The AI Search Competitive Analysis Prompt

Link to the prompts below 👇 In this video, we explain why AI visibility alone isn’t enough and what it really takes to get AI tools like ChatGPT to recommend your brand. We walk through how modern AI systems move buyers beyond awareness and into consideration, often before they ever visit a website. This video is for marketers, founders, and SEO leaders who are seeing traffic plateau but want higher-quality leads. We show how AI recommendations work, why they convert better than traditional search traffic, and how to diagnose whether AI would actually suggest your brand—or quietly exclude it. Here’s the breakdown. 0:24 Why “AI Visibility is insufficient” 1:10 Proof that AI is recommending brands 1:40 Basic AI Competition Audit 3:35 Buyer-specific AI Competition Audit 4:57 How your audience is prompting the AI 5:45 Example: How copy edits win recommendations from AI 6:22 Why AI didn’t recommend their brand We start by challenging the idea that “AI visibility” is the end goal. Being mentioned by an AI doesn’t help if the recommendation context is negative or neutral. We show a real prompt example where brands appear in AI responses but are explicitly discouraged, and why that distinction matters more than impressions or mentions. Next, we connect this idea to analytics and conversion data. We explain why traffic from AI tools often converts at significantly higher rates than traffic from traditional search engines. The key difference is intent: AI users are already comparing options, not just browsing them. That shift changes how brands should think about SEO, content, and messaging. From there, we walk through a practical AI perception audit. Using a real B2B example, we demonstrate how to analyze how AI training data portrays your brand compared to competitors. We show how to surface perceived strengths, weaknesses, and the patterns that influence whether an AI system is likely to recommend one company over another. We then go deeper with a buyer-specific A