# A Research-backed Guide to Brand Representation in AI ## What Limits Current Approaches to AI-powered Search Optimization ### **Share of Model (SOM)** ### **Answer Engine Optimization (AEO)** ### **LLM Optimization (LLMO)** ## Rethinking Brand Visibility in AI-powered Search ### A Taxonomy of AI Interfaces (and Why It Matters) #### Foundational Systems #### Hybrid Systems (Generative Engines) ### The Components of AI-powered Search Optimization #### Optimizing for Large Language Models #### Optimizing for Search Engines ##### Technical SEO #### Optimizing for Generative Engines ##### Introducing: Generative Engine Optimization (GEO) ###### Research Methodology ###### How to Improve Source Visibility ###### Mixing and Matching GEO Methods for the Most Impact #### GEO Strategy by Market Position ## Answering Our Core Questions (everything below is under construction) 🚧 ### **Can we measure and improve brand representation in AI-powered Search?** #### Measuring AI Representation #### Three Layers of Improving AI Representation ### **Do our existing Marketing, SEO, and PR strategies and tactics transfer to AI-powered search?** ## How PR and Marketing Pros Can Move Forward ## The Future of Brand Visibility in AI-powered Search