Customers are starting to ask ChatGPT, Claude, Gemini, and Perplexity which local business to trust. This quick audit helps you see whether AI assistants mention you, why they recommend competitors, and which public proof points to improve next.
I am a customer in [city/suburb] looking for [service]. Which local businesses would you recommend first, and why? Include what proof points would make you more confident in each recommendation.
Run this with your city, suburb, and service category. Save the businesses named, the reasons given, and any missing proof points.
Compare [your business name] with [competitor 1], [competitor 2], and [competitor 3] for a customer who needs [job/problem]. What would make a customer choose each one? What information is missing or unclear?
Use competitors that appeared in the first answer or show up in local search. Look for gaps in reviews, service pages, pricing clarity, photos, guarantees, and location signals.
Based on these AI recommendation gaps for [business name], create a prioritized action list for the website, Google Business Profile, reviews, FAQs, and service pages. Focus on fixes that would help both customers and AI assistants understand why we are a safe choice.
Only ship changes you can prove are true. Add specific service examples, before/after evidence, review language, FAQs, and location details where they are accurate.
Treat this as a customer-trust audit, not a trick for search engines. If AI tools do not know why your business is credible, real buyers probably need the same proof: clear service pages, reviews that mention outcomes, named locations, photos, guarantees, response times, and practical FAQs.
An AI visibility audit checks whether tools like ChatGPT, Claude, Gemini, and Perplexity understand who your business serves, when to recommend you, and which proof points make you credible compared with nearby competitors.
Run it once a month, and again after meaningful changes such as new service pages, stronger reviews, updated Google Business Profile details, fresh photos, or a new offer. Save the answers so you can see whether AI assistants start mentioning stronger evidence over time.
Start with public proof that helps real customers too: clear service-area pages, specific FAQs, reviews that mention outcomes, before-and-after examples, response-time promises, guarantees, staff credentials, and accurate location details.
Once the audit shows where customers and AI assistants lack proof, jump into the closest role library and build the specific messages, FAQs, review requests, and service content that close that gap.