AI tools returned at least one false fact about 64% of UK high street retailers in a vendor-run test, according to figures Searchable shared with Retail Focus. The most common error was placing businesses in the wrong postcode.
These tests point to something many marketing teams aren’t tracking. When AI systems such as ChatGPT or Google’s AI Mode answer questions about one of your locations, there’s no way to know what they’re saying about your business unless you manually check. They could be confidently claiming a business is closed, listing services they don’t offer, or giving a wrong address.
We’ve covered how to earn visibility in AI search, including Dan Taylor’s work on tracking AI prompts. This piece covers the other half of the problem. It looks at what AI is already telling people about your locations and how to find out before a customer does.
From Ranked To Described #
Traditional local search gives customers multiple options to compare, like a map pack, reviews, your website, or a competitor’s. Then, customers make their choice. AI search combines this process into a single synthesized answer that fully describes a business before the customer even visits the website or business profile.
Being described isn’t the same as being ranked; rankings can change, and descriptions might not always be accurate. Also, this visibility varies depending on the type of query.
Whitespark’s analysis found that AI Overviews appear in 15% of direct local-intent searches, like [personal injury lawyers in Phoenix]. For informational questions, they show up 92% of the time, and for hybrid questions, like whether to hire a lawyer after an accident, they appear 97% of the time. In the same study, local packs showed up for 93% of direct local-intent searches. Overall, AI Overviews were more common for informational and hybrid questions than for direct local-intent searches.
SOCi’s Local Visibility Index analyzed over 350,000 locations and found ChatGPT recommended 1.2% of them. That’s a far lower rate than the same brands’ appearances in Google’s local 3-pack, by SOCi’s own measurement. BrightLocal’s Local Consumer Review Survey found 45% of consumers now use ChatGPT or similar tools for local business recommendations, up from 6% the year before.
What The Answers Get Wrong #
Searchable released two sets of test results to trade press this month. In tests involving 165 London businesses, Searchable tested ChatGPT, Gemini, and Perplexity with 13,365 questions about services, contact info, size, and founding dates, then compared answers to Companies House records and official profiles.
According to CMOTech, 93% of these businesses had at least one basic fact that was wrong or missing. Half of the smaller businesses received at least one false fact, compared to 32% of larger companies. A second test examined UK high street retailers with over 72,000 questions. Retail Focus reported that one in 16 answers was incorrect. Wrong postcode errors occurred at a rate of one in 10, even when prompts specified the town.
Searchable co-founder Chris Donnelly told Retail Focus:
“For a smaller bricks-and-mortar retailer, if their online visibility mostly centres around its website and a Google Business listing, that’s a relatively thin trail of information for AI systems to learn from and to represent in their answers.”
The error categories match what business owners describe in Google’s support forums, reporting that they see wrong details presented confidently, and some say the errors are damaging their businesses.
The Blind Spot #
Traditional search leaves behind a trail of data. Impressions and clicks are tracked in Search Console; rankings fluctuate across trackers; and any drop often leads to an investigation. However, there’s no report that alerts businesses if an AI answer incorrectly states hours for your location or claims your business is closed.
Traditional search doesn’t alert you to how you’re represented either, but it doesn’t have to. It points customers to sources they can see and weigh for themselves, like your listing, your site, and reviews with dates attached. AI collapses those sources into a single written answer, and the customer reads it as fact. When it’s wrong, there’s no ranking position to watch and no traffic dip to trace, because the error lives in text you were never shown.
Major consumer AI tools generally don’t offer businesses an alert at the location level when their information is wrong. Google’s documentation states that AI responses may include mistakes, and individual AI Overviews carry a feedback link. This feedback serves to correct mistakes but isn’t a proactive monitoring system. It only works if someone notices the error first.
5 Systems, Not 1 #
The testing process can get complicated across various AI search platforms because they don’t work the same way. AI Overviews now appear as part of regular Google search results, AI Mode is a conversational experience right within Google Search. Gemini acts as Google’s separate AI assistant. Meanwhile, ChatGPT and Perplexity are separate products offered by OpenAI and Perplexity AI.
Each of these tools processes, selects, and combines information differently, so a single question might receive different answers depending on which platform you’re using. This variation is also seen in Searchable’s retail data, Perplexity was found to give inaccurate answers in 10% of cases, compared to 5% for Gemini and 4% for ChatGPT.
Testing one system tells you little about the others. A location that checks out in AI Overviews can still be misdescribed in ChatGPT.
How To Test What Customers See #
Start by thinking about questions your customers might have, like hours, services, or whether a location is good. Write these questions down in a standard list so each place gets checked the same way. Run the questions through AI Overviews and AI Mode in Google, plus ChatGPT, Gemini, and Perplexity. Where possible, test without saved conversation context or personalization, and keep track of the prompts and answers you get.
Since answers can vary each time, ask the same questions multiple times. Organize what you find into categories such as factual errors, missing info, or perception issues. Treat factual errors and omissions separately. Sentiment and recommendation order are reputation issues, not simple corrections. Pay special attention to fixing mistakes that could prevent someone from visiting, like incorrect hours or a branch reported as closed.
When sources are cited, verify that their information is accurate. Correct the information you control or ask for corrections when needed. Keep checking regularly because fixing a source today doesn’t automatically update the AI answers. Use a consistent list of questions and a log to make the process easier, especially if you have many locations. Change how often you check based on the number of locations and how often details change.
What To Do When AI Gets It Wrong #
Finding the error is the first step. Fixing it is about carefully adjusting the inputs these systems depend on, then checking whether the answers improve. Remember, each adjustment gets you closer to better, more dependable results.
If an answer got your hours wrong, confirm that your Google Business Profile, your website, and your own location pages agree with each other and with reality. Conflicting details across those are one of the clearest reasons an answer gets it wrong. The same name, address, and phone number consistency that local SEO has always required is the foundation, and it gets more complex once you run multiple locations. After correcting the sources you control, look at the sources you don’t own. When an answer cites your business, open it and check its date and what it actually says. It could be pulling the information from an old directory page, a review listing, or a page about a similarly named business. Fixing these issues will likely involve some direct outreach.
This is also where the size gap Donnelly pointed to starts to make sense. Smaller businesses drew more errors in Searchable’s tests, and his read was that a thin trail of third-party information gives these systems less to work from. Our own coverage of what correlates with ChatGPT citations reaches the same conclusion. A fuller, more consistent presence across the places these systems read gives them better material to describe you with.
If you find accuracy isn’t the issue, and you’re more concerned with getting recommended at all, that’s the visibility side. Dan Taylor has written for Search Engine Journal on tracking how AI represents your brand over time and how discovery changes as search personalizes around each user. Those are the places to start on the “how do we win here” question.
Looking Ahead #
Monitoring tools for AI answers are still in their early stages. Most can tell you whether you’re being mentioned and how often, which isn’t the same as telling you whether the mention is right.
Checking what an answer actually says about a location still comes down to reading it yourself. As these tools develop, that may change, but for now, the audit is manual, and when you find something wrong, the first move is to optimize the sources you control.
More Resources:
The Complete Guide To Local SEO For Multiple Locations68 Million AI Crawler Visits Show What Drives AI Search VisibilityMulti-Location SEO: How To Win Google & AI Search Visibility At Scale
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