Share of model (SOM) is the share of AI-generated answers in which your brand appears across a defined set of prompts and models. It is the AI-era counterpart to share of voice — a direct measure of how present you are in the AI conversation.
Where share of voice measures presence in earned media, SOM measures presence in AI answers. It answers a specific question: when people ask AI about your category, how often are you mentioned? That makes it the central metric for generative engine optimization and the number teams track to gauge AI visibility.
How Do You Calculate Share of Model?
Run a defined set of prompts against the major models, record whether your brand appears in each answer, and divide mentions by total answers. The result is your share. The value comes from segmenting it — by prompt set, model, and competitor — so you can see exactly where you win and where you are absent. Measuring share of voice in AI search covers the methodology.
What Is a Good Share of Model?
A "good" SOM depends on your category and how many competitors exist. The practical benchmark is relative: a brand should aim to grow its share quarter over quarter and to outrank its direct competitors on its priority prompts. How to track brand mentions across LLMs shows how to monitor changes over time.
Why Does Share of Model Matter for Growth?
AI answers now influence a meaningful share of discovery and buying decisions. DemandSage's ChatGPT statistics show how widely AI research is used, and Conductor's GEO benchmarks confirm brands are evaluated by AI before users visit their site. If you are not in those answers, you are absent at the moment of decision.
How Do You Improve Share of Model?
Improve it by building content that answers your priority prompts directly, strengthening entity presence so your brand is recognized, and keeping content fresh so it stays in the AI index. Each of these moves a prompt from "competitor mentioned" to "you mentioned." The AI search monitoring tools comparison helps you measure the progress.
How Conbersa Grows Share of Model for Brands
Conbersa combines structured content, entity-building distribution, and citation tracking to move the brands it works with from absent to present in AI answers. Our platform manages the full loop — publish extractable content, distribute it consistently, and measure where it appears across models — so share of model improves measurably.
We built Conbersa because share of model is the metric that tells you whether AI search is working for you at all. If you are not tracking it, you are flying blind in the channel that increasingly decides what brands people consider.