An AI brand audit measures what ChatGPT, Gemini, Perplexity, Claude, and other AI engines say about your brand when buyers ask about your category. A good audit scores four things \u2014 presence (do you appear), accuracy (are the facts right), sentiment (how you are described), and share of voice (how you rank against competitors) \u2014 across every major platform, not just one.<\/p>\n\n\n\n
Buyers increasingly ask AI assistants for recommendations before they ever reach Google. When someone asks “What’s the best tool for [your category]?”, the model returns a short list \u2014 and if your brand is missing, misdescribed, or ranked below competitors, you lose the deal silently. An AI brand audit is the process of systematically checking what these models say about you, so you can fix what is wrong before it costs you customers.<\/p>\n\n\n\n
This is different from traditional brand monitoring, which tracks what people say about you on social media and news. An AI brand audit tracks what the models themselves<\/em> tell your potential customers \u2014 a newer, increasingly decisive battleground.<\/p>\n\n\n\n The most common mistake is opening ChatGPT and asking, “What do you know about [my brand]?” This feels intuitive but produces misleading results. When you name your brand, you prime the model to talk about it \u2014 so you learn what it can say when prompted, not whether it mentions you on its own when a real buyer asks a neutral question.<\/p>\n\n\n\n Two more mistakes follow from this: checking only one model (each describes you differently, so one platform gives a false picture), and auditing once and assuming it holds (model updates shift answers without warning). A real audit avoids all three.<\/p>\n\n\n\n Score your brand on four dimensions across every platform. Together they turn a vague impression into a number you can track over time.<\/p>\n\n\n\nThe wrong way most people audit their AI presence<\/h2>\n\n\n\n
The right way: a 4-dimension scoring method<\/h2>\n\n\n\n