How to Measure Your Brand's AI Visibility (and What Good Looks Like)

One of the most common questions we hear from marketing teams is: “I've made changes to improve our AI visibility — how do I know if they're working?”

It's a fair question. Unlike traditional SEO, there's no position 1 in an AI answer, no impressions report, no click-through rate. But that doesn't mean you can't measure GEO performance rigorously. You just need a different framework.

The core AI visibility metrics

1. Mention rate

The percentage of queries — across your tracked question set — where your brand is mentioned in the AI's answer. A mention rate above 70% across your core queries is strong. Below 30% is a concern.

2. Per-engine breakdown

Your mention rate across ChatGPT, Gemini, Perplexity, and Grok will differ — sometimes dramatically. Understanding which engines mention you tells you where your optimisation efforts should focus.

3. Share of voice

When an AI engine answers a question about your category, who does it mention? Share of voice measures how often your brand is named relative to competitors across your tracked query set.

4. Sentiment

Being mentioned is good. Being mentioned positively is better. AI engines don't just name brands — they describe them in context. Tracking whether your mentions are positive, neutral, or negative helps you understand whether your visibility is actually working in your favour.

5. Visibility trend

Single-point-in-time measurements are useful, but trends are where the insight lives. Is your mention rate improving month over month? Tracking your GEO score over time gives you the feedback loop you need to know whether your optimisation work is paying off.

What “good” looks like

• GEO score 70+: Strong. Your brand is consistently mentioned across most engines and queries.
• GEO score 40–69: Moderate. You're visible in some contexts but not others. Targeted content and entity work will move the needle.
• GEO score below 40: Weak. Your brand is largely invisible in AI answers. The good news: the fundamentals are well-established and can be fixed systematically.

How often should you measure?

Monthly measurement is the right cadence for most teams. AI models update their training data and retrieval patterns on cycles that make weekly measurement noisy and quarterly measurement too slow to catch problems early.

The three questions to ask about your results

1. Am I mentioned more than last month?
2. Am I gaining or losing ground against my top competitors?
3. Are there specific engines or queries where I'm consistently missing?

These three questions will guide 90% of your GEO strategy. If you can answer them confidently every month, you're measuring well.