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AI Visibility Overview

In this guide we'll introduce you to the key AI Visibility concepts of the Meltwater API and platform.

AI Visibility (powered by Meltwater GenAI Lens) lets you measure how your brand shows up when people ask questions of AI assistants and answer engines such as ChatGPT, Google Gemini, Perplexity, and Microsoft Copilot. As audiences shift from traditional search to AI-generated answers, AI Visibility data tells you whether - and how favourably - your brand is being surfaced, cited, and recommended.

This capability is often described in the market as Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO). Where GEO/AEO describe the practice of improving your presence in AI answers, the AI Visibility API provides the measurement layer that makes that practice possible.

Meltwater platform​

The Meltwater platform ingests and enriches data from a wide variety of sources, including news and social platforms. Data is enriched by a set of enrichments (sentiment, language, key phrases, etc.) and stored in a consistent data schema. The Meltwater application accesses these data stores to provide application features. The Meltwater API is built upon the same platform and data stores.

The AI Visibility feature extends this model to a new source: the responses produced by large language models (LLMs) and answer engines. Rather than monitoring what publishers and social accounts say about your brand, AI Visibility monitors what AI assistants say about your brand when prompted.

Key concepts​

Prompts​

A prompt is a question or instruction sent to an AI assistant - for example, "What are the best media monitoring tools?" or "Which PR agencies work with electric vehicle brands?". You define a set of prompts that represent how your audience is likely to ask about your category, brand, and competitors.

Models​

A model is the AI assistant or answer engine that responds to a prompt, for example ChatGPT, Gemini, Perplexity, or Copilot. The same prompt can return very different answers across models, so AI Visibility tracks results per model.

Responses​

A response is the answer an AI model returns for a given prompt at a given point in time. Responses are the raw material the platform analyses to determine whether your brand was mentioned, how it was described, and which sources the model cited.

Brand mentions and sentiment​

When a response references your brand, that is a mention. As with the rest of the Meltwater platform, mentions are enriched with sentiment so you can distinguish favourable, neutral, and unfavourable framing in AI answers.

Citations​

A citation is a source the AI model references to support its answer - typically a web page or article. Citation tracking tells you which sources are shaping what AI models say about your brand and category, so you can prioritise where to influence.

Share of voice​

Share of Voice (sometimes called Share of Model Voice) measures how often your brand appears in AI responses across your prompt set, relative to your competitors. This is the headline AI Visibility metric and mirrors the share-of-voice concept already used across Meltwater's Listening and Social Analytics products.

What you can do with the API​

The AI Visibility API lets you programmatically:

  • Fetch your GenAI Lens prompts and prompt folders - see Fetching Prompts
  • Fetch aggregate metrics, trends over time, and top terms for your prompts - see Analyzing Prompts
  • Measure share of voice for your brand against competitors surfaced in AI answers
  • Monitor how brand mentions and sentiment change over time