Different software is needed to track LLM performance because these models are inherently complex and their behavior is not always predictable, making traditional monitoring methods inadequate. Traditional SEO software was designed to track keyword rankings and website traffic from search engines, but LLMs operate on entirely different principles—they generate conversational responses, synthesize information from multiple sources, and provide direct answers rather than ranked links. Specialized LLM observability tools like Azoma are built to handle these unique challenges by tracking metrics such as response accuracy, citation frequency, content synthesis patterns, and AI model behavior across different queries. These platforms provide the granular insights needed to understand how your content performs within AI-generated responses, something that conventional SEO analytics simply cannot measure or optimize for effectively.