Detailed Definition
AI models generate text stochastically (governed by temperature and top-p sampling). Repetition Consistency evaluates whether a brand is recommended every single time a prompt is asked or only sporadically.
Formula / Calculation Standard
Consistency (%) = (Identical Mention Outcomes / Total Repetition Cycles) × 100Why It Matters for Brands
A brand that appears 10 out of 10 times has high consumer reliability, whereas a brand that appears only 2 out of 10 times suffers from prompt variance.
How Fameproof Measures It
Fameproof runs a minimum of 2 repetition cycles per prompt/model pairing to calculate variance and 95% confidence intervals.
Read Full Evaluation Methodology →Example Entities Measured with this Metric
Related Terms
Generative Engine Optimization (GEO)The methodology of optimizing brand presence, canonical entity representation, and authority to increase mentions in generative AI answers.Unaided Prompt Mention RateThe frequency with which an AI model organically mentions an entity when asked neutral, category-level questions without referencing the entity by name.AI Visibility ScoreA composite 0–100 score measuring an entity's mention frequency, ordinal prominence, category coverage, and repetition stability across AI models.
Related Research Articles
Generative Engine Optimization (GEO): The Complete Guide to AI Model Visibility in 2026Discover how Generative Engine Optimization (GEO) differs from traditional SEO, how ChatGPT, Claude, and Gemini evaluate entities, and how to measure unaided AI visibility.Why ChatGPT, Claude, and Gemini Recommend Different Brands (And How to Audit Them)Why does ChatGPT list OpenAI and Apple first while Claude emphasizes Anthropic partners or open-source leaders? Learn the architectural and pre-training reasons behind model variance.