When you ask an LLM whether it recommends your product, you're running a test where you're both the subject and the observer, from inside the system you're measuring. Here's a clean-room protocol to test it properly.
Canonical URL: https://aeogeoai.net/blog-why-checking-your-own-ai-visibility-lies
You want to know whether ChatGPT recommends your product. So you open it and ask: "What's the best tool for X?" Your product shows up. You close the tab, reassured.
You just ran a broken experiment.
Not because the answer was wrong, but because of how you got it. You queried a system you're trying to measure, from inside that system, using an identity it already associates with the thing you're measuring. Every variable that should have been controlled was contaminated. If a colleague showed you that methodology in a code review, you'd reject it.
