How SaidTrue approaches a ChatGPT visibility checker
At SaidTrue we treat visibility in conversational AI as a measurable part of a business’s public profile. Customers come to us because they need to know what prospective buyers see when they ask ChatGPT, Gemini, Perplexity or Claude about a category, a local service, or a specific company. Common problems we encounter are brands that aren’t recognized by models, incorrect or outdated facts being asserted about a business, competitor names appearing where a client should be cited, and answers that lack clear sourcing or conflate similarly named organizations.
Common customer problems
Clients typically report three recurring issues. First, absence: the model fails to name the business when a real prospect would expect it to. Second, accuracy gaps: the model states incorrect hours, services, or reputation claims. Third, sourcing and traceability: the answer contains confident recommendations with no clear citation to a verifiable URL, making it hard to correct or escalate the error. These are problems because conversational models are increasingly a first stop for product or vendor research, not just a search-engine supplement (see AI Visibility Checker (FREE) for ChatGPT, Claude & Gemini | SEOcrawl AI — https://seocrawl.ai/ai-visibility-checker).
Method and steps we take
We run a disciplined, repeatable process. We ask the same customer-facing queries of the major conversational engines, collect their responses, and record whether the business is identified, how it is described, and whether the answer includes a named citation or links. We compare each model’s statements to the verified facts from the business website and public records, flag divergence, and annotate claims by type: identification, recommendation, factual detail, and sourcing. Our work is hands-on: we surface example prompts and the raw AI replies, then summarise where models agree, where they differ, and where correction is required.
How this differs from other checkers
Some tools produce a one-off snapshot or a short prompt set; for example, other providers generate buyer-discovery prompts and report a simple share-of-voice metric based on a handful of ChatGPT runs (see ChatGPT Visibility Tracker: Free Brand Citation Checker | Meev — https://meev.ai/chatgpt-ai-visibility-checker). We focus on diagnosis plus traceable evidence: the exact answers, the sourcing (if any), and the points of factual divergence.
Outcomes customers can expect
Clients receive a clear visibility report: the exact AI responses for key queries, where each model sourced its claims (if it did), a summary of mismatches against verified facts, and recommended next steps to reduce misidentification or misinformation. For businesses that subscribe to monitoring, we provide ongoing scans so changes in model behavior become an actionable trend rather than a surprise. The result is practical visibility control: know what’s being said about you in AI-driven recommendations, why it’s being said, and where to focus remediation.