine will stumble across them. A local firm has a thin trail. A handful of reviews, a directory listing, maybe a mention in a regional newspaper.
Thin trails break easily. If one engine happens to weight a source you're absent from, you vanish from its answers entirely.
Academic work backs this up. A recent audit of what ChatGPT, Claude, Gemini and Perplexity recommend across thousands of local venues found that most venues were never surfaced at all when compared against a complete market census. The long tail of local business is simply unseen by the machines.
And the stakes are rising because clicks are falling. Pew found that users are less likely to follow links when an AI summary sits above the results, so the name inside the summary is the only real estate left. Pew's own analysis of AI summary clicks shows the drop in link-following plainly. Miss the summary and you miss the customer.
State-level queries: where the engines really diverge
Broad national queries tend to converge a little. The big names float to the top everywhere. State-specific queries are where the maps come apart.
Take a query framed around a single state, say Illinois. The engine has to decide which regional sources count as trustworthy for that geography, whether the question is about personal injury lawyers in Chicago, HVAC contractors in Springfield or where to play slots and table games across the state’s casinos. Gemini may favour whatever Google already associates with the state. ChatGPT may reach for a different set of publishers. Each one treats a different handful of local resources as authoritative.
This is the part most small firms miss. The resources that engines cite for a state are not always the ones you’d expect. Niche regional guides, state-specific directories and category roundups get quoted because they are tightly scoped to a place, and casino guides show the pattern clearly. When someone asks where to find casino games, bonuses and trusted sites in Illinois, the answer depends on the state’s particular mix of land-based casinos and online options, according to New Game Network, and a guide built around that mix is exactly the kind of page an engine can quote cleanly. The same logic holds for a roundup of Chicago dentists or a directory of Peoria contractors: scoped, state-level pages get pulled into answers, and two engines may pull different ones.
What to actually do about it
You cannot control four engines. You can widen the net so that at least one of them finds you, and ideally all of them. Here is how.
Audit before you act. Ask each engine the same ten questions a customer would ask. Write down who gets named. Do it again in a week. You will see the churn firsthand, and you'll learn which engine ignores you.
Get listed where the engines already look. Directories matter again. Verified profiles on structured business listings, such as those found in a marketplace of vetted companies, give the machines something clean to quote. A listing that states your name, location, services and leadership in plain language is far easier for a model to reuse than a marketing page full of slogans.
Be specific about place. Generic copy loses. Name the city, the county, the neighborhoods you serve. Engines match local queries to local language.
Collect mentions, not just reviews. A line in a regional news story, a chamber of commerce page or a local roundup counts as evidence. Reviews help, but varied third-party mentions build the thick trail that survives engine-to-engine disagreement.
Measure on a schedule. Because answers drift, a single check means nothing. Monthly tracking across several engines turns a vague worry into a trend line you can act on.
The budget question
Small firms hear "AI visibility" and picture another expensive retainer. It doesn't have to be. Most of the work above is low cost: tidying listings, writing sharper local copy, asking partners for a mention. The audit itself costs an afternoon.
What it does demand is consistency. The firms that win here are not the ones with the biggest spend. They are the ones that check, fix, and check again.
Frequently asked questions
Why do ChatGPT and Gemini recommend different businesses?
They draw on different evidence. Gemini leans on Google's index, maps and business profiles, while ChatGPT blends other web sources and retrieval. Each weights sources differently, so the shortlists diverge, and even the same engine can change its answer between runs.
Does ranking well on Google guarantee a mention in AI answers?
No. A strong Google ranking helps with Gemini but says little about ChatGPT, Claude or Perplexity. Each assistant builds answers from its own source mix, so you need a presence across several kinds of third-party sources, not just your own site.
How often should a local business check its AI visibility?
Monthly is a sensible rhythm. Answers fluctuate from run to run, so a one-off check misleads. Ask the same set of customer questions across several engines, log who gets named, and compare month to month to spot real movement.
Are directory listings still worth maintaining?
Yes, arguably more than before. Structured, verified listings give models clean, quotable facts about your name, location and services. They also create the third-party mentions that make you easier to find across engines that disagree with each other.
What matters more for local AI visibility, reviews or mentions?
Both count, but varied mentions carry extra weight for thin local footprints. Reviews prove customer satisfaction, while press lines, chamber pages and regional roundups prove you exist in the wider record. A mix gives engines more places to find you.
The takeaway
The 42% overlap figure is not a quirk to file away. It is a warning that AI visibility is fragmented by design, and that the fragmentation punishes small, local operators first. The fix is unglamorous: be easy to find in many places, describe yourself precisely, and measure often. Do that, and the next time two engines disagree, you'll be on at least one of the lists.
Share
Peyman Khosravani
Industry Expert & Contributor
Peyman Khosravani is a global blockchain and digital transformation expert with a passion for marketing, futuristic ideas, analytics insights, startup businesses, and effective communications. He has extensive experience in blockchain and DeFi projects and is committed to using technology to bring justice and fairness to society and promote freedom. Peyman has worked with international organisations to improve digital transformation strategies and data-gathering strategies that help identify customer touchpoints and sources of data that tell the story of what is happening. With his expertise in blockchain, digital transformation, marketing, analytics insights, startup businesses, and effective communications, Peyman is dedicated to helping businesses succeed in the digital age. He believes that technology can be used as a tool for positive change in the world.
