AI chatbots are increasingly steering customers to the wrong locations, wrong websites, and outdated contact details for UK retailers. A new study tested ChatGPT, Google's Gemini, and Perplexity with over 72,000 questions about British high street retailers' locations, contact information, and brand identity. While the chatbots answered nearly all queries, one in 16 answers contained false information, and 64% of businesses had at least one falsehood returned about them.

The errors carry real consequences. Wrong postcodes appeared in one in 10 location answers, and in 15% of cases where the address was incorrect, the AI sent customers 20 miles or more away from the actual shop. About one in 15 website answers pointed to a dead link, a lookalike site, or a completely different business.

Why Are Some AI Engines More Accurate Than Others?

Accuracy varied significantly across the three AI engines tested. Perplexity returned false answers 10% of the time, compared to 4% for ChatGPT and 5% for Gemini. This variation matters because different users rely on different platforms, and a retailer might appear correctly in one engine while being misrepresented in another.

Who Gets Hurt Most by AI Inaccuracy?

Small retailers suffer disproportionately from AI chatbot errors. Large brands have a deep pool of third-party sources for AI systems to learn from, including news coverage, review sites, and industry publications. A small shop's online footprint may consist of just one website and a Google Business listing, giving AI systems less accurate material to work with. This creates a compounding disadvantage: smaller businesses are less visible in AI answers to begin with, and when they do appear, the information is more likely to be wrong.

The stakes are high. A Rithium survey of UK and US shoppers found that 90% use AI products for product research and 53% use them to choose a retailer. Critically, 58% of shoppers lose trust in a brand when AI gives them wrong product information. For a small retailer already struggling with visibility, a single wrong postcode in an AI answer can mean lost foot traffic and damaged reputation.

How to Improve Your AI Visibility and Accuracy

• Keep Your Website and Directory Listings Current: Update your business website regularly with accurate contact details, hours, and location information. Ensure your Google Business listing is complete and matches your website exactly, since AI systems rely on these sources to learn about your business.
• State Essential Services and Details Clearly: Use clear headings and structured information on your website for things like address, phone number, website URL, and key services. AI systems are better at extracting information from well-organized pages than from dense prose.
• Cultivate Local Press Mentions and Trade Association Listings: Build your third-party citation footprint by getting mentioned in local news, trade association directories, and review sites. These sources shape how AI systems describe your business and provide the "backup" information AI engines use when verifying facts about you.

As AI answers increasingly displace traditional search results as the first point of contact between customers and businesses, monitoring what chatbots say about your company is becoming essential hygiene. It is the AI-era equivalent of checking your Google Business listing.

What Does This Mean for the Broader AI Search Landscape?

This research reveals a critical gap in how AI systems handle factual accuracy for small and medium-sized businesses. Unlike search engines, which rank pages by relevance and authority, AI chatbots generate answers by retrieving and synthesizing information from multiple sources. When a business has limited online presence, AI systems have fewer sources to cross-reference, making errors more likely.

The problem is not unique to retail. As businesses across industries compete for visibility in AI-powered answer engines, the discipline of Answer Engine Optimization (AEO) is emerging as a critical marketing function. AEO involves structuring your digital presence so that AI engines find you, understand you, and recommend you accurately. For climate tech companies, logistics platforms, and other specialized sectors, this means ensuring that your website copy, third-party citations, and structured data all speak the language AI engines use when describing your category.

Enterprise marketing teams are beginning to build dedicated workflows to track how their brands appear in AI-generated answers across multiple engines and languages. Platforms designed specifically for AI visibility monitoring now track mentions across ChatGPT, Claude, Perplexity, Gemini, and other engines, measuring not just whether a brand appears but how it is described and which sources the AI cited to justify its answer.

For small retailers and SMEs without dedicated marketing teams, the path forward is simpler: keep your information current, make it easy for AI systems to find and understand, and build your presence on trusted third-party platforms. The cost of inaction is growing as more customers turn to AI chatbots to find where to shop.