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How ChatGPT Decides Which Local Garages to Recommend

8 min readRecallIQ Editorial Team
ChatGPTAEOAI Search

ChatGPT doesn't have a map, and it doesn't crawl the web in real time. So when it recommends 'the best MOT garage in Leeds', how does it decide? The answer reveals exactly what independent garages need to do to get cited — and what's making them invisible right now.

Where ChatGPT Gets Its Local Business Data

ChatGPT (and most large language models) are trained on massive datasets scraped from the web. This includes business directories, review sites, news articles, forum discussions, and structured data from websites. The model builds an internal representation of which businesses are well-known, trustworthy, and relevant to specific queries.

For local business recommendations, ChatGPT combines this training data with retrieval from sources like Bing (for GPT-4 with browsing enabled), Yelp, and TripAdvisor. If your garage doesn't appear prominently in any of these sources, it's essentially invisible to ChatGPT's recommendations.

The Three Factors ChatGPT Weighs

1. Presence and consistency across directories: Garages listed on Google My Business, Bing Places, Yell.com, and Trustpilot with consistent name, address, and phone number (NAP data) score higher. Inconsistencies — even small ones like "St" vs "Street" in your address — create doubt.

2. Quality and quantity of reviews: ChatGPT considers review signals, particularly from Google and Trustpilot. A garage with 80 four-star reviews appears far more in AI recommendations than one with 5 five-star reviews.

3. Structured content that answers specific queries: Garages with FAQ content and schema markup that directly answers questions like "do you offer MOT for vans?" get cited for those specific queries. Generic business listings don't.

The Browsing Factor: Perplexity and Google AIO

Unlike base ChatGPT, Perplexity and Google's AI Overviews actively browse the web in real time when answering queries. This changes the optimisation approach slightly:

For Perplexity: Your website needs fresh, regularly updated content. Perplexity favours sources that were recently published or updated — a static website last touched in 2019 will rarely be cited.

For Google AIO: This is essentially traditional SEO plus structured data. Garages that rank in Google's top 5 organic results for "MOT [town]" have a strong chance of appearing in AI Overviews. The schema markup then determines whether they get cited specifically.

Practical Steps to Appear in ChatGPT Recommendations

Step 1: Complete and verify your Google My Business listing. This is the single highest-impact action. Make sure your category is "MOT Testing Station" or "Car Repair and Maintenance" — not just "Automotive".

Step 2: Build consistent listings on Bing Places, Yell.com, and Trustpilot. All with identical NAP data.

Step 3: Get to 50+ Google reviews. Focus on review velocity (consistent new reviews monthly) over total count.

Step 4: Publish structured FAQ content on your website or a claimed profile page. Target the specific questions drivers ask AI assistants.

How Long Until You Appear?

Changes to AI knowledge bases happen gradually. Most garages implementing a proper AEO strategy see their first ChatGPT citations within 6–10 weeks. Perplexity and Google AIO are faster — 3–5 weeks for recently published content.

The key is consistency. One optimised page won't sustain citations permanently. Monthly refreshes and new content keep your profile active in AI knowledge bases.

Put This Into Practice

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