Why ChatGPT may not recommend your product, and a DIY 20-minute audit to check

The author argues that AI assistants like ChatGPT answer category questions with a few brand names, so products left out lose visibility that analytics tools cannot measure. Large language models draw on training data, retrieved web pages, and how consistently a product is described across the web. The author proposes testing 12 prompts across four families on five AI models, scoring mention rate, position, sentiment, and cited sources, then repeating the check weekly. Key fixes include writing one canonical one-sentence description used everywhere, creating answer-focused pages, and getting listed in the directories and comparison pages that models already cite. The author also notes that results for retrieval-based models can shift within two to four weeks.