Model market share
Updated June 20, 2026 · Reviewed by the Quratic editorial team
Definition
Model market share is the relative usage of AI answer engines — ChatGPT, Perplexity, Google AI Mode, Gemini, Copilot, Claude, and local platforms — within a given country or audience segment. It determines which engines a GEO program must prioritize; optimizing only the US-default stack misses where buyers actually ask questions.
Not every market runs on ChatGPT
Global thought leadership assumes ChatGPT-plus-Google covers “AI search.” In practice, engine mix varies by country, language, device, and cohort — enterprise buyers vs consumers, mobile vs desktop. Model market share is the weighting function for GEO investment: track the engines that carry category research in your market, weighted by importance.
How to use share data strategically
If Perplexity leads research prompts in Singapore but Google AI Mode dominates in Tokyo, playbooks diverge: Perplexity rewards citable docs and third-party reviews; Google layers reward index depth and structured data. A single global content calendar ignores the weighting.
In Asian markets
This metric is the quantitative backbone of the Asia-anchored glossary. Quratic samples from residential IPs per country because model market share is geographic — US panel data misallocates budget. Pair share data with prompt surfacing so you track the right engines on the right prompts.
Example
An agency client deck weights visibility targets 50% Google AI surfaces / 30% Perplexity / 20% ChatGPT for Singapore, but flips to heavier Google + local answer engines for Korea — aligning KPIs with measured share instead of US defaults.