Best AI Visibility Tool: Track ChatGPT & Google AI Mentions

The digital marketing landscape is currently navigating its most disruptive inflection point since the inception of the search engine. For two decades, SEO was defined by the "blue link" economy. We optimized for keywords, obsessed over metadata, and fought for a top-three position on a static results page. Today, that reality has been superseded by an AI-first search environment. Users are no longer just "searching" for information; they are engaging in non-deterministic, generative conversations. Whether through ChatGPT Search, Google AI Overviews, or Gemini, the interface between the consumer and the brand has moved from a directory of links to a synthesized answer engine.

In this new era, traditional rank tracking, while still necessary for baseline traffic, is insufficient for brand dominance. The core problem for modern marketers is the "AI blind spot." You might maintain a #1 organic ranking for a high-value transactional keyword, but if an AI model synthesizes a comprehensive answer and fails to mention your brand, or worse, cites your competitor as the sole authority, your traditional ranking is effectively invisible to the user. Understanding how these Large Language Models (LLMs) perceive, cite, and recommend your brand is the new prerequisite for growth.

To navigate this, you need a command center built specifically for the Generative AI era. The AI Visibility Toolkit from Semrush has emerged as the definitive solution for this challenge. This isn't just another monitoring tool; it is a sophisticated suite designed to track brand mentions, analyze sentiment at a granular level, and identify visibility gaps in AI search. It is the bridge between traditional SEO and AI discovery, ensuring that your brand doesn't just exist in an index but is actively recommended by the AI assistants that users trust.

Strategist Note: We are moving from SEO to AEO (Answer Engine Optimization). In traditional search, you competed for clicks. In AI search, you are competing for "weights" in the model's RAG (Retrieval-Augmented Generation) pipeline. If you aren't being cited, you don't exist in the user's immediate decision-making window.

Before you can optimize, you must have a baseline. The Visibility Overview report is where every AI SEO campaign begins. It translates the abstract concept of "AI presence" into a quantifiable metric: the AI Visibility Score.

The AI Visibility Score is a benchmark value ranging from 0 to 100. Unlike traditional visibility percentages which are often based on click-through rate (CTR) estimates, the AI Visibility Score is a relative metric. It is calculated by measuring how often your brand is mentioned in AI-generated answers compared to the median number of mentions for your top industry competitors.

Strategist Note: Why use the median? AI search is non-deterministic. Results can vary by session. By benchmarking against the industry median, which Semrush identifies automatically for your domain, you get a stabilized view of your market authority that accounts for the inherent "hallucination" or variability risks of LLMs.

To interpret your performance over time, the report offers three distinct lenses:

1. Main Metrics (Mentions, Cited Pages, Citations): Mentions refer to any instance where your brand name appears in an answer. Cited Pages are the specific URLs the AI uses as references. Citations are the total count of those references. If your "Cited Pages" count is low but "Mentions" are high, it suggests the AI "knows" you but doesn't yet "trust" you enough to link back to your deep content.

2. Monthly Audience: This is an estimation of the reach your brand achieves through these AI mentions. It helps communicate the "value of the mention" to stakeholders who are used to seeing impressions and reach in traditional media reports.

3. AI Visibility: A trend line that maps your score over time. A sudden drop here, unmatched by a drop in traditional rankings, often indicates a model update or a change in how the LLM prioritizes certain source types (e.g., shifting from blogs to forums).

The toolkit provides granular breakdown modules that are essential for global resource allocation:

• Distribution by LLM: This module identifies exactly which models (e.g., GPT-4o, Gemini) are referencing your brand. If you dominate in ChatGPT but are absent from Google AI Overviews, your strategy must pivot toward the specific "E-E-A-T" (Experience, Expertise, Authoritativeness, and Trustworthiness) signals Google’s Search Generative Experience prioritizes.

• Mentions by Country: AI search is not monolithic. The Visibility Overview supports a "Worldwide" scale but also allows you to drill down into 40+ specific countries.

For the global strategist, the ability to see performance across the following regions is a game-changer for localizing AI authority: Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Finland, France, Germany, Hong Kong, India, Indonesia, Ireland, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, Norway, Panama, Peru, Philippines, Poland, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Arab Emirates, United Kingdom, United States, Uruguay, and Vietnam.

In AI search, visibility is often a zero-sum game. When an AI model provides a list of the "Best Enterprise CRM Software," it typically limits itself to 3–5 recommendations. If your brand isn't in that synthesized list, a competitor has captured 100% of that discovery opportunity.

The Competitor Research report allows you to enter your domain and add up to four rivals for a side-by-side comparison. The strategic "gold" in this report is the identification of Topic & Prompt Gaps. These are specific prompts where your competitors are consistently cited as a source or mentioned in the generated answer, but your brand is excluded.

To close these gaps, an expert strategist follows this manual remediation process:

1. Export the Gap List: Download the CSV of prompts where you have 0% visibility but competitors have >0%.

2. Analyze the "Preferred Source": Look at the "Cited Pages" for those prompts. Is the AI citing a competitor's blog, a third-party review site, or a social media thread?

3. Reverse Engineer the Authority: If the AI prefers a competitor's page, use the Semrush SEO Toolkit to analyze that page's structure. Is it using "schema.org" markup that makes it easier for LLMs to parse? Is the content length more "digestible"?

Strategist Note: Often, you'll find that you aren't missing the content, but you're missing the "citation footprint." This is where you leverage the PR and Social toolkits to ensure that the third-party sites the AI trusts are also talking about you.

The way users interact with AI is fundamentally different from traditional search. They have moved from "fragmented keywords" to "structured dialogue." Traditional keyword research tells you what people type; Prompt Research tells you what people ask.

Backed by the largest US prompt database (over 261 million prompts), this tool allows you to move from targeting keywords to targeting entire conversations. By entering a broad topic or product category, you can discover the actual conversational queries the audience is posing to platforms like ChatGPT and Perplexity.

• AI Topic Volume: This is an estimation of how often a particular conversation or topic is queried within AI environments. High volume indicates a core pillar for your content strategy.

• Intent: Just as in traditional SEO, understanding the user's need (Informational, Transactional, Navigational) is crucial. In AI SEO, intent helps you decide the "tone" of the answer you want to influence.

• Topic Prioritization: By viewing volume and difficulty side-by-side, you can build a roadmap.

Strategist Note: For B2B clients, I prioritize "High-Intent/Low-Volume" prompts. If someone asks an AI for a "step-by-step comparison of [Brand A] vs [Brand B]," that user is at the very bottom of the funnel. Being the cited source for that answer is worth more than a top-of-funnel mention for a generic term.

In the world of Generative AI, "mentions" are only half the battle. Because LLMs "synthesize" information, they don't just show your brand; they describe it. If the training data or RAG sources are peppered with negative reviews or outdated information, the AI will confidently state that your brand is "overpriced" or "lacks customer support." This is why the Brand Performance suite is essential for reputation management.

The Share of Voice vs. Sentiment chart is a high-level visualization that plots your brand against competitors on two critical axes.

• High SOV / High Sentiment: The "Dominant Authority" quadrant. You are mentioned often and favorably.

• High SOV / Low Sentiment: The "Reputation Risk" quadrant. You are being talked about, but the AI is synthesizing a negative narrative. This requires immediate "remediation of crawl-budget bottlenecks" on negative sentiment sources (like fixing issues on public review forums).

• Low SOV / High Sentiment: The "Undiscovered Gem" quadrant. You have a great reputation, but the AI doesn't have enough data to cite you frequently. You need more "LLM Seeding."

• Perception Report: This monitors sentiment trends over time. If you launch a major campaign or product update, you can track how long it takes for that "new reality" to be reflected in the AI’s synthesized descriptions of your brand.

• Narrative Drivers: This report identifies the Top Cited Domains and specific questions shaping your story. If a specific industry blog is being cited by AI every time your brand is mentioned, that blog becomes your #1 PR priority.

• Questions Report: This provides a granular look at the specific prompts driving the market conversation. You can see the exact language the AI uses to frame your brand vs. your competitors.

AI models are non-static; they are updated, retrained, and fine-tuned constantly. This means your visibility can shift overnight. Prompt Tracking, integrated within the Position Tracking tool, allows you to monitor your AI performance with the same rigor as traditional rankings.

Within Position Tracking, you can select specific AI environments as your "search engine":

• ChatGPT Search

• Google AI Mode

• Gemini

Once selected, you add your priority prompts. The tool provides daily updates on your Visibility and Average Position within the generative response.

One of the hardest parts of AI SEO is proving its value alongside traditional SEO. The Devices & Locations tab allows you to compare your AI rankings side-by-side with your traditional Google rankings. If you can show a client that you hold the #1 organic spot and are the primary citation in the AI Overview for the same query, you are demonstrating total search dominance. This side-by-side view is the definitive way to report on "Total Visibility" to stakeholders.

You cannot be cited by an AI if the AI’s crawler cannot "digest" your site. Technical readiness is the prerequisite for generative visibility. The AI Search Site Audit focuses on "AI Crawlability," which differs significantly from traditional "Googlebot" crawlability.

This widget performs several mission-critical checks:

• llms.txt files: This is a new, emerging standard. Much like robots.txt instructs search bots, llms.txt provides clear, markdown-formatted instructions for LLMs on how to process your site’s most important information. The audit flags if this is missing.

• Content Length Optimization: LLMs have "context windows." If your content is too long, unstructured, or "fluffy," the model may fail to extract the key facts needed for a citation.

• "Last-Modified" Headers: AI models prioritize fresh information. If your server doesn't correctly communicate when a page was last updated, the LLM may discard your content in favor of a "fresher" (though perhaps less accurate) competitor.

• Robots.txt Bot Blocking: Many sites accidentally block specific user agents like GPTBot or Google-Extended. The audit flags these blockers immediately so you can remediate them and regain your visibility.

Strategist Note: If you are a B2B tech brand, check your robots.txt now. Many "security" plugins automatically block all AI bots by default, effectively nuking your AI visibility before you even start.

To transition from "tracking" to "dominating," follow this six-step optimization lifecycle:

1. Benchmark with Overview: Determine your baseline AI Visibility Score. Identify which specific LLMs are currently your strongest allies and where you have a "blind spot."

2. Identify Gaps via Competitor Research: Find the top 50 prompts where rivals win and you lose. Use a VLOOKUP or the export tool to compare these against your traditional keyword rankings to find "unprotected" territory.

3. Discover New Topics with Prompt Research: Identify the high-volume, high-intent questions your audience is asking. Look for "Trending" topics that traditional keyword research hasn't caught yet.

4. Analyze Perception with Brand Performance: Look at your "Share of Voice vs. Sentiment" chart. If your sentiment is neutral or negative, prioritize content that addresses those specific "Narrative Drivers."

5. Execute via Content and Social Toolkits: Create "AI-friendly" content, highly structured, fact-dense, and technically accessible. Use the Social toolkit to build the "brand signals" that LLMs use to verify authority.

6. Track Daily with Prompt Tracking: Set up your campaigns for ChatGPT and Google AI Mode. Monitor the impact of your optimizations and adjust in real-time when a model update shifts the landscape.

The efficacy of the AI Visibility Toolkit is best demonstrated through the results of leading practitioners who have integrated it into their core service offerings.

Sure Oak, led by SEO Director Andrea Schultz, has leaned heavily into AI Search Optimization (AEO). By focusing on Google AI Overviews and securing citations in major LLMs, they have achieved:

• +286% increase in Google AI Overview appearances.

• +41% month-over-month increase in referrals directly from ChatGPT.

• 40% of all new leads now originate from AI visibility channels.

Schultz emphasizes that being listed as a source on an LLM is a powerful trust signal that converts at a higher rate than traditional search traffic.

Jordan Brannon, President of Coalition Technologies, uses the AI Visibility Score as a core KPI for client reporting. By moving beyond traditional "rankings" and showing "LLM Presence," they have driven:

• +429% increase in AI referral traffic for their clients.

• +547% increase in conversions from LLM sources.

Brannon notes that the AI Visibility Score is the "missing piece" of the puzzle that allows his team to prove they are future-proofing their clients' brands.

The AI Visibility Toolkit is designed to be accessible as a standalone power-up or as part of a comprehensive marketing ecosystem.

For $99 per month, the standalone toolkit includes:

• 1 Folder for organization.

• 300 daily queries in AI Analysis reports (Overview, Competitor, etc.).

• 1,000 daily queries in Prompt Research.

• 25 prompts for daily Prompt Tracking.

• Brand Performance analysis for 1 domain.

• AI Search Checks for up to 100 pages in Site Audit.

• 10 CSV exports daily (up to 1,000 rows per export).

For agencies and growing teams, Semrush One bundles SEO and AI Visibility tools into tiers that offer significantly higher tracking limits:

• Starter: Includes tracking for up to 50 prompts.

• Pro+: Includes tracking for up to 100 prompts.

• Advanced: Includes tracking for up to 200 prompts.

In a corporate account environment, visibility and access are managed through User Management.

• Subuser Licenses: Additional licenses can be added for $99 per subuser, granting them their own access to reports and separate sets of Brand Performance analyses.

• Automatic Sharing: Within a corporate account, Brand Performance reports are automatically shared among all members who have a toolkit limit allocated to them. This ensures seamless collaboration between Brand Managers and SEO Specialists.

• Add-Ons: If you need to scale, you can purchase "Additional Domains for Brand Performance" for $99/month each, or "Additional Prompts" (50 prompts) for $60/month.

The toolkit provides global reach, covering the most critical markets for international brands.

Regional Coverage List

• AI Analysis (Overview, Competitor, Prompt Research): Supports 40+ countries (listed in Section 3) plus a "Worldwide" aggregate scale.

• Brand Performance: Offers a staggering 68,000+ options for location and language selection, covering countries, states, and even specific cities.

• Prompt Tracking: Supports 220+ countries and territories, ensuring coverage in virtually any market where AI search is active.

Data Update Frequency

• Daily (Rolling): Visibility Overview, Competitor Research, Prompt Research, and Prompt Tracking.

• Weekly: Brand Performance reports (to allow for the synthesis of larger datasets).

• On-Demand: AI Search Site Audit (runs whenever you trigger a new crawl).

Is there a free trial for the AI Visibility Toolkit?

The toolkit does not offer a standalone free trial. However, Semrush One often provides trial options that allow you to explore the unified platform, including AI features.

Where does the data come from?

The toolkit is powered by the largest US prompt database (261M+ prompts). It simulates real-world user behavior by running these queries through LLMs like ChatGPT and Google AI Mode and then uses proprietary AI to analyze the responses for mentions, citations, and sentiment.

How is the AI Visibility Score calculated?

It is a relative benchmark (0-100) reflecting your brand mentions in AI-generated answers compared to the median number of mentions for your top industry competitors, which are identified automatically by the tool.

Can I export my data for client reports?

Yes. You can export up to 1,000 rows per CSV export (10 per day). Furthermore, the toolkit integrates with My Reports, allowing you to drag-and-drop AI visibility metrics into professional PDF reports or schedule recurring email updates for stakeholders.

How do Brand Performance reports differ from standard monitoring? Standard monitoring just tells you that you were mentioned. Brand Performance uses LLMs to "read" the mentions and categorize the tone (Positive, Negative, Neutral) and the attributes associated with your brand, providing "AI Strategic Opportunities" (automated recommendations) based on that data.

The window to gain a significant competitive advantage in the AI search landscape is currently wide open, but it is narrowing as more brands realize that "AEO" is as critical as SEO. We are moving toward a future where the AI is the primary gatekeeper of information. If the AI doesn't know you, trust you, or recommend you, your brand's digital presence is effectively severed from the modern consumer journey.

By utilizing the AI Visibility Toolkit, you are taking control of your brand's narrative in an era of non-deterministic search. You are moving from a reactive "hope we get mentioned" posture to a proactive "we own this conversation" strategy. Don't leave your discovery to chance. Use the data, close the gaps, and become the brand the AI recommends.