Every part of the pipeline, end to end. Nothing hidden, nothing hand-tuned.
When you enter a brand and category, Mentioned asks Claude to write 5 realistic questions a buyer would type when looking for a recommendation in that category — phrased the way a real person searches, not the way a marketer would ask. The questions never mention your brand name, so the test reflects an organic recommendation, not a leading one. If question generation fails for any reason, Mentioned falls back to a fixed set of neutral templates rather than guessing or skipping the check.
All 5 questions are sent to the model in parallel, each as its own independent conversation. There's no shared context between them and no hint about what brand is being tested — this mirrors what 5 different buyers asking 5 different questions would actually see.
Each answer is normalized (lowercased, punctuation stripped) and checked for your brand name as a substring. If it's there, Mentioned pulls the sentence containing it as the quoted snippet you see in your results — that snippet is copied directly from the model's output, never rewritten or summarized.
When your brand doesn't appear, Mentioned extracts other brand-shaped names from the answer — typically bolded names or items in a numbered/bulleted list — filtered against a list of generic words so "the best option" doesn't get counted as a competitor. This is a heuristic, not a guarantee it catches every name, but it never invents a competitor that isn't actually in the text.
Your score is simply: how many of the 5 answers mentioned your brand, out of 5. That's it — there's no weighting, no confidence interval, no adjustment. 3/5 means your brand showed up in 3 of the 5 independent answers.