Why AI visibility is hard to pin down
Most businesses meet AI search as a rumour: someone says a chatbot recommended a competitor, or described the company in a way that no one in the company recognises. When we run those same questions at scale, the pattern is consistent. An engine may describe a business accurately, may recommend it alongside rivals, may attribute it to the wrong website, or may not confidently identify it at all — and each engine does something different. Omniscient Digital's buyer's guide to generative engine optimization tools makes the structural point behind this: a tool "has to report on more than one of ChatGPT, Google AI Overviews and AI Mode, Perplexity, Gemini, Copilot, or Claude," because "your buyers are not all in the same place."
The method we use
SaidTrue starts from the questions customers already ask, not from a keyword list. Those questions are put to ChatGPT, Gemini, Perplexity and Claude, and for each answer we record three things separately: what was said, what was sourced, and where that diverges from the truth about the business. The result is scored using our published approach, so the number on a scorecard can be traced back to specific answers rather than to a general impression. Backlinko's round-up of AI visibility tools recommends a similarly bounded start — pick one tool, add three to five competitors, and track ten or more prompts for thirty days — which is why we favour a defined question set over an open-ended crawl. After the baseline, ongoing work is monthly monitoring paired with a verified AI profile, so the facts engines draw on are the business's own.
What customers can expect
Growth Method's comparison of visibility tools is blunt about the limits of reporting alone: "monitoring AI visibility is not, by itself, very useful. A dashboard that tells you ChatGPT recommends your competitors is just bad news on a schedule." Improving visibility means "covering the subtopics the AI answers include, earning citations on the sources they trust, giving them a direct answer worth quoting." That is why our reports lead with the sources engines actually cited and the points where their description is wrong, rather than with a single headline figure. Customers get a documented baseline, a public scorecard whose scoring can be examined, and a month-by-month view of whether the descriptions are moving. What we do not promise is a guaranteed position in an AI answer; nobody controls that output.
Sources
Backlinko, "6 AI Visibility Tools to Track Your Brand Across LLMs (2026)", https://backlinko.com/llm-tracking-tools
Omniscient Digital, "Top 10 Generative Engine Optimization Tools: A Buyer's Guide", https://beomniscient.com/blog/generative-engine-optimization-tools/
Growth Method, "AI Visibility Tools Compared: How They Actually Work", https://growthmethod.com/ai-visibility-tools/