LLM Visibility Tracking

🔄 Refresh Auto-Generated Queries in LLM Visibility

🔍 Overview When you create an LLM Visibility project, Search Atlas can automatically generate a set of topics and queries based on your website and target audience. Customers sometimes want to regenerate these auto-generated queries — for example, after refining their niche or expanding into new areas — without having to delete and recreate the entire project. This article explains how query management currently works and what your options are right now. ⚙️ How Auto-Generated Queries Work Today When a new LLM Visibility project is created, Search Atlas automatically generates a list of topics and queries based on your domain and settings. These auto-generated queries give you an immediate starting point for tracking your AI visibility across large language models. Currently, there is no built-in option to regenerate auto-generated topics for an existing project without recreating it. The ability to refresh or regenerate queries in place is a feature that has been requested and is not yet available. ✅ What You Can Do Right Now While a dedicated refresh feature is not yet available, the following general approaches may help you keep your queries relevant. Because the exact steps depend on your specific project setup, we recommend reaching out to our support team for guidance tailored to your situation: - Add or remove queries within your project: You may be able to manually add new topics or remove outdated ones inside your existing project, depending on the options available in your account. - Recreate the project: If your topics have changed significantly, you can delete the existing project and create a new one to trigger a fresh round of auto-generation based on your current domain and settings. Be aware that historical data from the original project will not carry over. Note: If you are unsure which option best fits your needs, or if you encounter any limitations while managing your queries, please contact our support team for assistance. 📋 When Escalating, Have the Following Ready If you need the support team to assist with your query refresh request, please have the following information available: - Your LLM Visibility project name - A description of what you would like updated (e.g., specific topics or queries to add, remove, or regenerate) - Any error messages or unexpected behavior you encountered, including the exact wording and when it occurred If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🚀 Purchase Additional LLM Visibility Slots

🔍 Why you reached the limit Each Search Atlas plan includes a set number of AI Visibility projects. If you see the message “You have reached the maximum of 4 LLM visibility projects for your plan”, all project slots included with your plan are currently in use. 🛒 How to purchase more slots 1. Sign in to Search Atlas. 2. Open AI Visibility from the left sidebar. 3. Choose the option to add or purchase additional project slots. 4. Review the available top-up in the purchase window and complete checkout. 5. Return to AI Visibility and create or activate your additional project. 💳 Pricing and credits The available LLM Visibility project top-up is currently listed at $29. It also includes a 250 AI Visibility credit bonus. Pricing, availability, and any applicable options are shown in the purchase window before you confirm payment. ⚙️ What happens after purchase Your added capacity is applied to your account after checkout. You can then use the additional slot to monitor another website or client project. Project slots and AI Visibility credits are separate: a slot allows another project, while credits support activity within AI Visibility. 📌 If you no longer need a slot To manage unused top-up capacity, open AI Visibility and review the available project management options. Reduction or downgrade options may depend on your account status and scheduled project deactivations. 💬 Need help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🤖 LLM Visibility Limits and Costs

📌 Quick answer Citation notifications have no additional cost. You can set them up for any site included in your plan’s LLM Visibility tracking slots. The maximum number of sites depends on your Search Atlas plan. Your plan-specific tracking slot limit determines how many sites you can monitor at once. Each tracked site uses one LLM Visibility tracking slot. 💳 Credit cost LLM Visibility citation notifications do not use additional daily credits per site. After a site is configured, notifications are included with the available tracking feature on your plan. 📊 Check your site limit 1. Open AI Visibility from the left sidebar. 2. Go to AI Visibility at /llm-visibility. 3. Review your current tracked sites and available tracking slots. 4. Add sites only while your plan has available slots. Your account’s displayed plan limit is the maximum number of sites you can have set up at the same time. Upgrading your plan may increase the number of available tracking slots. 🔔 Set up citation notifications 1. Open AI Visibility from the left sidebar. 2. Select or add the site you want to monitor. 3. Configure the citation notification settings for that site. 4. Save the settings to begin receiving notifications. ❓ Common questions Can I track unlimited sites? No. Tracking is limited by the number of LLM Visibility slots included in your plan. Do notifications cost credits every day? No. Citation notifications have no additional daily credit cost per site. What happens when I reach my limit? You must remove an existing tracked site or move to a plan with more tracking slots before adding another site. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🔍 Free Up LLM Visibility Project Quota Slots

🧩 Understanding the LLM Visibility Quota Your plan includes a set number of active LLM Visibility project slots. If you see a message indicating your quota is fully used — for example, showing more used slots than your plan allows — it usually means some projects are counted toward your quota even if they are not clearly visible to you in the dashboard. Important: You can find all your LLM Visibility projects on the AI Visibility projects page (open AI Visibility in the left sidebar). The steps below explain how to locate and deactivate those projects to free up your slots. ⚠️ Why Your Quota May Look Inflated A known issue caused some accounts to have the same domain tracked more than once (for example, once with no country code and once with a country code like "US"). This counted as two separate projects and inflated the quota. Engineering has resolved this, and quota counts should now reflect your actual active projects. If your numbers still look incorrect after following the steps below, contact support using the instructions at the bottom of this article. 🛠️ How to Free Up a Quota Slot To free up an LLM Visibility project slot, you need to deactivate your existing LLM Visibility projects rather than deleting unrelated projects (such as Site Explorer projects). Follow these steps: 1. Locate your LLM Visibility projects. Open AI Visibility in the left sidebar to view the AI Visibility projects page and find any active LLM Visibility projects that may be consuming quota slots. 2. Identify which projects you no longer need. Review the projects that are consuming your quota. Look for duplicates (same domain tracked more than once) or projects you no longer actively use. 3. Deactivate the LLM Visibility project. On the project you want to remove from your quota, use the available project options to deactivate it. Do not delete your Site Explorer or other unrelated projects — only deactivate the LLM Visibility project itself. 4. Confirm your quota updates. After deactivating a project, your available slot count should refresh. If it does not update immediately, wait a moment and reload the page. 5. Start your new audit. Once a slot is free, you can create a new LLM Visibility project and run your audit. 💡 Tips to Avoid Running Out of Slots - Periodically review your active LLM Visibility projects to catch any duplicates or inactive projects that may be consuming slots unnecessarily. - Deactivate projects you have finished analyzing to keep your quota available for new work. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🔍 Understanding LLM Visibility Data Gaps and Chart Artifacts

🧭 Overview If your LLM Visibility chart shows data before your project's first scan, a long flat line, or a sudden drop with no recovery, you are likely seeing a combination of two things: a UI display artifact and the natural consequence of when your first scan ran. This article explains both so you can interpret your data with confidence. 📅 Why There Is No Data Before a Certain Date LLM Visibility data is only generated when a scan runs. If your project was created weeks or months before its first scan was executed, there is simply no data for that earlier period — the platform has nothing to display because no scan occurred. In the example that prompted this article, a project was created in early March but was not scanned until May 5. As a result: - May 5 is the earliest real data point. - No LLM Visibility data exists for March or April, because no scans ran during that time. To find out when your project's first scan ran, review the scan history inside your project. Your earliest real data point is the date of that first completed scan. 📈 Why the Chart Shows Data Before the First Scan This is a known UI interpolation artifact. When the dashboard has only one data point — or a limited number of data points at the start of a project — it visually extends that earliest value backwards across the chart timeline. The flat line you see before your first scan date is not fabricated data and it is not a measurement of zero visibility. It is simply the chart repeating the earliest known value to fill the empty space on the left side of the graph. The same behavior can appear between scan dates: if scans were sparse, the chart carries the most recent known value forward visually until the next real scan result appears. In short: any portion of the chart that appears as a flat horizontal line before your first scan date, or between widely spaced scans, reflects this display behavior — not an actual measurement from that time period. 📉 Why the Data Dropped Sharply and Did Not Recover A sudden drop in your LLM Visibility chart — especially one that stays flat at a low value with no recovery — is most commonly explained by one of the following: - The drop marks the end of the interpolated region. When a new real scan runs after a long gap, the chart transitions from the repeated early value to the actual scan result. If real visibility is lower than the interpolated value, this appears as a sharp decline. - Scan frequency changed. If scans became less frequent or stopped temporarily, the chart may hold a low value flat until the next scan provides a new result. - A genuine change in LLM visibility. Real drops in how often AI-powered search tools surface your brand are also possible and would appear the same way on the chart. To distinguish a UI artifact from a real visibility change, check the dates of your actual scans. If the drop aligns with the first real scan after a long gap, it is likely the artifact transition point. If scans were running regularly before and after the drop, the change is likely real. ✅ How to Verify Your Real Data Points 1. Open your LLM Visibility project from Left sidebar → AI Visibility. 2. Review the scan history for your project to identify the dates on which real scans completed. 3. Cross-reference those dates with the chart. Data that falls on a real scan date is a genuine measurement. Data that appears as a flat line before or between scan dates is the UI interpolation artifact. 4. Focus your analysis on the period from your first real scan date onwards to ensure you are working with accurate information. 🛠️ What the Engineering Team Has Addressed The Search Atlas engineering team has already shipped a fix to improve how the Visibility Score chart handles projects with a single data point, reducing the visual impact of this interpolation artifact. Additional improvements to the LLM Visibility frontend are also complete. If you are still seeing unexpected chart behavior after reviewing the scan history steps above, the issue may require further investigation. 💬 Still Have Questions? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🔍 Claude Missing From AI Visibility Results

🧭 Overview If you have noticed that Claude (Anthropic's AI assistant) is not listed in your AI Visibility results, this is a known issue that our team is aware of. This article explains what to expect and what information to have ready if you need to escalate. ❓ Why Claude Is Not Showing in Results Claude is currently not appearing in AI Visibility results. This is a known issue that has been reported to our team. At this time, the root cause is under investigation, and no self-serve workaround is available to restore Claude data within the AI Visibility feature. - Your account data is not lost. All other LLM results remain intact. - No action is needed on your end while our team investigates. - This affects Claude specifically. Other LLMs tracked in AI Visibility should continue to display normally. 📊 Which LLMs Are Currently Tracked AI Visibility tracks brand mentions and responses across the major supported language models. Log in and navigate to the AI Visibility section of the platform to see the full list of LLMs actively monitored for your domain. The feature is continuously updated as new models become reliably trackable. 📋 What to Have Ready When Escalating Because Claude's absence from AI Visibility requires backend investigation, please have the following information ready when you contact support: - Your project name and the domain you are tracking. - The date and approximate time you first noticed Claude missing from results. - A screenshot of your AI Visibility dashboard showing the missing data. - Confirmation of whether other LLMs are displaying correctly or are also affected. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📤 How to Export LLM Visibility Data as CSV

This article explains how to locate and use the CSV export feature for your LLM Visibility data. If you've been looking for a download or export button and couldn't find it, follow the steps below to export your data directly from the platform. 🛠️ How to Export LLM Visibility Data as CSV 1. Log in to your Search Atlas account and navigate to the AI Visibility section from the left-hand sidebar (Left sidebar → AI Visibility). 2. Open the specific LLM Visibility report you want to export (for example, your brand mentions or visibility score breakdown). 3. Once the data table has loaded, look for the Download .CSV button (Reports → Report Builder) or the Export button on other pages — this is typically located in the upper-right area of the report panel, near the date range selector or filter controls. 4. Click the Download .CSV button (in Reports → Report Builder) or the Export button on other pages. Your browser will download a .csv file that you can open in Excel, Google Sheets, or any spreadsheet application. 🔍 Troubleshooting If you do not see an export button, try the following: - Make sure you have fully loaded the report by selecting a date range and waiting for the data table to populate — the export button may only appear once data is present. - Check that your account plan includes LLM Visibility data exports. Export availability may depend on your subscription tier. - Try refreshing the page or clearing your browser cache, as the button can occasionally fail to render on first load. - If the LLM Visibility section itself is not visible in your sidebar, confirm with your account owner that the feature is enabled for your workspace. ✅ What to Expect Once exported, your LLM Visibility data will be available as a .csv file containing the visibility metrics and data points shown in the report. You can open and analyze this file in Excel, Google Sheets, or any compatible spreadsheet tool. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🚀 Introducing LLM Visibility

As AI-powered assistants like ChatGPT, Gemini, Claude, and Perplexity reshape how customers discover and research brands, companies need clear visibility into how they are represented in this new channel. LLM Visibility gives you a dedicated dashboard to track brand mentions, visibility trends, sentiment, and competitor benchmarks across major large language models — all in one place. 🌟 Why It Matters Traditional SEO and social listening tools weren't built to measure how generative AI represents your brand. LLM Visibility fills that gap with AI-native metrics — visibility share inside model answers, sentiment of AI-generated descriptions, and the citation sources LLMs rely on — so you can manage reputation, track competitors, and optimize your presence in a channel that conventional analytics can't see. 🧩 Key Features 📊 Multi-Domain Monitoring Easily track visibility for multiple brands or domains at once—perfect for agencies managing multiple clients or enterprises with large brand portfolios. 📈 Advanced LLM Analytics & Reporting Dive deep into AI-specific insights, sentiment analysis, and trend tracking. Sentiment is reported as a 0–100 average score (not a percentage of positive mentions), so charts labeled as sentiment history reflect the average score over time. Generate professional reports tailored for brand managers or client presentations. 🆚 Competitive Benchmarking Compare your brand's AI visibility against competitors or industry benchmarks across multiple LLMs. ⚡ Optimization Recommendations Go beyond monitoring with actionable guidance on how to improve your brand's visibility and reputation across AI models. Examples of the kinds of recommendations you may see include: suggested content topics to publish based on gaps in LLM coverage, identification of citation gaps where competitors are cited but your brand isn't, and structured data or on-page improvements that help LLMs surface your brand more accurately. 🎯 Who is it for? - Agencies managing multiple client brands - Enterprises with multiple product lines or domains - Enterprises with large brand portfolios - Marketing consultants focused on AI-driven visibility - Brand managers tracking AI-channel reputation - SEOs and marketers monitoring competitor visibility in LLMs - Companies who want LLM monitoring without investing in the full SEO suite 🏆 Why LLM Visibility is Different 1. Built for AI, not social media – Unlike traditional monitoring tools, this focuses on AI-generated responses. 2. Multi-domain ready – Manage many brands from a single dashboard. 3. Deeper insights – Beyond basic mention tracking, with AI-native analytics. 4. Agency-friendly – White-label reporting and portfolio management built in. 📌 Use Cases - Client reporting – Add LLM visibility sections to your agency reports. - Brand management – Track multiple domains across one dashboard. - Competitive intelligence – Understand your standing vs. competitors. - Crisis monitoring – Get alerts for negative AI mentions. - AI optimization – Focus on LLM visibility without the SEO overhead. 🔑 Getting Started When you log in to Search Atlas, go to the left sidebar and click on AI Visibility. From there, select the project or domain you want to analyze to open your dashboard. 📦 Quota & Plan Limits LLM Visibility uses two separate limits that customers often confuse: - LLM tracking quota – the number of projects/queries you can run. This can be increased through OTTO top-ups. - LLM site count – the number of distinct sites/brands you can track. This is determined by your plan tier and is not increased by OTTO top-ups. If you need to track more sites than your plan allows, you'll need to upgrade your plan tier — adding quota alone won't unlock additional site slots. 📊 Summary Dashboard The Summary tab provides a snapshot of your brand's overall performance across LLMs: - Overall Visibility % – How often your brand appears in LLM responses. - Overall Sentiment Score – A 0–100 average score reflecting how positively, neutrally, or negatively your brand is described (not a percentage of positive mentions). - Citations Found – Total brand mentions across platforms. - Visibility vs Competitors – Benchmarking your brand against others. 👁️ Visibility Tab The Visibility tab shows how often your brand is mentioned across different platforms. You can view: - Visibility Trends over time. - Competitor Comparisons with a toggle for side-by-side insights. - Share of Voice – A breakdown of your brand's percentage vs competitors. - Visibility Score Rank – Where your brand ranks compared to others in the market. You'll also find a detailed Citations Sources table to see where AI models are pulling brand mentions from. 💬 Sentiment (Left sidebar → AI Visibility → Sentiment) The Sentiment page (Left sidebar → AI Visibility → Sentiment) analyzes how AI models describe your brand when directly asked about it. Sentiment values shown in this tab are 0–100 average scores, not percentages of positive mentions — a higher score means AI responses describe your brand more favorably on average. It includes: - Positive vs Negative sentiment history over time (displayed as a 0–100 average score). - Sentiment by Platform – Compare how ChatGPT, Gemini, Claude, and Perplexity describe your brand. - Key Topics Driving Sentiment – Identify which themes (e.g., product quality, pricing, customer service) are influencing AI responses. 🔎 Topics & Queries (Left sidebar → AI Visibility → Topics & Queries) The Topics & Queries page (Left sidebar → AI Visibility → Topics & Queries) shows the specific areas where your brand is being mentioned and how those mentions perform. You'll see: - Top Performing Topics with visibility score, rank, citation share, and search volume. - The ability to expand topics and view related queries. An Analyze option to dive deeper into a single topic. ❓ Troubleshooting & FAQ "Competitor management is only available for user-tracked projects" This error means the project you're viewing is not being recognized as an actively user-tracked project, so competitor management is disabled for it. It can sometimes appear due to orphaned quota or routing issues even on brands you believe you are tracking. To resolve it: - Verify you are viewing the correct project URL, including the country_code parameter for the brand you intend to manage. - Confirm the brand is set up as a tracked project in your account. - If the error persists on a brand you know is tracked, contact Search Atlas support so we can investigate. "No available quota for LLM Visibility Analysis" on a brand I'm already tracking In some cases this message can render incorrectly on pages for brands you are actively tracking due to country_code routing. If you see this error on a brand you've already set up: - Try navigating directly to the brand URL with the correct country_code parameter. - If the issue continues, contact support — this may be a known routing edge case that has since been patched. ⚡ Next Steps Start exploring LLM Visibility in your dashboard today and unlock new insights into how AI models are shaping your brand's digital presence. Mastering visibility in AI-driven environments is no longer optional—it's essential. With LLM Visibility, you gain a dedicated lens into how your brand is represented across ChatGPT, Claude, Gemini, and other LLMs. By combining multi-domain monitoring, competitor benchmarking, sentiment analysis, and actionable recommendations, this standalone tool empowers agencies and enterprises to stay competitive and proactive. It's not just about tracking mentions—it's about shaping your brand's future in the AI-first era.

🗑️ How to View, Manage, and Delete LLM Visibility Projects in Search Atlas

What Is LLM Visibility? LLM Visibility is a Search Atlas tool that tracks how your brand is mentioned and represented in answers generated by large language models (LLMs) such as ChatGPT, Gemini, Perplexity, Claude, and Microsoft Copilot. Each LLM Visibility project monitors one brand or domain and runs periodic scans to measure mention frequency, sentiment, and share of voice across AI platforms. Navigation path: Left sidebar → AI Visibility OTTO vs. LLM Visibility — What Is the Difference? OTTO and LLM Visibility are two completely independent tools inside Search Atlas. Both use the word project — but they serve different purposes, live in different sections of the platform, and draw from separate quotas. ⚠️ OTTO and LLM Visibility are separate functions. Deleting an OTTO project does NOT affect your LLM Visibility quota — and deleting an LLM Visibility project does NOT affect your OTTO site quota. OTTO SEO — At a Glance - What it does: Automates on-page SEO — deploys metadata, schema, internal links, and content blocks directly to your live website. - Where it lives: Left Sidebar → OTTO SEO → All Sites (SEO Automation) - What a project means: One connected website (domain) with an installed OTTO Pixel or Plugin. - Counts toward OTTO quota? Yes — uses OTTO site slots. - Counts toward LLM Visibility quota? No. LLM Visibility — At a Glance - What it does: Tracks how often and how positively your brand appears in AI-generated answers from ChatGPT, Gemini, Perplexity, Claude, and Microsoft Copilot. - Where it lives: Left Sidebar → AI Visibility - What a project means: One brand or domain being monitored for AI mentions and sentiment trends. - Counts toward OTTO quota? No. - Counts toward LLM Visibility quota? Yes — each project occupies one LLM Visibility slot. Understanding the LLM Visibility Project Limit Each Search Atlas plan includes a fixed number of LLM Visibility project slots. Check your plan page for your specific limit. When you reach this limit, the platform prevents you from creating new projects until you free a slot, purchase additional slots, or upgrade your plan. To resolve a full quota you have three options: - Delete an existing LLM Visibility project to free a slot immediately (see steps below). - Purchase additional LLM Visibility project slots as a quota top-up through the platform's top-up checkout, without upgrading your plan. - Upgrade your plan to increase your project limit (see the Upgrade section below). Where to View Your Existing LLM Visibility Projects 1. Log in to your Search Atlas account. 2. In the left sidebar, click AI Visibility. 3. The LLM Visibility dashboard opens. All existing projects are listed here with their name, domain, and current scan status. 4. Your quota usage — for example, 2 of 2 projects used — is displayed at the top of the dashboard or within the project list header. If LLM Visibility does not appear in your left sidebar, verify that your current plan includes this feature. Contact Search Atlas Support via the in-app Help Widget if you believe it should be accessible. How to Delete an LLM Visibility Project ⚠️ Warning: Deletion is permanent. All scan history, mention data, sentiment scores, and visibility trends for the deleted project are removed immediately and cannot be recovered. Confirm you no longer need the project before proceeding. 1. Navigate to Left sidebar → AI Visibility. 2. Find the project you want to remove in the project list. 3. Click the three-dot menu (⋮) next to the project name. 4. Select Delete from the dropdown menu. 5. Confirm the deletion in the dialog that appears. 6. The slot is typically released within a few minutes; refresh the page if the counter has not updated after 5 minutes. If the slot remains locked after refreshing, contact Search Atlas Support for a manual reset. How to Create a New LLM Visibility Project After Freeing a Slot 1. After deleting a project (or after upgrading to add more slots), navigate to Left sidebar → AI Visibility. 2. Click Add Domain. 3. Enter your brand name and domain URL. 4. Select the topics, keywords, and LLM platforms you want to track (ChatGPT, Gemini, Perplexity, Claude, Microsoft Copilot, and others available in your plan). 5. Click Save or Create Project. 6. The first scan runs on the next scheduled cycle. Initial trend data typically requires 2–3 weeks of collection before statistics and charts become visible in the dashboard. How to Upgrade for More LLM Visibility Projects If you need more project slots than your current plan includes, upgrade your subscription from the billing dashboard. 1. Click your Avatar Menu (👤) (avatar) in the top-right corner of the Search Atlas dashboard to open the Avatar Menu (👤). 2. Select Billing → Plans & Top-ups. 3. Review the available plan tiers and their included LLM Visibility project limits. 4. Click Change Plan or Manage Subscription on the plan that meets your needs. 5. Your new quota takes effect immediately after the upgrade is processed. For enterprise accounts or custom quota increases beyond standard plan limits, contact Search Atlas Support directly via the in-app Help Widget.

📊 Why the Citations Section in Brand Insights Shows Unrelated Domains

The Citations section in Brand Insights shows the websites that AI engines referenced when answering questions about your industry topics — which is why it includes competitors and third-party sources alongside your own domain. This is expected behavior, not an attribution error. 🔍 What the Citations Section in Brand Insights Shows The Citations section lists the websites that AI engines — such as ChatGPT, Gemini, and Perplexity — referenced when answering questions about topics in your industry. AI engines pull from many sources to build an answer, so the list reflects the full set of domains they cited across your topic area. Your own domain appears here too. For eastbayobgyn.com, your domain is the most cited domain in the report and appears in 39 AI responses. In most cases, your top-ranked domain confirms data accuracy. If citation counts seem unusually high or inconsistent, this may reflect a data refresh lag — refresh the page or contact support. 🌐 Why Competitor and Third-Party Domains Appear in Citations The other domains in the list are competitors and third-party sources that AI engines also referenced when answering questions in your topic area. Their presence does not mean those sites mention your business — it means AI engines drew on them to answer questions related to your industry. The Citations list reflects the competitive landscape, not an error Think of the Citations list as the competitive landscape as AI engines see it. When an AI engine answers a question in your field, it weighs many authoritative and competing sources. Brand Insights surfaces those sources so you can see who you share space with in AI-generated answers. This helps you understand which sources AI engines trust in your industry and identify gaps where your content could build stronger authority. - Your domain — how often AI engines cite your site for your topics. - Competitor domains — other businesses AI engines reference for the same topics. - Third-party sources — directories, publications, and reference sites AI engines trust in your field. ⚙️ How the Citations Section Gets Populated You do not need to add or configure anything. The Citations section auto-populated when you viewed Site Metrics — no manual setup required. As AI engines reference new sources for your topics, the list reflects what they cite. ✅ How to Read Your Brand Insights Citations Data Use the Citations section to gauge your visibility in AI answers relative to others in your space. 1. In the left sidebar, go to Local → Local Citations. 2. Find your domain near the top and note its response count — for eastbayobgyn.com this is 39 AI responses. 3. Review the competitor and third-party domains below it to see which sources AI engines favor for your topics. 4. Use the ranking to spot where you lead and where competing sources are cited more often. When your domain sits at the top with the highest response count, you are reading the data correctly — that signals strong AI citation presence for your industry topics. ❓ Frequently Asked Questions About Citations Why does Total Cited Sources stay the same when I click different recommendations? This can occur with large datasets. Refresh your browser to sync the display. 🎯 You now know that the Citations section in Brand Insights intentionally shows competitor and third-party domains because they reflect every source AI engines cite for your industry — with your own domain ranked by how often it is referenced. Understanding which third-party sources AI engines cite helps you benchmark your content strategy and identify high-authority domains to reference in your own content. Review your Site Metrics regularly to track how your AI citation presence changes over time.

🔍 New LLM Platforms Showing No Visibility Data Yet

🤔 Why Is There No Data for Grok or Copilot? If you recently upgraded your plan to access AI Visibility (formerly LLM Visibility) data for platforms like Grok or Microsoft Copilot, it is expected that those platforms may show no results yet — this is not a bug. Upgrading your plan unlocks access to newly supported LLM platforms, but it does not generate historical data retroactively. Search Atlas begins collecting visibility data for a platform from the point it becomes active in our system. Because these platforms were added recently, the data collection window is short and results are still accumulating. ⏳ When Will Data Start Appearing? Data for newly added LLM platforms typically begins populating within a few business days of a platform going live. Results will grow over time as Search Atlas continues querying those platforms on your behalf. Refreshing the page or re-saving your project will not speed up this process — data is collected on a scheduled background cycle. - Plan upgrade — unlocks platform access immediately. - Data collection — begins automatically once the platform is live in our system. - Visible results — typically appear within a few business days and grow incrementally from there. 🔎 How to Check Your AI Visibility Data Once data starts populating, you can view it by navigating to Left sidebar → Authority → QUEST AI Visibility (formerly LLM Visibility). From this screen you will see all supported LLM platforms and their visibility metrics for your tracked keywords. 1. Go to Left sidebar → Authority → QUEST AI Visibility (formerly LLM Visibility). 2. Review the list of LLM platforms displayed on the screen. 3. Select a platform such as Grok or Copilot to view its data. 4. If the platform appears in the list but shows no results, data collection is still in its early phase — check back in a few business days. ✅ Confirming Your Plan Includes These Platforms Not all Search Atlas plans include every LLM platform. Before troubleshooting further, verify that your subscription covers the specific platforms you want to track. - If a platform is visible at Left sidebar → Authority → QUEST AI Visibility (formerly LLM Visibility) but shows no data yet, your plan includes it and collection has already started. - If a platform is not listed at all, it may not be included in your current plan. Consider upgrading or contact support via the chat widget to confirm what is covered. 💡 Tips While You Wait - Check back every few business days — results grow incrementally as collection cycles complete. - Use LLM platforms that already have data to benchmark your current performance while newer platforms populate. - Avoid repeatedly re-adding your project or toggling settings, as this will not accelerate data collection. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🌍 How LLM Visibility Geolocation Simulation Works

Overview The geolocation setting in LLM Visibility does not simply filter a regional dataset. It actively injects geolocation signals into live AI platform requests so that responses reflect what a real user in the selected country would receive. This article explains the general mechanics of how that works and what to expect across different AI platforms. How Geolocation Injection Works When you select a country in LLM Visibility, the platform routes the query through a scraper provider that manipulates the outbound IP address to match the selected country. This means the AI platform receives the request as if it originated from a real user in that country, producing geographically relevant responses. - Geolocation injection works at the network level — the AI platform sees a country-appropriate IP and responds accordingly. - This is true geolocation injection, not post-collection filtering. The responses you see reflect what a real user in that country would receive from the AI. Supported Granularity Geolocation injection currently operates at the country level. The specific granularity available and any workarounds for more targeted simulation (such as city-level queries) may vary depending on your plan and platform. If you need finer geographic targeting than what the country selector provides, contact our support team for guidance on your specific use case. Platform-Specific Behavior Geolocation injection may not behave identically across all AI platforms available in LLM Visibility. Different platforms handle country-level signals in their own ways, which can affect how consistently geolocation is reflected in the responses you receive. If you notice unexpected behavior on a specific platform, note the platform name, the country selected, and the query used so our team can investigate. Need Help? If you experience results that do not match your expected geography, or if you have questions about how geolocation simulation applies to your specific use case, our support team can help. When reaching out, please have ready: the platform you were using, the country you selected, the query text, and any example responses that appeared incorrect. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🌍 LLM Visibility Geolocation and City Targeting Explained

🗺️ Overview The AI Visibility tool (left sidebar → AI Visibility) lets you monitor how large language models (LLMs) cite your brand and competitors across different locations. This article explains exactly how the country picker works, whether city-level targeting is available, and how location behavior differs across ChatGPT, Gemini, and Google AI Mode. 🌐 How the Country Picker Works The country selector in AI Visibility does two things simultaneously: - Filters the data you see in your dashboard to show only results collected for that country. - Injects a simulated geolocation context into the queries sent to supported LLMs, so the model responds as if the user is located in that country. This means your results reflect both localized data storage and geographically influenced model responses — not just a filtered view of a single global dataset. 🏙️ City-Level Targeting City-level targeting is available for select queries in AI Visibility. Search Atlas has been actively expanding city-level coverage, and new cities are being added on an ongoing basis. If you do not see your target city listed, it may not yet be supported — but the city list continues to grow. To check available cities, open QUEST AI Visibility, select your country, and look for the city dropdown beneath the country selector. If a city option is not present for your region, country-level targeting will apply by default. Note: A known issue is being investigated where the country/location selection can reset from a non-US country back to the US when navigating from Site Explorer into AI Visibility. If you notice your location has changed unexpectedly, simply reselect your preferred country and city before running a query. 🤖 How Location Behavior Differs by LLM Each LLM handles geolocation context differently. Here is a breakdown of how each model responds to location signals set in AI Visibility: - ChatGPT (OpenAI): Geolocation is simulated by including location context in the query prompt. ChatGPT does not have native real-time location access via the API, so Search Atlas injects country and city context directly into the request. Responses reflect the instructed location rather than a true IP-based location. - Gemini (Google): Gemini accepts geolocation parameters that influence local relevance in its responses. Search Atlas passes the selected country (and city where available) as part of the request, and Gemini factors this into rankings and citations. - Google AI Mode (AI Overviews / AI Mode in Search): Google AI Mode is the most location-sensitive of the three. It uses both the simulated location context and Google's own localization signals. Because of this, results in Google AI Mode may be harder to replicate manually in a browser unless your browser location, language, and search settings exactly match the simulation parameters. An active investigation is underway for cases where AI Visibility reports a website citation that cannot be replicated directly in Google AI Mode. 🗣️ Does Query Language Affect Which Model Version Responds? Yes — query language can influence model behavior in the following ways: - ChatGPT: Queries written in a non-English language may route to language-optimized model configurations. The underlying model version remains the same, but response style, phrasing, and local knowledge depth can vary by language. - Gemini: Gemini is multilingual and adjusts its response quality and sourcing based on the query language. Queries in languages with less training data may return different citation patterns than English queries for the same topic. - Google AI Mode: Language strongly influences which localized index Google draws from. A query in French, for example, will pull from French-language web content even if the country is set to a predominantly English-speaking country. For the most accurate local simulation, align your query language with the language spoken in your target location. Best practice: Write your tracked queries in the language your target audience actually uses when searching, and pair them with the matching country and city setting for the most realistic visibility data. 📍 Coming Soon: Per-Location Local AI Visibility Tracking Search Atlas is developing a dedicated per-location local AI Visibility tracking feature for Google Business Profile (GBP) locations. This will allow businesses with multiple physical locations to track AI-generated mentions and citations at a granular, location-specific level. This feature is currently in the planning stage and is not yet available. ✅ Quick Reference Summary - The country picker both filters data and simulates geolocation in LLM requests. - City-level targeting is available for select cities and expanding over time. - If your location resets to the US unexpectedly, reselect it manually — a fix is in progress. - ChatGPT uses prompt-injected location; Gemini and Google AI Mode use native location parameters. - Query language affects citation sources and model response quality across all three LLMs. - Per-location GBP tracking is on the roadmap but not yet released. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📊 LLM Visibility Metrics: Rank, Score, Citations, Share of Voice

🔍 Overview When reviewing the AI Visibility tool (Left sidebar → AI Visibility), you may notice that a competitor shows a high Rank or Visibility Score while displaying zero Citations. This is not a data error. These metrics measure different things, and a competitor can legitimately score well on one while showing nothing on another. This article explains what each metric measures, how they relate to each other, and how to interpret competitor data correctly. 📐 What Each Metric Measures There are four core metrics in the AI Visibility tool. Understanding what each one tracks is the key to reading competitor comparisons accurately. - Rank — The average position at which a brand or domain appears across all tracked AI-generated responses for your monitored prompts. A lower number means the brand appears earlier and more prominently in AI answers. - Visibility Score — A composite score that reflects how often and how prominently a brand appears in AI responses. It accounts for both mention frequency and position within responses. A high score means the brand is consistently present and well-placed in AI-generated content. - Citations — The number of times an AI model (such as ChatGPT, Gemini, or Perplexity) explicitly linked to or referenced a specific URL as a source. Citations are a subset of brand mentions — a brand can be named in a response without its URL being cited as a source. - Share of Voice — The percentage of all tracked AI responses in which your brand (or a competitor) receives any mention, compared to the total mention pool across all tracked brands. It reflects relative dominance across the prompt set. ⚠️ Why Competitors Can Rank High With Zero Citations This is the most common source of confusion. Here is exactly why it happens: Citations and Rank are independent signals. Rank and Visibility Score are calculated from brand or entity mentions inside AI responses — meaning the AI named the brand in its answer. Citations, by contrast, only appear when the AI model also provided a source URL alongside that mention. Many AI models frequently mention brands, products, or companies by name without attaching a source link. This is especially common in conversational or recommendation-style responses. The brand is still ranked and scored for that mention — but no citation URL is recorded because none was provided by the AI. As a result, a competitor like Quantive.com can have: - A strong Rank because it is consistently named early in AI responses to your tracked prompts. - A high Visibility Score because it appears frequently and in prominent positions. - Zero Citations because the AI responses that mentioned Quantive.com did not include a linked source URL to their domain. This does not mean the competitor is invisible or irrelevant. It means AI models are referencing them as a known entity without sourcing a specific page. 🔗 How the Metrics Relate to Each Other Think of these metrics as a funnel, from broadest to most specific: 1. Share of Voice — How often is the brand mentioned at all across every tracked prompt? 2. Visibility Score — How prominently and consistently does the brand appear when it is mentioned? 3. Rank — Where in the response does the brand typically appear when mentioned? 4. Citations — Of all those mentions, how many included a direct source URL to the domain? A competitor can perform strongly at steps 1–3 while scoring zero at step 4. The absence of citations does not cancel out strong Rank or Visibility Score results — they are simply measuring a different dimension of AI presence. 📊 Practical Example Suppose you are tracking 50 prompts related to OKR software. Across those prompts: - Quantive.com is mentioned by name in 38 out of 50 responses, usually in the first or second sentence — giving it a strong Rank and high Visibility Score. - None of those 38 responses included a hyperlinked source URL pointing to Quantive.com — so Citations = 0. - Your domain is mentioned in 20 responses, often mid-paragraph, with 5 of those including a source URL — so your Citations = 5, but your Rank and Visibility Score are lower. In this scenario, Quantive.com has stronger AI brand presence (Rank, Visibility Score, Share of Voice), while your domain has more verified source links (Citations). Both represent real competitive intelligence — they just answer different questions. ✅ How to Use This Information - Use Rank and Visibility Score to assess overall AI brand presence for any competitor, regardless of their citation count. - Use Citations to understand which domains are being sourced as authoritative references — this is where content and link strategies have the most impact. - Use Share of Voice to benchmark your relative presence against all tracked competitors in aggregate. - If a competitor has high Rank but zero Citations, prioritise analysing the prompts where they appear and consider what content or entity signals make AI models mention them confidently without needing a source. 💬 Need Help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

LLM Visibility Quota Showing Fully Used Incorrectly

Overview Some accounts have encountered a bug where the LLM Visibility quota appears fully used even when no active projects exist. This false quota-exhausted state prevents users from adding new sites for tracking. The root cause is a system-level issue — not actual usage on the account. Search Atlas engineering is aware of this issue and has worked to resolve it. If you are still experiencing this problem, follow the steps below to confirm the symptoms and get it resolved. Symptoms of This Bug - Your LLM Visibility quota appears at or near 100% used. - You have no active LLM Visibility projects, or far fewer than the quota limit suggests. - You are blocked from adding new sites for tracking. - The quota usage does not decrease even after removing projects. Steps to Self-Resolve or Report the Issue 1. Navigate to the LLM Visibility section of your account and confirm whether your quota still appears fully used despite having no active projects. 2. If the quota appears incorrectly exhausted, try refreshing your browser and logging out then back in to rule out a display caching issue. 3. Check whether any recently removed projects are still reflected in your quota count. If so, wait a few minutes and refresh again, as counts can take a short time to update. 4. If the quota still shows as fully used after these steps and you are certain you have no active projects consuming it, this indicates a system-level issue that requires a manual review on your account. 5. Contact our support team via the live chat widget in the bottom-right corner of the platform — type human teammate to be connected with a member of our team. Include the following details so the team can escalate your case quickly: your account email address, the domain(s) you are trying to add, a description of what your quota display shows versus how many active projects you have, and a screenshot of the quota display if possible. What to Expect After You Contact Support When this issue is escalated, the engineering team will investigate your specific account, correct the quota data manually if needed, and confirm once your quota accurately reflects your actual usage. You will be notified when the fix has been applied so you can resume adding sites. If you have questions or are not sure whether your symptoms match this bug, reach out to our support team via the live chat widget in the bottom-right corner of the platform — type human teammate to be connected with a member of our team, and we will help you confirm and resolve the issue.

🐛 LLM Visibility Quota Shows Exhausted Incorrectly

Overview Some users see a "Quota Exhausted" error in LLM Visibility even though they have not filled all their allocated project slots. For example, you may have 3 active projects out of 4 allowed, yet the platform reports your quota as fully consumed. This is a known bug that affects certain accounts. The issue requires a fix applied directly to your account by our support team. What Causes This A backend bug can cause your LLM Visibility quota display to fall out of sync with your actual project usage. As a result, your quota may appear fully consumed even when you are within your plan's limits. How to Resolve It 1. Confirm the mismatch. Count how many LLM Visibility projects you have actively running and compare that number to the quota limit on your plan. If your active project count is lower than your plan limit but your quota still shows as exhausted, you are likely affected by this bug. 2. Check for duplicate or stuck projects. Review your project list for any entries that appear duplicated, are stuck in a pending or activating state, or were created more than once due to a failed setup attempt. Note the names and statuses of any suspicious projects, as this information will help the support team identify the root cause faster. 3. Do not delete active projects as a workaround. Removing legitimate projects is not necessary and may cause you to lose tracking history. 4. Contact support to request a quota reset. Because this issue requires a backend fix applied directly to your account, reach out to our support team and describe the mismatch you are seeing — your active project count versus the quota limit on your plan. Include any duplicate or stuck project names you identified in the previous step. The support team will escalate to engineering to correct your quota balance. 5. Confirm the fix is applied. After the support team processes your request, verify that you can now create or access projects up to your plan limit and that any quota exhaustion error is no longer displayed. If the error persists after the team confirms the fix, reply in the same support thread so the team can investigate further. What Happens After the Fix Once the support team applies the fix to your account, your quota balance will update to reflect your real usage. You will regain access to your remaining slots and any incorrect exhaustion errors will disappear. Tips to Avoid Confusion in the Future - If you see a quota exhaustion message unexpectedly, always compare the number of projects you can see in your project list against your plan's limit before taking any action. - Avoid creating the same project multiple times if a setup step appears to fail — this can contribute to quota tracking issues. Wait for confirmation before retrying. - If a project appears stuck during activation or returns an unexpected error, contact support before attempting to recreate it. Need Further Help? If your quota still shows as exhausted after reviewing the steps above, contact our support team directly via the live chat widget in the bottom-right corner of the platform — type human teammate to be connected with a member of our team.

⚡ LLM Visibility Query Quota: Auto-Generated vs. Deployed

Overview LLM Visibility tracks two distinct types of queries: auto-generated queries and deployed queries. Understanding the difference is essential to managing your monthly query quota and troubleshooting issues related to Atlas Brain deployment. If a deployment attempt fails or consumes more quota than expected, this article explains what to check and how to escalate. What Are Auto-Generated Queries? Auto-generated queries are created automatically by the platform when you set up a project or topic in LLM Visibility. The system produces a set of relevant questions and prompts representing how real users might ask about your brand, product, or topic across large language models. - Auto-generated queries are created in the background without manual input. - They appear in your query list inside AI Visibility → Topics & Queries. - Having auto-generated queries does not mean they have been deployed or tested against LLMs yet. What Are Deployed Queries? Deployed queries are queries that have been actively sent to one or more LLMs for processing. Deployment is the action that triggers live data collection — it is when a query moves from a waiting state to an active, results-producing state. - Deployment can be initiated manually or automatically by the platform. - A query can only be deployed if your remaining quota can accommodate it. How to Check Your Current Quota Usage To understand how your quota is being consumed, navigate to your LLM Visibility project and review the query list. You can distinguish between query types by checking the status column or labels associated with each query — auto-generated queries will typically show a pending or draft status until they are deployed. Review the total count of auto-generated queries versus those marked as deployed or active to get a sense of how your quota is being allocated. If your account dashboard shows a quota or usage indicator, compare your current consumption against your monthly limit to determine how much headroom remains before initiating a large deployment. Steps to Take If Your Deployment Is Blocked If an Atlas Brain deployment appears blocked or does not complete as expected, try the following steps before escalating: 1. Review your current query list in LLM Visibility and count how many queries are in a deployed or active state versus auto-generated or pending. 2. Check whether your total active query count is approaching or at your plan's monthly limit, as this is the most common reason a deployment does not proceed. 3. If you have queries in an auto-generated state that you do not need, remove or archive them to free up quota before reattempting deployment. 4. Retry the deployment after making any adjustments and monitor whether it proceeds to an active state. If the deployment remains blocked after these steps, our support team will need to review your account directly. Please have the following ready when you reach out: - Your project name and the topic(s) affected - The exact error message you received (if any) - The approximate date and time the deployment was attempted - The number of queries you were attempting to deploy If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🤖 Understanding LLM Visibility Subtopics and Actions

🔍 What Is LLM Visibility in Search Atlas? LLM Visibility tracks how your brand, products, and topics appear inside AI-generated responses from large language models (LLMs) like ChatGPT, Gemini, and others. To access this section, go to Left sidebar → AI Visibility (URL: /llm-visibility). Within this dashboard, you will see a breakdown of subtopics — specific themes and subjects that LLMs associate with your brand or domain when generating answers. Understanding these subtopics helps you identify where your brand is already being surfaced by AI and where opportunities exist to improve visibility. 📂 What Are LLM Visibility Subtopics? Subtopics are the specific subject areas or themes that appear within LLM-generated responses when your brand or a related query is mentioned. They are automatically identified and grouped by the platform based on patterns found across multiple AI responses. - They are not submitted by your customers. Subtopics are extracted directly from the content of LLM-generated answers — they reflect how AI models currently describe, categorise, or discuss your brand and related subjects. - They reveal your AI footprint. Each subtopic shows a distinct angle through which LLMs are referencing your brand, such as product features, use cases, industry categories, or competitor comparisons. - They are dynamically updated. As LLM responses evolve over time, the subtopics in your dashboard are refreshed to reflect the latest AI-generated content patterns. 📊 How to Interpret Your Subtopics When reviewing your subtopics, pay attention to the following signals: 1. Frequency: How often a subtopic appears across LLM responses indicates how strongly that theme is associated with your brand by AI models. 2. Sentiment: Whether the LLM mentions your brand positively, neutrally, or negatively within a given subtopic context. 3. Coverage gaps: Subtopics where your brand is mentioned infrequently — or not at all — highlight content areas you may want to strengthen. 4. Competitive presence: Some subtopics may reveal that competitors are more prominently featured than your brand, signalling areas to prioritise. 🚀 What Actions Can You Take With LLM Responses and Subtopics? The insights from LLM Visibility subtopics are most valuable when translated into concrete content and authority-building actions. Here is what you can do: - Create targeted content: If a subtopic shows low brand presence, publish authoritative content (blog posts, landing pages, guides) that directly addresses that theme. This increases the likelihood that LLMs will pull from your content when generating answers. - Strengthen topical authority: Use Left sidebar → Authority → QUEST LLM Visibility to build structured authority signals around the subtopics where you want greater AI recognition. - Build supporting assets: Use Left sidebar → Authority → Cloud Stacks to create content networks that reinforce your brand's association with key subtopics across the web. - Improve indexation: Ensure your supporting content is being discovered by using Left sidebar → Authority → Indexer (URL Indexer) to submit new and updated pages for faster indexing. - Launch outreach campaigns: Earn mentions and citations in high-authority sources related to your subtopics using Left sidebar → Authority → Campaigns. External references signal to LLMs that your brand is a trusted source on a given subject. - Monitor LLM response changes: Revisit your AI Visibility dashboard regularly to track whether your actions are shifting how LLMs describe your brand within each subtopic over time. 💡 Quick Tips for Getting the Most From Subtopics - Focus first on high-frequency subtopics where your brand is mentioned but with neutral or negative sentiment — these offer the fastest improvement opportunities. - Prioritise subtopics that align with your core product or service offerings to ensure AI-generated answers are accurate and on-brand. - Cross-reference subtopics with your existing keyword and content strategy to find alignment between traditional SEO and LLM visibility goals. 🛠️ Need More Help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🗑️ Remove Auto-Generated Topics and Queries from LLM Visibility

🔍 Overview When you create or configure an LLM Visibility project, Search Atlas may automatically generate topics and related queries based on your project settings. If these auto-generated topics are not relevant to your goals, you can remove them along with their associated queries to free up space within your quota limit and replace them with queries that better reflect your business. This article walks you through how to remove auto-generated topics and their associated queries from an existing LLM Visibility project. 🧭 Before You Begin Keep the following in mind before deleting topics and queries: - Deletion is permanent. Removed topics and their associated queries cannot be recovered. Make sure you no longer need them before proceeding. - Quota is released immediately. Once a topic and its queries are deleted, your quota is updated straight away and you can add new queries without delay. - Associated queries are removed together. Deleting a topic will also delete all queries nested under it. If you only want to remove specific queries, you can do that independently without deleting the entire topic. 📍 Navigate to Your LLM Visibility Project 1. Log in to your Search Atlas account. 2. In the left sidebar, click AI Visibility. This takes you to the /llm-visibility section. 3. Locate and open the LLM Visibility project you want to edit. 🗂️ Remove an Auto-Generated Topic and Its Queries 1. Inside your project, navigate to the Topics section where your auto-generated topics are listed. 2. Identify the auto-generated topic you want to remove. Auto-generated topics are typically labelled or grouped separately from manually added ones. 3. Click the three-dot menu (⋮) or the options icon next to the topic name. 4. Select Delete Topic from the dropdown menu. 5. A confirmation prompt will appear. Review the number of associated queries that will also be deleted, then click Confirm Delete to proceed. 6. The topic and all its associated queries are now removed from your project, and your quota is updated. 7. Repeat steps 2–6 for each additional auto-generated topic you want to remove. ✂️ Remove Individual Queries Without Deleting the Topic If you want to keep a topic but remove only certain queries beneath it, follow these steps: 1. Click on the topic name to expand it and view its associated queries. 2. Locate the query you want to remove. 3. Click the three-dot menu (⋮) or the delete icon next to the query. 4. Select Delete Query and confirm when prompted. 5. Repeat for any additional queries you want to remove. ➕ Add Your Own Queries After Freeing Up Quota Once you have deleted the unwanted auto-generated topics and queries, your quota will reflect the newly available space. To add your promotional product queries: 1. Inside the same LLM Visibility project, navigate to the Topics section. 2. Click Add Topic to create a new topic, or select an existing topic to add queries beneath it. 3. Enter your new queries manually, or use the query suggestion tool if available. 4. Save your changes. Your new queries will now be tracked within the project. ❓ Frequently Asked Questions - How do I know which topics were auto-generated? Auto-generated topics are created by Search Atlas based on your project configuration. They may appear in bulk when a project is first set up. If you are unsure which topics were auto-generated versus manually added, review topics that do not align with your intended tracking goals. - Will deleting topics affect my historical data? Yes. Removing a topic and its queries will also remove any historical visibility data associated with those queries. Export any data you wish to retain before deleting. - How many queries can I add after freeing up quota? Your available quota is displayed within your project or account settings. Each deleted query returns one unit of quota back to your limit. 💬 Need Help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📅 Understanding LLM Visibility Data Update Schedule

📋 Overview LLM Visibility in Search Atlas tracks how often your brand or website appears in AI-generated responses across large language models. Because this data requires significant backend processing, it updates on a monthly schedule rather than continuously like keyword data. This article explains how the update cycle works and what to expect. 🔄 How Often Does LLM Visibility Data Update? LLM Visibility data updates once per month. This means the data you see reflects a snapshot from the previous month's processing run. For example, if today is January 27th and the data displayed shows January 10–11, this is expected behavior. The next data refresh will occur at the start of the following month and will then appear in your dashboard shortly after. ⚙️ Who Controls the Update Schedule? LLM Visibility updates are managed by the Search Atlas development team on a monthly basis, not by automated daily or weekly pipelines. This is intentional — querying large language models at scale requires careful coordination to ensure data accuracy and platform stability. As a result: - You cannot trigger a manual refresh of LLM Visibility data from within the platform. - There are no settings or buttons to request an on-demand update. - The data will update once the development team runs the next scheduled monthly refresh. 📊 How Is This Different from Keyword Data? Keyword rank tracking and LLM Visibility operate on completely separate update cycles: - Keyword data can be refreshed more frequently and is driven by automated crawling processes. - LLM Visibility data is updated monthly by the development team due to the complexity of querying AI language models at scale. This difference is by design. Do not expect LLM Visibility to reflect real-time or weekly changes the way keyword rankings might. 🗺️ Where to Find LLM Visibility in the Platform LLM Visibility data is accessible within Search Atlas. Look for LLM Visibility or AI Visibility sections in your platform navigation. If you are unsure where to find the relevant section for your account, the support team can point you to the correct location. ✅ What You Should Do While Waiting for New Data Since data refreshes monthly, here is how to make the most of the current data while waiting for the next update: - Review trends over time: Monthly snapshots are still valuable for identifying directional trends in your brand's AI visibility. Compare month-over-month results rather than looking for daily changes. - Document your current standings: Note which queries your brand currently appears in (or is absent from) so you have a clear baseline to compare against when new data arrives. - Focus on content improvements: Use the current data to identify gaps in your brand's AI presence and make content or authority-building improvements in the meantime. - Set expectations with your team: Communicate to stakeholders that LLM Visibility data is a monthly metric, not a real-time signal, so reporting cycles are aligned accordingly. - Check back at the start of next month: New data is released on a monthly cycle, so plan your review cadence around the beginning of each calendar month. If you are seeing data that appears significantly outdated beyond a full month, or if you have questions about your specific LLM Visibility readings, please reach out for support. When contacting support, have your project name and the date range currently shown in your LLM Visibility report ready so the team can investigate efficiently. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

🤖 Understanding LLM Visibility Competitor Ranking Metrics

🔍 Overview When reviewing your LLM Visibility data, you may notice that some competitors — for example, a domain like Quantive.com — display a higher Rank or Visibility Score than your own site, even though they show zero citations in the tool. This can feel contradictory, but it reflects how these two metrics are calculated independently of each other. This article explains what each metric measures and how to interpret them together. 📊 What the Rank and Visibility Score Actually Measure It is important to understand that Rank and Visibility Score are not the same metric and do not depend on each other directly. - Rank reflects how prominently a domain appears in Large Language Model (LLM) responses across the tracked keyword set. A domain can rank highly if it is frequently mentioned, recommended, or referenced by AI models — even without a hyperlinked citation being captured. - Visibility Score is a composite score that factors in the frequency and positioning of a domain's appearances across AI-generated responses. A high score indicates that the domain surfaces often and in prominent positions within those responses. - Citations, by contrast, are trackable links or direct source attributions that an LLM includes in its output. Some AI models reference a domain by name or recommend it without producing a formal citation link — these appearances still contribute to Rank and Visibility Score but do not increment the citation count. 💡 Why a Competitor Can Have Zero Citations but a High Score This scenario is more common than it may seem, and it comes down to a key distinction: being mentioned is not the same as being cited. 1. LLMs mention without linking. AI models like ChatGPT, Gemini, or Perplexity frequently name brands and domains in their responses without attaching a clickable source link. These name-drops are captured in Rank and Visibility Score calculations but do not register as citations. 2. Model behaviour varies by query type. For informational or navigational queries, LLMs are more likely to recommend a brand by name. For research-heavy queries, they are more likely to cite a source. A competitor strong in branded mentions will score well even with few or no citations. 3. Citation tracking depends on link availability. If an LLM response does not include a structured source block or inline hyperlink, no citation is recorded — even if the brand is prominently featured in the answer. In short, a competitor with a high Visibility Score and zero citations is likely being named or recommended frequently by AI models without those responses producing trackable citation links. 🛠️ How to Use This Data Effectively Rather than treating a high competitor Visibility Score as an error, use it as a signal to inform your strategy. - Assess brand mention strength. A competitor with high Rank and Visibility but zero citations has strong brand recognition in AI outputs. This suggests their brand or domain name is well-embedded in LLM training data or frequently reinforced through content. - Audit your own citation-to-mention ratio. If your site has citations but a lower Visibility Score, focus on increasing the breadth of topics and queries where your brand appears — not just where it is linked. - Use LLM Visibility alongside other tools. Navigate to Left sidebar → AI Visibility (URL: /llm-visibility) to explore your full dataset. Cross-reference with Left sidebar → Keywords → Rank Tracker to understand how traditional search performance correlates with AI visibility. - Track trends over time. A single snapshot can be misleading. Monitor how competitor scores shift week over week to identify whether their AI presence is growing, stable, or declining. ✅ Key Takeaways - Rank and Visibility Score measure AI mention prominence — citations are a separate, narrower metric. - Zero citations does not mean zero AI presence; it means the AI models are referencing that domain without producing trackable citation links. - A competitor outranking you in LLM Visibility is a strategic signal, not a data error. - Use the full suite of metrics together for the most accurate picture of competitive AI presence. 💬 Need More Help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📋 LLM Visibility Data Retention and Deletion Policy

📋 What Happens to Your LLM Visibility Data Your LLM Visibility data is retained in your Search Atlas account for as long as your subscription remains active. We do not automatically delete or remove any LLM Visibility data during normal account operation. Your tracked data, historical records, and monitoring insights remain safely stored and accessible whenever you need them. 🔒 Data Retention During Your Subscription While your account is active, all LLM Visibility data is preserved, including: - Historical tracking data and snapshots - Competitor visibility metrics - QUEST LLM Visibility campaign records - Performance trends and analytics - All stored insights and reports You can access this data at any time by navigating to AI Visibility in the left sidebar, or by visiting the QUEST LLM Visibility section under Authority in the left sidebar. 🗑️ What Happens if Your Account is Cancelled If you cancel your Search Atlas subscription, your account data is handled as follows: - Your account will be marked as inactive - Your account data and projects remain on your account and are not deleted - If you resubscribe, your data and projects will be available again If you have questions about your account after cancellation, contact us through the live chat widget. ⚙️ Account Deletion and Data Removal If you request account deletion or if your account is suspended due to violation of our terms of service, data removal may occur. The timeline and process depend on: - Legal and compliance requirements - Data residency regulations in your region - Your specific account agreement We recommend exporting or backing up any critical LLM Visibility data before initiating account deletion if data preservation is important to your business. 💡 Best Practices for Data Protection To ensure your LLM Visibility data remains safe and accessible: 1. Keep your subscription active to guarantee continuous data retention 2. Regularly download or export reports from your LLM Visibility dashboard for backup purposes 3. Review your account settings and billing information to avoid accidental cancellation 4. Document any custom QUEST LLM Visibility campaigns or monitoring setups for future reference ❓ Do You Have Questions About Your Data Your LLM Visibility data is yours, and we take data protection seriously. If you need clarification on your account's specific data retention policy, your contract terms, or how to export your data, we're here to help. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📊 Understanding Perplexity Visibility in Site Metrics

📋 Overview When reviewing Perplexity visibility data inside AI Visibility (left sidebar → AI Visibility), you may notice that the domain displayed as a top-ranking or recommended result differs from the site you entered. This is expected behaviour and reflects how Perplexity's AI-powered search engine surfaces content — not a data error in Search Atlas. 🔍 Why a Different Domain Appears Perplexity is an AI answer engine. Unlike traditional search engines that return a ranked list of blue links, Perplexity synthesises answers and cites the sources it considers most authoritative for a given query. This means: - The domain Perplexity recommends may not be the site you are analysing — it is the site Perplexity's model currently favours for related queries. - Search Atlas reports this data accurately and without modification. If Perplexity cites a different domain than the one you entered, it is because that is the source Perplexity selected in its generated answer. - This is a competitive insight, not a bug. It tells you which domain is winning visibility in AI-generated responses for your target topic. 📊 How to Read the Perplexity Visibility Metric To access and interpret this data, go to the left sidebar → AI Visibility and add the domain you want to analyse. Once the report loads, locate the Perplexity visibility data within the report. Any domain shown there is a site that Perplexity has cited in AI-generated answers related to your entered domain's topic or niche. Treat these domains as AI search competitors — sites you may want to study or outperform to increase your own Perplexity citation rate. ⚙️ Common Scenario Explained As a general example: if you enter your domain and the Perplexity visibility data shows a different domain, it means that when users ask Perplexity questions related to your niche, Perplexity's AI is currently citing that other domain as its preferred source. Search Atlas surfaces this so you can identify the gap and take action. This is not misleading data — it is a direct reflection of the AI search landscape for that niche at the time the data was collected. 💡 How to Improve Your Perplexity Visibility If a competitor domain is being cited instead of yours, consider reviewing the content and authority signals of the sites that are appearing, and look for opportunities to strengthen your own site's coverage of relevant topics so that AI answer engines are more likely to cite it as an authoritative source. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

⏳ New LLM Platforms Need Time to Show Data

🔍 Overview If you recently upgraded your plan or noticed that a platform like Grok or Copilot appears in your AI Visibility dashboard but shows no data, this is expected behavior. Newly-added or newly-enabled LLM platforms require a 2–3 week data accumulation window before trends, scores, and visibility statistics can be generated and displayed. This article explains why this happens, what the ramp-up period looks like, and what you can do in the meantime. 📋 Why No Data Appears for New Platforms Search Atlas calculates AI Visibility trends by collecting and comparing data across multiple snapshots over time. A single snapshot is not enough to generate a meaningful trend line or visibility score. For a newly-enabled platform, the system needs to: - Complete its first full data collection cycle for that platform. - Accumulate enough historical snapshots to calculate movement and trends. - Process and surface those results inside your dashboard. Until that threshold is reached, the platform row will appear in your dashboard but display no statistics. This is not a bug and is not related to your snapshot schedule or plan status. 📅 What the 2–3 Week Window Means The 2–3 week ramp-up period begins from the date the platform was first enabled on your account — either by Search Atlas adding it to the platform roster, or by your account gaining access to it through a plan upgrade. - Week 1: Initial snapshots are collected. No trend data is visible yet. - Week 2: Additional snapshots accumulate. Data may begin appearing for some keywords, but coverage will be incomplete. - Week 3 and beyond: Enough snapshots exist to generate reliable trends, scores, and visibility percentages across your tracked keywords. The exact timing can vary slightly depending on your keyword volume and snapshot frequency set on your project. ⬆️ What Changes After a Plan Upgrade Upgrading to a higher plan — such as the Pro plan — unlocks access to additional LLM platforms like Grok and Copilot. However, unlocking a platform does not retroactively populate historical data. Data collection starts from the moment access is granted, so the 2–3 week window applies from your upgrade date. If you upgraded recently and see these platforms listed in your dashboard with no numbers, your account is working correctly. The data will populate automatically as snapshots accumulate — no action is required on your part. 🖥️ How to Check Your AI Visibility Dashboard 1. In the left sidebar, click AI Visibility (URL: /llm-visibility). 2. Review the platform list. Platforms still in their ramp-up period will appear without visibility scores or trend graphs. 3. Check back after 2–3 weeks from your upgrade or from the date the platform first appeared on your account. You do not need to refresh, re-run snapshots, or contact support to trigger data collection — it happens automatically on your project's snapshot schedule. ❓ How to Tell If This Is Your Situation This ramp-up scenario is the most likely explanation if all of the following are true: - You recently upgraded your plan and Grok or Copilot appeared as new platforms shortly after. - The affected platforms show no data at all — no score, no trend line, no keyword-level breakdown. - Other platforms on your account (such as ChatGPT or Perplexity) are displaying data normally. If other platforms are also missing data, or if it has been more than 3 weeks since the platform was enabled and still nothing appears, that may indicate a different issue worth investigating. ✅ Quick Summary - Grok, Copilot, and other newly-enabled platforms need 2–3 weeks of snapshot data before statistics appear. - This applies after a plan upgrade — historical data is not backfilled. - No action is needed; data populates automatically. - Check your dashboard at AI Visibility in the left sidebar after the ramp-up window has passed. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

⏳ Grok, Copilot or New LLM Platforms Not Showing Data Yet

📋 Overview If you recently upgraded to the PRO plan and enabled new LLM platforms such as Grok or Microsoft Copilot, you may notice that visibility data has not appeared yet — even after refreshing. This is expected. Newly added platforms require time to collect and process data before results appear in your dashboard. ⏱️ Why Data Is Not Showing Immediately When a new LLM platform is activated, Search Atlas begins tracking visibility data from that point forward. The initial data population is not instant — the system needs time to crawl, analyze, and aggregate results. This process typically takes up to 24–48 hours from the moment your plan upgrade and platform activation are both in place. ✅ What to Do 1. Confirm your PRO plan is active in your account billing settings. 2. Confirm platforms are enabled in your AI Visibility (formerly LLM Visibility) settings (Left sidebar → Authority → QUEST AI Visibility (formerly LLM Visibility)). 3. Look for the processing indicator — when a platform is newly activated, the dashboard displays a processing/loading state while analysis runs. This confirms that data collection has started and the platform is being analyzed. 4. Wait 24–48 hours after both steps above are complete. 5. Refresh your dashboard after the wait period to check for updated data. 📌 Important Notes - Data collection begins from the moment a platform is activated — historical data is not backfilled. - If you recently created a new brand or project and the dashboard shows empty data, a known bug that prevented country analysis from running at project creation has been resolved. If the dashboard still shows empty data for a new project after 48 hours, contact support for investigation. - Anthropic Claude and Google AI Overview are not yet available as tracked platforms — they are planned additions and cannot yet be selected in AI Visibility (formerly LLM Visibility) settings. - If data still does not appear after 48 hours with confirmed settings, contact support for investigation. 💬 Still need help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📊 Add Competitors and Export LLM Visibility Reports

📋 Overview Search Atlas's AI Visibility section lets you track how often your domain appears in AI-generated responses — and how that compares to your competitors. This article explains how to add and manage competitors and export your LLM visibility data. 🌐 Navigating to AI Visibility All LLM visibility tools live under the AI Visibility section of Search Atlas. Open the left sidebar and click AI Visibility to expand the section, then select the relevant sub-section for the task you want to complete. ➕ Adding Competitors to a Project Once your domain project is set up, you can add competitors to compare LLM visibility data side by side. To add a competitor: 1. Navigate to the AI Visibility section in the left sidebar. 2. Open your domain project. 3. Look for the competitor management area within the project view. 4. Enter the competitor's domain and save your changes. You can add multiple competitors to a single project. Once added, each competitor's domain will appear alongside yours so you can compare LLM visibility performance directly. 📈 Comparing Competitor Visibility After adding competitors, the AI Visibility section displays a comparison view showing how your domain stacks up against competitors in AI-generated results. Key metrics typically include how frequently each domain is cited by AI models and how performance changes over time, helping you spot gains or drops quickly. Explore the available sub-sections within AI Visibility to review breakdowns by topic, query, sentiment signals, and citation data for both your domain and your competitors. 📤 Exporting LLM Visibility Reports You can export visibility data from within the AI Visibility section as a downloadable file. To export a report: 1. Navigate to the relevant view or table within AI Visibility that contains the data you want to download. 2. Look for an export or download option associated with that view. 3. Click the export button and save the file to your device. If you do not see an export option for a specific data view, or if you are unsure which views support export, reach out to our support team for guidance on what is currently available. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📤 Exporting LLM Visibility Alerts and Citation Reports

🔍 Overview When Search Atlas detects a change in how AI language models cite your site, it sends a Citation Movement Detected alert email. This article explains what you can do with that alert, whether it can be downloaded directly, and how to export the underlying citation movement data to share with clients. 📧 Can I Download the Alert Email Directly? The Citation Movement Detected alert email itself cannot be downloaded or exported as a document directly from the Search Atlas platform. The email is a notification only — it is delivered to your inbox to let you know a change has occurred, but it does not function as a standalone exportable report. However, you have several practical options to capture and share the information with clients: - Screenshot the email: Take a screenshot of the alert email and include it in a client report or presentation. - Print to PDF: Open the alert email in your email client, use your browser or email app's Print function, and select Save as PDF to create a document version. - Copy the data: Copy the key metrics and citation changes mentioned in the email and paste them into your own report template. 📊 How to Export Citation Movement Data from the Platform For a more complete and professional export, you can pull citation movement data directly from Search Atlas. The most relevant data lives in your Site Metrics and LLM visibility reports. Follow these steps: 1. Log in to Search Atlas and navigate to your project dashboard. 2. In the left sidebar, select OTTO SEO, then click Overview. 3. Review the OTTO ROI and visibility sections, which reflect AI citation performance over time. 4. To access audit-level data, go to OTTO SEO → Site Audit → All Audits and filter for LLM or citation-related audit items. 5. Where an export option is available on a data table or chart, click the Export or Download button (typically a download icon in the top-right corner of the report panel) to save the data as a CSV or PDF file. Not all panels display an export button — if one is not visible, use the screenshot or print-to-PDF method described above to capture the data. 📁 Alternative Export Formats Available Depending on the report section, Search Atlas supports the following export formats for LLM and site visibility data: - CSV: Available on most data tables; ideal for sharing raw metrics or importing into spreadsheets. - PDF: Available on select summary and overview panels; suitable for client-facing documents. - Screenshot / Print to PDF: A reliable fallback for any view that does not offer a built-in export button. 🤝 How to Share Alert Data with Clients To present Citation Movement Detected information professionally to your clients, we recommend the following workflow: 1. Export the underlying data from OTTO SEO using the steps above, or capture a screenshot of the alert email. 2. Add context by including the date the alert was triggered, which AI models were affected, and whether citation frequency increased or decreased. 3. Combine with OTTO ROI metrics from OTTO SEO → Overview to show the business impact alongside the citation movement. 4. Use your own report template — paste the exported CSV data or screenshots into a Google Doc, slide deck, or PDF report for your client. This approach gives clients a clear, branded summary rather than a raw platform notification. 💡 Tips for Ongoing Client Reporting - Set a regular cadence (weekly or monthly) to export citation and LLM visibility data so you always have historical snapshots available. - Save exported CSVs with a date in the filename (for example, citation-movement-2026-08-25.csv) to make version tracking easy. - If your client also has platform access, you can invite them as a collaborator so they can view LLM visibility data directly inside Search Atlas. 🆘 Need More Help? If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📄 Export LLM Visibility Alerts as Client Documents

📋 Overview Search Atlas sends automated email alerts when your site's LLM visibility changes — including when new AI citations are detected or citation movement occurs. Customers often want to share these notifications with clients as a polished, downloadable document. This article explains what's currently possible and the best workaround to use right now. 🔍 What Are LLM Visibility Alerts? LLM visibility alerts are automated email notifications triggered by changes in how AI models (such as ChatGPT, Gemini, or Perplexity) cite your website. These alerts are delivered directly to your inbox and are designed to keep you informed of AI visibility performance changes. ⚠️ Current Export Limitation At this time, Search Atlas does not offer a one-click option to download LLM visibility alert emails as a PDF or document directly from the platform. This is a feature request that has been noted by our team. 🛠️ Recommended Workaround: Save Your Email as a PDF Until a native export option is available, the fastest way to create a shareable document from an LLM visibility alert email is to save it as a PDF from your email client. Follow these steps: 1. Open the LLM visibility alert email in your inbox (Gmail, Outlook, Apple Mail, or similar). 2. Click Print — this is usually found in the email's options or three-dot menu. 3. In the print dialog, change the Destination or Printer to Save as PDF. 4. Click Save and choose a location on your computer. 5. Send the saved PDF file directly to your client. This produces a clean, professional-looking document that preserves all the alert details included in the email notification. 📬 Submitting This as a Feature Request If a native in-platform export option for LLM visibility alerts is important to your workflow, you can submit this as a feature request by reaching out to our team. When doing so, it helps to include: - Your project name and the email address associated with your account. - A description of how you would use a native export or sharing option (e.g., client reporting, agency use). If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be connected with a member of our team.

📊 LLM Visibility Credits Maxed Out by Automated Refreshes

🔍 What Happened? If your LLM Visibility credits are suddenly exhausted and you haven't been running manual scans, the cause is likely a burst of automated refresh jobs firing in a short window. For example, a known incident caused 32 refresh jobs to run in a single day, consuming most of a monthly allocation in one go. This is not caused by your manual actions — it is a background process tied to LLM Visibility tracking. ⚙️ Why Automated Refreshes Consume Credits LLM Visibility tracking periodically refreshes data for your active projects automatically. Under normal conditions, these refreshes are spread across the month and stay within your allocation. However, in some cases a large number of refresh jobs can fire at once — rapidly draining your monthly credit quota before you have a chance to notice. A known engineering issue caused monthly credit resets to fail to fire for some accounts, leaving users stuck at their allocation cap even when a new billing period began. This issue has since been resolved, but if your quota was consumed during that window it may not have been automatically restored. 🛠️ How to Check Your LLM Visibility Activity 1. Navigate to the left sidebar → AI Visibility to review the status of your active projects. 2. Check whether your projects show quota consumption or blocked scans — a maxed-out allocation can prevent new scans from running. 3. Review your active projects to identify which ones are set up for automated tracking, as each active project contributes to refresh job volume. 💡 What You Can Do Right Now - Do not add more active projects while your quota is maxed out — additional projects increase the number of automated refreshes that fire each cycle. - Check your project activation settings by reviewing which projects have LLM Visibility tracking enabled. Deactivating projects you no longer need actively monitored will reduce automated refresh consumption going forward. - Request a quota reset if your credits were consumed by an automated burst rather than intentional use — see the section below. 🔄 How to Request a Credit Quota Reset If automated refreshes exhausted your allocation unexpectedly, our team can reset your quota. This is not something you can do yourself from within the platform — it requires action from our support team. To get your quota reset as quickly as possible: 1. Reach out to our support team directly through the platform. 2. Share the date(s) when you noticed the credits were depleted and confirm that you did not intentionally trigger a large number of manual scans. 3. Our team will review your account and apply a quota reset where applicable. If you need further assistance, please don't hesitate to contact our support team via the chat widget in the platform — we're happy to help.

LLM Visibility Quota Not Resetting After Billing Date

🔍 Overview Each billing cycle, your LLM Visibility quota should reset automatically on your renewal date. In some cases, a known platform issue can prevent this reset from firing correctly, leaving your quota appearing fully consumed even after your billing date has passed. This article explains what to check and how to get the issue resolved quickly. ⚠️ Is This Happening to You? You are likely affected if you notice all of the following: - Your LLM Visibility quota appears fully used up. - Your billing cycle renewal date has already passed. - You have not been able to run new LLM Visibility reports despite the new billing period starting. - No new quota has been credited to your account after the expected reset date. This is a known backend issue that has affected a number of paying customers. It cannot be resolved by making changes within your account settings — it requires a manual reset performed by the Search Atlas Billing and Accounts team. 🛠️ What You Should Do Follow these steps to confirm the issue and gather the information our team needs to perform the manual reset on your behalf as quickly as possible: 1. Confirm your billing renewal date. Click your avatar in the top-right and select Billing (Billing page) to note the exact date your cycle was supposed to renew. This helps our team verify the discrepancy on the backend. 2. Note how many days have passed. Record today's date and how many days it has been since the expected reset. Our team will need this context. 3. Check for active projects. Review your LLM Visibility reports to confirm whether active projects are genuinely consuming your quota, or whether the quota appears consumed with no active reports visible. Make a note of what you find. 4. Gather your account details. Have your account email address or workspace name ready, along with the information collected in the steps above. 5. Contact our support team. Reach out to the Search Atlas support team through the contact method available to you (such as the in-platform chat or your account's support channel). Share your billing renewal date, how many days the quota has been stuck, and whether any active reports are visible. The support team will escalate to the Billing and Accounts team, who will perform the manual backend reset and restore your quota. 📋 What to Include in Your Message To help our team resolve this without unnecessary back-and-forth, include the following details in your message: - Your account email address or workspace name. - The date your billing cycle was expected to renew. - Today's date and how many days have passed since the expected reset. - Whether active LLM Visibility reports are visible in your account or whether the quota appears consumed with no active reports showing. Once our Billing and Accounts team is notified and has this information, they can perform the backend reset and restore your quota promptly.

🌟 How to Improve Visibility in ChatGPT Searches

To improve visibility in ChatGPT searches, brands must focus on Generative Engine Optimization (GEO). Unlike traditional SEO, GEO prioritizes structured, high-quality content that AI models can easily interpret and surface in responses. ChatGPT visibility is crucial because AI-driven recommendations now significantly impact discovery, trust, and conversions. Success requires optimizing for generative engines, monitoring AI crawlers, and continuously adapting to evolving AI search technologies. 💡 Benefits of Optimizing for ChatGPT Visibility Optimizing for ChatGPT offers multiple advantages for businesses: - 🚀 Increased Organic Branded Traffic: ChatGPT recommendations drive searches on Google or Bing. - 👀 Improved Brand Visibility: Gain exposure to new audiences directly in AI responses. - 💰 Increased Conversions: AI-driven queries deliver pre-qualified, high-intent traffic. - 🤝 Improved Brand Trust: Appearing in ChatGPT signals authority and credibility. 🧠 How Does ChatGPT Rank Websites? Unlike traditional search engines, ChatGPT relies less on backlinks and more on content quality, accuracy, and relevance. It prioritizes structured and reputable sources. This process, known as Generative Engine Optimization (GEO), is becoming essential for modern marketers. 📌 What Helps Businesses Rank in ChatGPT? 1. Content Optimization AI prefers content that is clear, structured, and relevant. Key strategies include: - Content Quality: Authoritative, well-researched answers to user questions. - Formats: Q&A structure, hierarchical headings, short paragraphs, and bullet points. - Summaries: Snippet-ready highlights at the top of articles. - Freshness: Regularly updated statistics, examples, and recommendations. - User Intent Alignment: Match content depth to the query’s purpose. 📊 Use the Search Atlas Scholar Tool to measure hidden GEO factors like: Path:Left Side Bar ➝ Content ➝ Scholar - Content Clarity & Flow - Factuality & Information Gain - Human Effort (schema, images, formatting) - Freshness & Intent Alignment - Entities & Contextual Flow - Query Relevance & Readability 2. Online Presence and Authority Strong online authority signals trust to AI models. To build it: - Secure brand mentions on reputable platforms. - Earn backlinks from trusted websites in your niche. - Get featured consistently in review sites, directories, and industry sources. - Aim for mentions and backlinks from sources ChatGPT already uses. 💡 Use the Search Atlas Quest Tool: Path: Left Side Bar ➝ Authority ➝ LLM Visibility ➝ Quest LLM Visibility - Enter a query. Quest analyzes the exact sources AI relies on. - Launch instant outreach campaigns to those sites. 3. Technical & On-Page SEO Strategies AI models need structured, optimized data. Focus on: - Schema Markup: Implement structured data for Q&A, entities, and FAQs. - Bing Optimization: Since ChatGPT integrates with Bing, strong performance there improves AI visibility. - Site Speed: Ensure fast load times and mobile-friendliness. - Keyword Research: Use conversational, question-based keywords. 💡 Pro Tip: Add your site to Bing Webmaster Tools to maximize discoverability: 1. Add and verify your site. 2. Submit URLs for faster indexing. 3. Monitor crawl activity. 4. Local Business Visibility For local businesses, GEO also means local optimization: - Create and verify a Bing Places listing. - Ensure consistent details across Google, Yelp, BBB, and Bing. - Encourage fresh customer reviews and feature them on your site. - Automate local SEO with tools for keyword tracking, competitor monitoring, and review management. 5. Monitoring & Adaptation Visibility in ChatGPT is dynamic. Stay agile by: - Using monitoring tools to track content performance. - Keeping up with AI technology updates. - Testing new strategies and refining based on results. 6. NLP (Natural Language Processing) Optimization Since AI understands natural language, optimization must adapt: - Write in conversational tones. - Use semantic keyword variations and topic clusters. - Include follow-up questions and answers within your content. - Prioritize entity relationships over single keywords. 🔍 How to Track LLM Crawler Activity LLM crawlers (e.g., GPTBot, ClaudeBot, Bing, Google) visit your site to gather data. To monitor them, use this path inside Search Atlas Dahsboard: OTTO SEO ➝ Site Audit ➝ Crawl Monitoring: - See which pages attract AI crawlers. - Track crawl frequency and bot priorities. - Adjust internal linking and technical SEO for better discoverability. 💡 This tool is integrated with OTTO SEO AI agent, which automatically resolves crawlability issues. Improving ChatGPT visibility means embracing Generative Engine Optimization across content, authority, technical SEO, local presence, and NLP strategies. With tools like Search Atlas Scholar, Quest, and Crawl Monitoring, businesses can track, adapt, and lead in AI-driven discovery. In the AI-first search era, being visible in ChatGPT is no longer optional—it’s the future of brand growth. 🚀

View and Manage Your LLM Visibility Quota Sites

Overview Your LLM Visibility feature runs on a quota system, meaning a set number of sites can be active under your plan at any one time. If you run into issues — such as being unable to enable LLM Visibility for a new site, or seeing unexpected quota limits — the most common cause is that your quota slots are already occupied by existing sites. This article explains how to check which sites are currently using your LLM Visibility quotas and how to manage them. Why You May Be Hitting a Quota Limit LLM Visibility is tied to a credit and quota system. Each site you activate consumes a quota slot. If all your slots are taken, you will not be able to enable LLM Visibility for additional sites until you free up space by removing or deactivating one of your existing sites. Common signs that you have hit your quota limit include: - You are unable to enable LLM Visibility for a new site. - You are unsure which sites are currently counted against your quota. How to View and Manage Your LLM Visibility Quota Sites To see which sites are currently consuming your LLM Visibility quota and to free up slots, we recommend reaching out to our support team directly. Because quota assignments are managed at the account level, our team can: - Look up which sites are currently active under your LLM Visibility quota. - Remove or reassign a site on your behalf to free up a quota slot. - Advise on options to increase your quota allocation if you need coverage across more sites. When you contact us, please have your account details and the site URLs you want to add or remove ready so we can resolve this as quickly as possible. Tips for Managing LLM Visibility Quotas Efficiently - Regularly review which sites are active under your quota to avoid running out of slots unexpectedly. - Prioritise sites with the highest strategic value for LLM Visibility monitoring so that when you do need to free up a slot, you know which sites are lower priority. - If you anticipate needing LLM Visibility across a larger number of sites, ask our support team about quota increase options before you hit the limit. If you need help identifying or adjusting your LLM Visibility quota sites, please reach out to us via the chat icon in your Search Atlas account and our team will be happy to assist.

📊 AI Visibility Data for Copilot Requires a Collection Period

After upgrading to Pro and enabling Copilot in AI Visibility (formerly LLM Visibility), your platform is correctly configured — Search Atlas just needs 2–3 weeks of data collection before trend statistics can appear. Note: Grok has been removed from AI Visibility (formerly LLM Visibility) due to upstream access restrictions by xAI — refer to the removal-notice banner in-product for the latest status. 📊 Why Copilot Data Is Not Showing After Your Pro Upgrade When you enable a new LLM platform in AI Visibility (formerly LLM Visibility), Search Atlas begins collecting data immediately — but it cannot generate trend statistics until enough historical data has accumulated. Platforms that have been tracked for months already have the data depth needed to produce reports; newly enabled platforms do not. This is expected behavior, not a bug or a misconfiguration. ⏳ How Long the Data Collection Period Takes AI Visibility (formerly LLM Visibility) requires 2–3 weeks of continuous data collection before meaningful trend statistics appear for a newly enabled platform. During this window: - Tracking is active and running in the background — no data is lost for supported platforms. Data collection depends on upstream data-vendor access and may be subject to change if a provider restricts access. - All data collected during the waiting period will be included in your reports once the threshold is reached. - Platforms you were already tracking before your Pro upgrade may show data sooner because they have had more time to accumulate history. If trend cards appeared blank immediately after enabling a platform and before the collection window elapsed, this was a known display bug that has since been fixed. If you still see blank cards after 2–3 weeks, contact support. ⚙️ How to Confirm Copilot Is Enabled Correctly Verify that your new platform is toggled on so tracking runs while you wait: 1. Go to Settings in your Search Atlas account. 2. Open the AI Visibility (formerly LLM Visibility) section. 3. Confirm that Copilot is enabled. If Copilot appears as enabled, your setup is correct. Data will appear automatically once the 2–3 week collection period is complete — no further action is needed. If data has not appeared after 3 weeks, contact support. ⚠️ If Data Does Not Appear After 3 Weeks If data has not appeared after 3 weeks, or if you see a platform removal notice in-product, the platform may no longer be supported. Contact support for current platform availability. 🎯 You now know that the 2–3 week data collection period is a normal part of onboarding any new LLM platform in AI Visibility (formerly LLM Visibility). Once that window passes, Copilot will appear in your reports alongside your other platforms — check back then to begin analyzing your trend data.

🛠️ Inconsistent Decimal Places in AI Visibility Scores

This article explains a known cosmetic display issue in the AI Visibility (formerly LLM Visibility) tab where some scores show more decimal places than others, and confirms that a fix is already in progress. Your visibility and sentiment data is accurate and needs no action from you. 🔍 What's Happening in the AI Visibility Tab In the AI Visibility (formerly LLM Visibility) tab, visibility and sentiment scores display with inconsistent decimal precision on the same screen. The two card groups round numbers differently, which can make them look like they measure different things. 📊 Where the Difference Appears - Top mini-cards — Overall Visibility Score, Overall Sentiment, and Citations Found show whole numbers or one decimal place, such as 0, 65.9 %, or 2.4K. - Platform breakdown cards — Visibility by Platform and Sentiment by Platform, along with the delta and pts change indicators, show three decimal places, such as 49.138 or ↓ 7.013 pts. 👥 Who Is Affected This affects anyone viewing the AI Visibility (formerly LLM Visibility) tab. It is a display-only formatting issue: the extra decimals add false precision and visual noise, but the numbers themselves are correct. ✅ Your Data Is Accurate This issue only changes how the numbers are formatted on screen. The underlying visibility and sentiment data is calculated correctly and is unaffected. You can continue to rely on the values shown, including the platform scores and the points-change indicators. 🛠️ Workaround Steps No workaround is needed. Because this is a cosmetic formatting issue and the data is accurate, there are no steps to apply on your end. You can keep using the AI Visibility (formerly LLM Visibility) tab as normal. 📡 Engineering Status Our team is aware of this display issue and a fix is already in progress, awaiting release. The update will standardize every score across the visibility and sentiment cards to a single decimal place, so the top mini-cards and the platform breakdown cards match. Once the fix ships, values like 49.138 will display as 49.1. 📞 When to Contact Support You do not need to contact support for the decimal formatting itself, since it is a known issue with a fix on the way. Reach out to our support team only if you notice a separate problem, such as a score that appears clearly incorrect or data that fails to load. 🌀 Rest assured, our team is on it. The fix to standardize all AI Visibility (formerly LLM Visibility) scores to one decimal place is queued for release, and your visibility and sentiment data remains accurate in the meantime.

🔍 Why Brand Insights Citations Show Unrelated Domains

📌 What This Article Covers If you have reviewed the Citations section of your Brand Insights report and noticed a domain that matches your topic but does not mention or belong to your business, you are not alone. This article explains why that happens, what those citations actually represent, and the steps you can take to evaluate them correctly. 🧠 How Brand Insights Gathers Citations The Citations section reflects the sources that large language models (LLMs) and AI search engines reference when answering questions related to your industry, topic, or service area. These are the same types of prompts your potential customers might ask an AI assistant. Because of this, the tool surfaces every domain the AI cited in response to a topic, not only the domains that name your specific business. The goal is to show you the wider landscape of who is being mentioned for the queries that matter to you. Keep in mind that Citations are distinct from your Visibility Score: Citations list the sources AI references for a topic, while your Visibility Score measures how often your brand specifically is mentioned. A domain can appear in Citations without that meaning it references your business. ❓ Why an Unrelated or Competitor Domain Appears Seeing a domain that is relevant to your topic but does not reference your business is expected behavior. Common reasons include: - Topic-based matching: The AI cited that domain because its content is relevant to the question, even though it does not mention your brand. - Competitor visibility: Other businesses in your space are being referenced for the same queries, which is useful competitive insight. - Authority sources: Directories, publications, or informational sites are frequently cited because AI models consider them trustworthy for the topic. - Source classification: Each cited domain is categorized by its relationship to your brand — for example as a competitor, a platform, or a general reference source — so a domain may be listed as a reference even though it does not mention your business. - Indirect association: A domain may share keywords, location, or services with your business without being connected to it. In short, a citation is a signal about the topic and the broader conversation, not confirmation that the source is about your company. 📊 How to Read These Citations Correctly Use the Citations section as a competitive and opportunity map rather than a list of brand mentions. When you review a citation, ask yourself: 1. Is the topic relevant to my business? If yes, the citation is working as intended. 2. Who is being cited instead of me? These domains show where you could earn visibility. 3. Is this a source I could be featured on? Directories and publications often present outreach or content opportunities. 4. Does this reveal a content gap? If competitors are cited for a topic you cover, it may signal an area to strengthen. ✅ What to Do With This Information Rather than treating an unrelated domain as an error, turn it into action: - Identify opportunities: Note authoritative domains where your business could be added or mentioned. - Benchmark competitors: Track which rivals appear for your key topics over time. - Guide your content: Create or improve content that targets the queries where you are not yet cited. - Monitor changes: Revisit the report regularly to see whether your visibility improves. ⚠️ When a Citation May Be Worth Reviewing While most unrelated citations are expected, you may want a closer look if you notice a domain that is entirely off-topic, in a different language or region than your audience, or repeatedly appearing without any clear connection to your industry. These cases are uncommon, but our team can help you interpret them.

🔍 Quest LLM Visibility Usage Guide

🔍 What Is Quest LLM Visibility Quest LLM Visibility helps you track how your domain appears in responses from large language models. Use it to identify visibility gaps and improve AI-driven search performance. 🛠️ How to Access Quest LLM Visibility Navigate to the left sidebar and select Authority followed by QUEST AI Visibility. The tool loads a query analysis interface where you can enter prompts and review results. 📊 Analyzing a Query Click Analyze query and enter your target prompt. Select any active domains from your projects. Submit the request to generate visibility data across multiple AI models. 📈 Viewing and Interpreting Results After analysis completes click View to open detailed reports. Review sentiment scores topic coverage and exact mentions. Use Open query actions to export data or rerun tests with adjustments. 🚀 Best Practices - Run analyses on high-value queries monthly - Compare results across different AI models - Track changes after content updates - Combine findings with Authority tools for stronger outcomes If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be instantly connected with a member of our team.

📊 Understanding Query Visibility Reports

🔍 How query types are handled Search Atlas separates queries into two groups: - Branded queries: Searches that mention your company, product, or brand name. - Non-branded queries: General searches that do not mention your brand. Both query types help measure how AI systems mention your business. However, they are used differently in reporting. 📈 How Overall Visibility % is calculated Overall Visibility % is calculated only from non-branded queries. This shows how visible your business is when people search for general topics without already naming your brand. Branded queries are excluded from this percentage so the result reflects discovery by new or broader audiences. Branded queries still contribute to citation tracking and sentiment analysis. 💬 Why branded queries still matter Branded queries help Search Atlas evaluate whether AI answers mention your business when users search for it directly. They can affect: - AI citations and brand mentions - Sentiment associated with your brand - The context and accuracy of AI-generated answers These results may appear in query-level details even though they do not change Overall Visibility %. 📄 Why the dashboard and report can differ The dashboard and exported or delivered report may not match immediately because they can be generated at different times. The dashboard may display newly processed query results while a report is still using the previous completed data set. Differences can also occur when comparing Overall Visibility % with detailed branded-query results. The percentage includes only non-branded queries, while detailed results may include both branded and non-branded queries, along with citations and sentiment. ⏱️ Why processing can take 24–48 hours AI visibility data requires Search Atlas to run queries, collect responses, identify citations, classify branded and non-branded results, and analyze sentiment. Reports are delivered after this processing is complete. Allow up to 24–48 hours for new data, updates, or a report to finish processing. During this period, the dashboard and report may temporarily show different information. After processing completes, compare the same date range, query set, and metric. ✅ What to check 1. Open AI Visibility from the left sidebar. 2. Confirm the date range and selected project are the same in the dashboard and report. 3. Check whether you are comparing Overall Visibility % with branded-query results, citations, or sentiment. 4. Wait up to 48 hours for recently submitted or updated data to finish processing. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be instantly connected with a member of our team.

📊 Finding LLM Visibility Email Metrics in Dashboard

📧 Why Your Email and Dashboard May Look Different Search Atlas sends regular LLM Visibility email digests that highlight citation gains, positive brand mentions, and visibility movement across AI-powered search engines. These numbers are a snapshot of activity over a specific reporting period. When you open the dashboard after reading a great email report, the data you see may reflect a different date range or a broader view — which can make the dashboard look less impressive at first glance. This article will show you exactly where to find the metrics that match what you see in your email. 🔍 Step 1: Navigate to Site Metrics The LLM Visibility data lives inside the Site Metrics section of Search Atlas. To get there: 1. Log in to your Search Atlas account. 2. In the left sidebar, click Site Metrics. 3. Locate and select the site you want to review (for example, virtuas.com) from the list. 4. You will land on the Overview sub-page for that site. 📈 Step 2: Open the Overview Sub-Page The Overview sub-page is the primary place to review aggregated performance data for your site, including LLM citation and visibility trends. To reach it directly: 1. From Site Metrics, click your site name or ID in the list. 2. Then select Overview from the sub-navigation. Here you will find a consolidated view of your site's performance metrics, including any LLM-related visibility movement that was summarised in your email report. 📅 Step 3: Match the Date Range to Your Email Report A very common reason the dashboard appears to show weaker numbers is a mismatched date range. Your email digest covers a fixed reporting window (for example, the past 7 or 30 days). The dashboard may default to a different period. - Locate the date range selector at the top of the Overview page. - Set the start and end dates to match the period covered in your email report. - The metrics will update to reflect that specific window, and you should see numbers consistent with your email. 🗝️ Step 4: Review Keywords and Pages for Deeper Detail If you want to drill further into the specific queries or pages driving your LLM visibility gains, use the additional sub-pages under Site Metrics: - Keywords — Shows which keyword-level queries are generating citations and impressions in AI-powered results. - Pages — Breaks down performance by individual page, so you can see which content is being cited most. - Site Events — Logs notable changes or milestones that may correlate with visibility spikes mentioned in your email. To access any of these, click Site Metrics in the left sidebar, select your site, and then choose the relevant sub-page from the navigation. 💡 Tips for Keeping Email and Dashboard in Sync - Check your email report date: The header of your LLM Visibility email will state the exact reporting period. Use this to set your dashboard date range. - Bookmark your site's Overview page: Going directly to Site Metrics → [Your Site] → Overview saves time and ensures you are always looking at the right property. - Use the correct site: If you manage multiple domains, confirm the correct site is selected in the Site Metrics list before reviewing data. 🛠️ Still Not Seeing the Right Numbers? If you have matched the date range and navigated to the correct site but the dashboard still does not reflect the metrics from your email, there may be a data sync delay or a configuration issue worth investigating. If you need further assistance, open the chat widget in the bottom-right corner of the platform and type human teammate to be instantly connected with a member of our team.

AI Visibility: Why the Setup Date and the First Analysis Date Differ

Two different dates An AI Visibility project has two dates, and they are not the same thing. - The tracking setup date is when the project was created and tracking was turned on. - The first analysis date is when the first analysis actually finished running. A project can be set up months before its first analysis completes. For example, a project whose tracking was set up in January 2026 had its first completed analysis on July 2, 2026, and showed nothing recorded for June. That gap is expected and does not mean the project was inactive. Where to see your projects Open AI Visibility in the left sidebar. That view lists the projects that are currently active. To stop a project from being tracked, open the three-dot menu on the project and choose deactivate. A deactivated project no longer appears with your active projects. The exact activation date The activation date of a specific project is not something this article or the assistant can look up for you. A teammate has to check it on your account. Click the chat icon in the bottom-right corner of the platform to start a live chat with a member of our team and ask them to confirm the activation date for the project.

Where to Find AI Visibility Responses

Where AI Visibility responses appear AI Visibility responses are available in the Topics & Queries area. A support agent confirmed this location when a customer asked where to find the AI responses for a prompt. If you are reviewing a prompt analysis, the customer-facing conversation also referred to the Analyze > AI Responses view. If the response details are not visible A support agent recommended maximizing the browser window and minimizing the chat panel so the full prompt details can be displayed. Contact support If you still cannot view the response details, click the chat icon in the bottom-right corner of the platform to start a live chat with a member of our team.