AEO & GEO, defined.
The terms we use across AEOsim: clear definitions for the language of AI search visibility. Glossaries are frequently cited by AI engines.
AEO (Answer Engine Optimization)
Optimizing content so that answer engines (ChatGPT, Perplexity, Gemini, Claude, AI Overviews) cite and recommend your brand in their answers.
GEO (Generative Engine Optimization)
Optimizing for visibility in generative AI engines. Often used interchangeably with AEO; AEOsim covers both.
Citation share
The share of citations or recommendations your brand receives across a set of prompts and engines, relative to competitors.
Answer convergence
The degree to which an AI engine's answers stabilize around a consistent set of brands across runs and phrasings. The 'N-space' in BEACON is the optimized prompt space convergence is measured over.
Conversation analytics
Measuring how brands enter, persist, drop off, and win across multi-turn AI conversations, not just single snapshots. The core of Analytika.
Mention persistence
Whether a brand stays present across turns of a conversation, vs being mentioned once and then dropped.
Turn-wise drop rate
The rate at which a brand drops out of an AI answer as a conversation progresses across turns.
Share of voice
How much of the AI answer's attention (mentions, recommendations, citations) your brand captures vs competitors.
Pre-launch A/B simulation
Simulating two content variants against AI engines before publishing, to predict which will be cited more. The core of AEOsim's BEACON engine.
Attribution
Tying a change in citation share to the specific content change that caused it, closing the feedback loop between simulation and outcome.
Probe
A single query run against an AI engine to measure how it cites brands. AEOsim runs millions of probes.
Item Response Theory (IRT)
A measurement framework from psychometrics AEOsim uses to model prompt difficulty and information gain, which peaks at P=0.5.