Glossary

LLM Visibility

LLM Visibility is an umbrella term for how often and how favourably large language models surface a brand — vendors package it differently, but the core inputs are prompts, models, and dated snapshots.

Not a single mathematical standard — always ask which prompts and which models.
Closest Getllmspy equivalents: LLM-Score, Share of Voice, GPI.

Definition

“LLM Visibility” is industry shorthand for measuring whether ChatGPT-class assistants recommend, mention, or cite your brand when buyers ask category questions. Agencies may show dashboards, heatmaps, or share-of-voice bars. Because there is no universal formula, the useful question is always operational: Which prompt pack? Which geography? Which model endpoints? Without those, two vendors can report wildly different “visibility”.

How it's computed

Common ingredients: (1) a fixed or organic prompt set, (2) multi-model execution, (3) mention detection + sentiment + hallucination flags, (4) aggregation into a headline score or rank. Some tools emphasise citations, others emphasise raw mentions — clarify before comparing numbers.

How it works in practice

Translate marketing speak into checks

Ask for the exact prompt list or sampling method.
Ask whether competitors are in the same denominator (SoV style) or not.
Demand dated snapshots so you know if ChatGPT updated overnight.

How to read it

Treat “visibility up 20%” as suspicious unless the vendor discloses denominator changes, new models added to the bundle, or new prompts inserted into the pack.

When to use

When evaluating a new monitoring vendor.
When PR asks for an external buzzword mapped to internal KPIs.
When you need a single slide title but still document the underlying metrics.

LLM-Score Share of Voice (SoV)GPI™ (Generative Presence Index)Brand visibility check

Benchmark visibility with Getllmspy