The AI Visibility Scorecard: 7 Metrics Every CMO Should Track

Search has changed. Customers are no longer only typing keywords into Google and choosing from a list of blue links. They are asking longer, more specific questions inside AI-powered platforms such as ChatGPT, Google Gemini, Perplexity and Google AI Overviews.

This creates a new challenge for marketing leaders.

It is no longer enough to ask, “Where do we rank on Google?”

The better question is:

When a customer asks an AI platform for advice, does our brand appear in the answer?

This is where AI visibility tracking becomes essential. Brands need a practical scorecard that shows how often they appear, how accurately they are described, how they compare to competitors and which sources AI platforms are using to form their answers.

Here are the 7 AI visibility metrics every CMO should be tracking. For context on why this shift is happening, read our introduction to Generative Engine Optimization.

1. Share of AI Voice

Share of AI voice measures how often your brand appears in AI-generated answers compared to your competitors.

For example, if a customer asks:

“What is the best private bank for high-net-worth individuals in South Africa?”

The AI platform may mention several brands. Share of AI voice helps you understand whether your brand is being included, ignored or outperformed by competitors.

This is one of the most important AI search metrics because it shows whether your brand is visible at the point of recommendation.

2. Prompt Visibility

Prompt visibility measures how often your brand appears across a defined set of important customer questions.

These prompts should reflect real buying intent, category questions and customer concerns.

Examples might include:

• “What is the best business banking option for small companies in South Africa?”
• “Which pet food brand is best for dogs with sensitive stomachs?”
• “What are the top digital agencies in Cape Town?”
• “Which insurance company offers the best customer service?”

Prompt visibility helps you understand where you are showing up and where you are absent. It also helps marketing teams move beyond generic rankings and start tracking the exact questions that influence customer decisions.

Our guide to measuring AI visibility explains how to set up a practical prompt tracking framework.

3. Competitor Presence

AI search is comparative by nature.

Customers often ask AI platforms to recommend, compare or shortlist brands. That means your visibility needs to be measured in relation to the brands you compete against.

Competitor presence shows:

• Which competitors appear more often than you
• Which competitors are recommended ahead of you
• Which competitors are described more positively
• Which competitors are cited by stronger sources

This matters because AI-generated answers can shape perception before a customer ever visits your website. If your competitor appears consistently and your brand does not, the customer journey may be influenced before your brand has a chance to respond.

4. Citation Frequency

Citation frequency measures how often AI platforms cite your website, articles, reports, listings, reviews or third-party mentions.

In traditional SEO, ranking was the main visibility signal. In AI search, citations are becoming one of the new visibility signals.

But citation frequency should not only track your own website. It should also track which external sources are shaping your brand narrative. These may include:

• Media articles
• Review platforms
• Directories
• Forums
• Industry reports
• Comparison sites

This gives marketing teams a clearer view of the information ecosystem around their brand and identifies where new content or PR investment will have the most impact.

5. Citation Quality

Not all citations are equal.

Being cited by a respected industry publication, credible news site or trusted authority is very different from being cited by a weak, outdated or irrelevant source.

Citation quality looks at the strength and relevance of the sources AI platforms are using. A brand should ask:

• Are AI engines citing our own website?
• Are they citing current information?
• Are they citing credible third-party sources?
• Are they citing competitors more often than us?
• Are they relying on outdated or inaccurate information?

Citation quality helps identify where a brand needs stronger proof, clearer content or better third-party authority. For a full framework on building citation strength, read how to get your brand into AI results.

6. Brand Accuracy

AI platforms can mention your brand, but still get the details wrong.

They may describe your services incorrectly, miss key differentiators, confuse your offering with a competitor, or use outdated information.

Brand accuracy measures whether AI-generated answers describe your brand correctly. This includes:

• What your company does
• Who you serve
• Where you operate
• What products or services you offer
• What makes you different
• Which competitors you are compared against

7. Sentiment and Recommendation Strength

It is not enough to know whether your brand appears. You also need to know how strongly it is recommended.

Sentiment and recommendation strength look at the tone and confidence of the AI-generated answer. For example, an AI platform may say:

• “Brand A is a strong option for enterprise clients.”
• “Brand B is known for affordability.”
• “Brand C has mixed customer reviews.”
• “Brand D is often recommended for premium service.”

These statements shape perception. Your brand may be present, but not preferred. It may be listed, but not recommended. It may be mentioned, but with hesitation.

Tracking sentiment helps marketing leaders understand whether AI platforms are building confidence in the brand or creating doubt.

Why This Scorecard Matters

AI visibility is becoming part of brand visibility.

Customers are using AI tools to research products, compare providers, shortlist options and ask for recommendations. This means your brand's presence inside AI-generated answers can influence awareness, trust and conversion.

The brands that win in AI search will not only be the brands with the best websites. They will be the brands with clear positioning, strong content, credible citations, consistent third-party signals and measurable visibility across AI platforms.

For a deeper look at the connection between traditional SEO investment and AI visibility, read our SEO vs GEO comparison.

The New CMO Scorecard

The old scorecard focused on rankings, traffic and clicks.

The new scorecard needs to include:

1. Share of AI voice — are you present at the point of recommendation?
2. Prompt visibility — which buying-intent questions do you show up for?
3. Competitor presence — who is being recommended instead of you?
4. Citation frequency — how often do AI engines reference your content?
5. Citation quality — are you backed by trusted, current sources?
6. Brand accuracy — does AI describe your brand correctly?
7. Sentiment and recommendation strength — are you recommended with confidence?

Because the future of search is not only about being found. It is about being recommended.

Run a free AI visibility audit to see where your brand stands across all seven dimensions today. Or read our guide to measuring AI visibility to understand how to track these metrics over time.