Stop Saying Generative Engine Optimization. It's Called Answer Engine Optimization

"Users are more prepared to buy than ever before when they arrive at your site from an answer engine. getty The Answer Engine Optimization industry has been infected by a terrible disease of terms that don't work. Whether it's ChatGPT or Google AI Overviews, Perplexity or Apple Intelligence, they're all providing answers to users questions. They're not providing generation. Generation is the mechanism that enables the AI platform to create end output the user is looking for: an answer."

"The argument is one of semantic value that provides greater clarity to the work that needs to be done and defines a category of content based on both business and user needs. What Does It Mean To "Optimize For Generation"? If you went to someone who didn't know what was going on and told them to make content for generative engine, what does that actually mean? Nothing. It sounds like a sci-fi technology that was made up in a lab."

"The confusion of generative engine optimization versus answer engine optimization began when Princeton and Georgia Tech researchers introduced " Generative Engine Optimization" in November 2023. With a bold opening, the researchers wrote, "This emerging technology, which we formalize under the unified framework of generative engines (GEs), can generate accurate and personalized responses, rapidly replacing traditional search engines like Google and Bing.""

Users arrive from answer engines with high purchase intent. The Answer Engine Optimization field suffers from imprecise terminology that conflates answering with generation. Platforms such as ChatGPT, Google AI Overviews, Perplexity, and Apple Intelligence deliver synthesized answers rather than pure generative output. Generation specifically denotes the mechanism that produces the final answer a user expects. Distinguishing answer engine optimization from generative engine optimization provides semantic clarity that aligns content strategy with both business goals and user needs. Proposed generative optimization frameworks can offer visibility gains but may obscure the practical functions of these systems.

Read at Forbes