From SEO to AEO for Optimizing LLM Output in E-commerce Applications

This paper proposes a methodological framework for transitioning from traditional Search Engine Optimization (SEO) to a new paradigm-Answer Engine Optimization (AEO)driven by Large Language Models (LLMs) and multimodal Generative AI systems.The study contrasts the architectural philosophies of leading LLMs, such as GPT-4o and Claude, illustrating how Custom Instructions, Constitutional AI, and long-context design affect enterprise-grade deployment.It introduces a structured approach to product description generation and content optimization in e-commerce, emphasizing Semantic Clarity, Schema.orgmarkup, and Extraction-Readiness as prerequisites for LLM citation and highquality output.The framework ultimately positions LLM-optimized content as a structured, machine-interpretable data object, offering a foundation for next-generation e-commerce systems that integrate conversational commerce, multimodal diagnostics, and automated technical support.