{"id":2544,"date":"2026-05-25T00:00:00","date_gmt":"2026-05-25T00:00:00","guid":{"rendered":"https:\/\/trackmybusiness.ai\/blog\/how-often-to-check-for-ai-brand-mentions-the-2026-frequency-guide\/"},"modified":"2026-05-25T03:23:21","modified_gmt":"2026-05-25T03:23:21","slug":"how-often-to-check-for-ai-brand-mentions-the-2026-frequency-guide","status":"publish","type":"post","link":"https:\/\/trackmybusiness.ai\/blog\/how-often-to-check-for-ai-brand-mentions-the-2026-frequency-guide\/","title":{"rendered":"How Often to Check for AI Brand Mentions: The 2026 Frequency Guide"},"content":{"rendered":"<p>47% of U.S. adults used AI to find a local business in the past month, which means nearly half of your potential customers are getting their first impression from an LLM. I understand the anxiety that comes with this shift. It&#8217;s frustrating to think that a hallucination or an outdated data point in a ChatGPT response could cost you a high-value lead before you even know they exist. If you&#8217;re wondering <strong>how often to check for ai brand mentions<\/strong> to prevent these losses, you aren&#8217;t alone. Most professionals feel they lack the time to manually query every new model, but they also can&#8217;t afford to ignore the 2 billion active users now searching via generative AI.<\/p>\n<p>I promise that by the end of this guide, you&#8217;ll have a clear, actionable schedule for monitoring your brand based on your specific business type. I&#8217;ll explain why frequency is a response to your industry&#8217;s volatility rather than a random choice. We&#8217;ll also look at how to use our tracker software and ChatGPT mention tracking to automate this process. This allows you to capture leads and protect your reputation while you focus on your core operations.<\/p>\n<div class=\"key-takeaways\">\n<h2 id=\"key-takeaways\"><a name=\"key-takeaways\"><\/a>Key Takeaways<\/h2>\n<ul>\n<li>Learn why AI citations are replacing traditional search rankings and how the &#8220;AI Volatility Index&#8221; dictates your specific monitoring needs.<\/li>\n<li>Find out exactly <strong>how often to check for ai brand mentions<\/strong> by analyzing the update cycles of the &#8220;live web&#8221; indices used by major LLMs.<\/li>\n<li>Identify the hidden risks of &#8220;Hallucination Decay&#8221; and learn how infrequent tracking allows competitors to hijack your brand\u2019s citation sources.<\/li>\n<li>Master a two-step monitoring strategy that involves mapping your primary prompt sets and identifying the sources where AI models pull their information.<\/li>\n<li>Discover how our LLM tracker software automates these processes to maintain brand visibility and ensure operational transparency.<\/li>\n<\/ul>\n<\/div>\n<div class=\"table-of-contents\" role=\"navigation\" aria-label=\"Table of Contents\">\n<h2 id=\"table-of-contents\"><a name=\"table-of-contents\"><\/a>Table of Contents<\/h2>\n<ul>\n<li><a href=\"#why-ai-brand-mentions-are-the-new-search-rankings\">Why AI Brand Mentions are the New Search Rankings<\/a><\/li>\n<li><a href=\"#determining-your-ideal-monitoring-frequency\">Determining Your Ideal Monitoring Frequency<\/a><\/li>\n<li><a href=\"#the-hidden-risks-of-infrequent-ai-monitoring\">The Hidden Risks of Infrequent AI Monitoring<\/a><\/li>\n<li><a href=\"#strategic-monitoring-how-to-check-effectively\">Strategic Monitoring: How to Check Effectively<\/a><\/li>\n<li><a href=\"#scaling-your-visibility-with-trackmybusiness\">Scaling Your Visibility with TrackMyBusiness<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"why-ai-brand-mentions-are-the-new-search-rankings\"><a name=\"why-ai-brand-mentions-are-the-new-search-rankings\"><\/a>Why AI Brand Mentions are the New Search Rankings<\/h2>\n<p>I define AI brand mentions as the specific citations, recommendations, or references your business receives within a generative response from platforms like ChatGPT, Gemini, or Perplexity. In the past, we focused on &#8220;blue links&#8221; and page-one rankings. Today, the metric for success has shifted. If an LLM doesn&#8217;t mention your brand when a user asks for a solution in your category, you simply don&#8217;t exist to that user. This is a critical component of modern <a href=\"https:\/\/en.wikipedia.org\/wiki\/Brand_management\" target=\"_blank\" rel=\"noopener\">brand management<\/a> because these mentions are the new &#8220;top spot&#8221; in search results.<\/p>\n<p>Traditional SEO tracking often fails here because it assumes a static environment. In 2026, search is dynamic. A generative answer changes based on the specific phrasing of a prompt, the user&#8217;s history, and the model&#8217;s real-time data retrieval. We&#8217;ve moved into an era of &#8220;answer-consumption&#8221; behavior. With referrals from AI platforms to third-party sites dropping by 15% recently, users are staying within the AI interface. They trust the answer provided and rarely click through to verify. If the answer is wrong or ignores you, the lead is lost instantly. This reality makes it vital to understand <strong>how often to check for ai brand mentions<\/strong> to ensure your brand remains the preferred choice.<\/p>\n<h3>The Anatomy of an AI Citation<\/h3>\n<p>Most modern LLMs use Retrieval-Augmented Generation (RAG) to pull data in real-time. This means the AI isn&#8217;t just relying on old training data; it&#8217;s actively &#8220;reading&#8221; the web to answer a prompt. I&#8217;ve categorized these into three distinct types of mentions:<\/p>\n<ul>\n<li><strong>Direct Recommendations:<\/strong> When the AI explicitly tells a user to use your service.<\/li>\n<li><strong>Comparative Listings:<\/strong> When your brand is weighed against competitors in a table or list.<\/li>\n<li><strong>Source Citations:<\/strong> The footnotes or links the AI provides to back up its claims.<\/li>\n<\/ul>\n<p>AI models weight &#8220;authority&#8221; differently than Google&#8217;s old algorithms. They prioritize consistency across multiple high-trust sources rather than just counting backlinks.<\/p>\n<h3>Why 2026 is the Tipping Point for AI Visibility<\/h3>\n<p>With over 2 billion active users on generative platforms, these tools have evolved into &#8220;Action Engines.&#8221; They don&#8217;t just find information; they help users make final decisions. 47% of U.S. adults now use AI to find local businesses, and this trend is global. Tech-forward regions like Saudi Arabia are seeing a rapid adoption of AI-first search habits, moving away from traditional engines entirely. If a hallucination suggests your business is unreliable, that error can snowball. I use our LLM tracker software to catch these inaccuracies before they settle into the model&#8217;s frequent response patterns. Knowing <strong>how often to check for ai brand mentions<\/strong> is the only way to maintain a clean digital footprint in this high-speed environment.<\/p>\n<h2 id=\"determining-your-ideal-monitoring-frequency\"><a name=\"determining-your-ideal-monitoring-frequency\"><\/a>Determining Your Ideal Monitoring Frequency<\/h2>\n<p>I believe that frequency is not a random calendar choice. It&#8217;s a response to your industry&#8217;s &#8220;AI Volatility Index.&#8221; This index measures how quickly LLMs update their information about your sector through live web indexing or training data refreshes. To decide <strong>how often to check for ai brand mentions<\/strong>, you must weigh the manual labor involved against the potential revenue from a single AI-driven lead. For many, the answer lies in balancing routine checks with &#8220;Trigger Events.&#8221; These are specific moments like a product launch, a competitor&#8217;s major PR push, or a sudden shift in regulatory requirements that demand an immediate audit of your brand&#8217;s presence in LLM outputs.<\/p>\n<p>Understanding how AI can <a href=\"https:\/\/hbr.org\/2024\/09\/how-ai-can-power-brand-management\" target=\"_blank\" rel=\"noopener\">power brand management<\/a> involves recognizing that generative search isn&#8217;t a static billboard. It&#8217;s a living conversation. I&#8217;ve broken down the optimal schedules based on business type to help you allocate your resources effectively. If you&#8217;re managing a large portfolio, using our <a href=\"https:\/\/trackmybusiness.ai\">tracker software<\/a> can help automate these checks so you don&#8217;t have to perform them manually.<\/p>\n<h3>The Daily Check: For High-Volume Consumer Brands<\/h3>\n<p>This schedule is essential for e-commerce, high-competition SaaS, and news-heavy sectors. In these industries, sentiment can shift in hours. I recommend checking daily to catch new competitor inclusions in &#8220;Best of&#8221; lists or to correct trending misinformation. If an LLM starts hallucinating a negative review or an incorrect price, you need to see it immediately to adjust your public data sources. A daily check ensures that your brand remains the primary recommendation for the millions of users querying AI platforms every morning.<\/p>\n<h3>The Weekly Check: The B2B Standard<\/h3>\n<p>For B2B companies, manufacturing firms, and professional services, a weekly rhythm is often the sweet spot. Procurement timelines are longer here. I suggest tracking citation sources and technical specification accuracy. If an AI model is misrepresenting your production capacity or your service area, a weekly check gives you enough time to update your documentation before the next major procurement cycle begins. It aligns perfectly with standard business reporting and allows for steady, incremental improvements to your AI visibility.<\/p>\n<h3>The Monthly Audit: For Niche and Local Businesses<\/h3>\n<p>If you run a specialized local service or a small boutique, a deep monthly audit is usually sufficient. <strong>How often to check for ai brand mentions<\/strong> in this context depends on your total share of voice. I focus on broad category positioning during these audits. Are you still appearing as a top choice for your city? Does the AI understand your core &#8220;About Us&#8221; information? This monthly check ensures your long-term strategy remains on track without requiring constant manual intervention, making it a sustainable choice for smaller teams.<\/p>\n<h2 id=\"the-hidden-risks-of-infrequent-ai-monitoring\"><a name=\"the-hidden-risks-of-infrequent-ai-monitoring\"><\/a>The Hidden Risks of Infrequent AI Monitoring<\/h2>\n<p>I see many businesses treat AI monitoring as a secondary task, but the cost of inaction is high. When you don&#8217;t establish a routine for <strong>how often to check for ai brand mentions<\/strong>, you&#8217;re susceptible to &#8220;Hallucination Decay.&#8221; This occurs when a small factual error in an LLM response goes uncorrected. Over time, as the model retrieves its own previous outputs or scrapes secondary sources that repeated the error, the falsehood solidifies. What began as a minor mistake about your service area or product features becomes a permanent part of the AI&#8217;s knowledge base. Correcting these errors early is much easier than trying to &#8220;un-teach&#8221; a model once the misinformation has been widely cached.<\/p>\n<p>There&#8217;s also the constant threat of &#8220;Competitor Displacement.&#8221; Generative search is a zero-sum game. If an AI model like Perplexity provides three recommendations for a specific query, and a competitor optimizes their data better than you, they will take your spot. I&#8217;ve observed that rivals often target the specific citation sources LLMs favor. Without consistent <strong>how often to check for ai brand mentions<\/strong>, you won&#8217;t notice when your brand is quietly dropped from a recommendation list until your lead volume begins to crater. This creates a &#8220;Silent Churn&#8221; where potential customers choose a competitor because the AI simply didn&#8217;t present you as an option.<\/p>\n<h3>Loss of Pipeline and Recommendation Equity<\/h3>\n<p>Being removed from an AI&#8217;s preferred citation list kills your top-of-funnel visibility instantly. Unlike traditional search where you might drop from rank one to rank three, being excluded from a generative answer often means you disappear entirely. Re-entering these recommendation loops is difficult because AI models prioritize consistency. If a model hasn&#8217;t cited you in months, it perceives you as less relevant. I use our ChatGPT mention tracking to ensure our clients maintain their &#8220;Recommendation Equity&#8221; by identifying exactly when their visibility begins to dip.<\/p>\n<h3>The Reputation Trap: Inaccurate Industry Data<\/h3>\n<p>In technical sectors like garment manufacturing, the risks are even more specific. An AI might claim a manufacturer lacks a specific ISO certification or an environmental compliance rating that they actually hold. If a procurement officer uses an AI to vet vendors, that single hallucination can lead to the loss of a multi-million dollar wholesale contract. I&#8217;ve found that outdated ERP data or old press releases often feed these errors. I recommend using our tracker software to monitor these technical specifications across all major LLMs. It&#8217;s the only way to ensure your operational reality matches the digital summary provided to your potential partners.<\/p>\n<h2 id=\"strategic-monitoring-how-to-check-effectively\"><a name=\"strategic-monitoring-how-to-check-effectively\"><\/a>Strategic Monitoring: How to Check Effectively<\/h2>\n<p>I approach brand monitoring with a four-step methodology designed to move beyond guesswork. While knowing <strong>how often to check for ai brand mentions<\/strong> is the foundation of your strategy, your actual effectiveness depends on the quality of your inputs. I start by identifying a &#8220;Primary Prompt Set.&#8221; These are the 5 to 10 high-intent questions that define your business in the eyes of a potential customer. Once I have the outputs, I map the &#8220;Citation Sources.&#8221; If an AI model like Perplexity lists your brand, I look at the &#8220;Source&#8221; tag to see if it pulled that data from your LinkedIn, a recent industry directory, or an old press release. This tells me exactly which external sites I need to influence to improve our visibility.<\/p>\n<p>I also perform &#8220;Cross-Model Testing&#8221; because ChatGPT, Gemini, and Perplexity often use different retrieval methods. A brand mentioned on one platform might be completely absent on another. Finally, I analyze for &#8220;Sentiment Drift&#8221; across different regions. For instance, the way an AI describes a brand to a user in Saudi Arabia may differ from a response generated in the United States due to local data weighting and regional regulatory disclosures. This process ensures that your monitoring is comprehensive rather than just a series of random searches. To handle this complexity at scale without spending hours on manual queries, I recommend using our <a href=\"https:\/\/trackmybusiness.ai\">LLM tracker software<\/a> to automate these multi-model comparisons.<\/p>\n<h3>Building Your AI Prompt Library<\/h3>\n<p>I focus on &#8220;intent-based&#8221; prompts that mimic real user behavior. Instead of searching for your brand name alone, I ask questions like, &#8220;Who is the most reliable garment ERP provider in Saudi Arabia?&#8221; This reveals whether the AI considers you a category leader for specific solutions. I also use &#8220;Negative Prompts&#8221; to ask who the AI recommends instead of my brand to identify which competitors are currently winning the citation battle. Prompt Engineering for Brands is a core 2026 skill that transforms simple monitoring into a competitive advantage. Determining <strong>how often to check for ai brand mentions<\/strong> using these specific prompts helps you spot shifts in your market share before they impact your bottom line.<\/p>\n<h3>Identifying and Influencing Citation Sources<\/h3>\n<p>I&#8217;ve found that AI models are increasingly transparent about their sources if you know where to look. By examining the footnotes or &#8220;Source: [Domain]&#8221; tags in a response, I can identify which third-party platforms are feeding the model&#8217;s answers. If an LLM is citing an outdated G2 profile or a neglected LinkedIn page, I prioritize refreshing those specific profiles immediately. I also &#8220;feed&#8221; the AI better data by implementing structured site data on our clients&#8217; websites. This methodology makes it easier for Retrieval-Augmented Generation (RAG) systems to scrape accurate, real-time information about your services and certifications.<\/p>\n<h2 id=\"scaling-your-visibility-with-trackmybusiness\"><a name=\"scaling-your-visibility-with-trackmybusiness\"><\/a>Scaling Your Visibility with TrackMyBusiness<\/h2>\n<p>I help you move from manual guesswork to automated precision by implementing the frequency framework we&#8217;ve discussed throughout this guide. Deciding <strong>how often to check for ai brand mentions<\/strong> is a much simpler process when you have a system that handles the heavy lifting for you. Our tracker software monitors the major LLMs to ensure your brand is represented accurately and fairly. This automation is vital because it removes the burden of manual searching. It allows you to focus on responding to the leads these AI platforms generate rather than spending your day typing prompts into a chat box.<\/p>\n<p>In the garment industry, operational transparency is a major factor in securing wholesale contracts. If an LLM cites outdated production data or incorrect certification status, it damages your credibility instantly. I designed our LLM tracker software to serve as a bridge between your actual business operations and the data AI models retrieve. By maintaining a single source of truth, you ensure that every ChatGPT mention tracking result reflects your current capabilities. This is especially important for brands operating in Saudi Arabia. Regional AI search optimization requires a specific focus on local data sources that global tools often overlook. I prioritize these regional nuances to ensure your brand remains a leader in the Middle Eastern tech landscape.<\/p>\n<h3>From Mention Tracking to Business Growth<\/h3>\n<p>I believe that knowing your AI share of voice is a strategic asset for long-term growth. When you see a spike in mentions for a specific product category, you can adjust your production and inventory planning in real-time to meet that demand. This data also informs how you manage your internal technical stack, including custom software bolt-ons and integrations. If the AI is struggling to understand a specific technical feature of your service, you can refine your structured data to clarify that point. My approach is to provide a modular tracking system that grows alongside your brand. This ensures you always have the right level of visibility as your market share expands.<\/p>\n<h3>Get Started with the AI Tracker<\/h3>\n<p>The TrackMyBusiness dashboard provides a consolidated view of your brand&#8217;s presence across all major generative search platforms. I&#8217;ve focused on professional diligence in how we gather this data, ensuring that every report is functional and direct. You can see your primary prompt sets, citation sources, and sentiment trends in one place. This transparency allows you to take proactive steps to protect your reputation and capture new opportunities before your competitors do. <a href=\"https:\/\/trackmybusiness.ai\">See how TrackMyBusiness can protect your brand mentions today<\/a> and take control of your digital narrative in the age of AI.<\/p>\n<h2 id=\"master-your-brands-generative-presence\"><a name=\"master-your-brands-generative-presence\"><\/a>Master Your Brand&#8217;s Generative Presence<\/h2>\n<p>I&#8217;ve shown that AI mentions are the primary way customers discover and vet businesses in 2026. Transitioning from traditional search to generative monitoring is a necessary shift to protect your reputation. We&#8217;ve established that frequency depends on your specific industry&#8217;s volatility; it doesn&#8217;t matter if you require daily checks for consumer goods or weekly audits for B2B contracts. Determining <strong>how often to check for ai brand mentions<\/strong> is the first step toward preventing the &#8220;Silent Churn&#8221; caused by hallucinations and competitor displacement.<\/p>\n<p>My tracker software offers a specialized solution for garment and decoration industry workflows. It provides cloud-based transparency across all production modules. This ensures the data LLMs cite is always accurate and current. This first-of-its-kind ChatGPT and LLM mention tracking system allows you to maintain control over your digital narrative without the burden of manual searches. I&#8217;m confident that these tools will help you capture more leads while maintaining the trust of your audience. You have the methodology to succeed; now you just need the right system to scale it.<\/p>\n<p><a href=\"https:\/\/trackmybusiness.ai\">Start tracking your AI brand mentions with TrackMyBusiness<\/a><\/p>\n<h2 id=\"frequently-asked-questions\"><a name=\"frequently-asked-questions\"><\/a>Frequently Asked Questions<\/h2>\n<h3>How often should a small business check for AI brand mentions?<\/h3>\n<p>I recommend that most small or niche businesses perform a deep audit once per month. This frequency allows you to spot long-term shifts in your category positioning without requiring daily manual labor. If you operate in a high-competition sector, you might need to increase this to a weekly rhythm to stay ahead of competitor displacement. Understanding <strong>how often to check for ai brand mentions<\/strong> depends on how quickly your local market data changes.<\/p>\n<h3>Is there a free tool to track mentions in ChatGPT?<\/h3>\n<p>There is currently no automated free tool that provides comprehensive tracking across ChatGPT or other major LLMs. You can perform manual searches by typing prompts into the interface, but this is time-consuming and difficult to scale. Most professional teams use our specialized tracker software to automate this process. This ensures you receive consistent data without the need for manual daily queries.<\/p>\n<h3>Can I stop an AI from mentioning my brand incorrectly?<\/h3>\n<p>You cannot directly edit an AI&#8217;s response, but you can influence the sources it uses for Retrieval-Augmented Generation. I suggest updating your high-authority profiles like LinkedIn, G2, and industry-specific directories. When you provide clean, structured data on these platforms, the AI is more likely to pull accurate information during its next web crawl. Consistency across these third-party sites is the best way to fix persistent hallucinations.<\/p>\n<h3>Does AI search visibility affect my traditional SEO rankings?<\/h3>\n<p>AI visibility and traditional SEO are distinct but connected. While a mention in ChatGPT doesn&#8217;t directly boost your Google rank, 93% of users take a verification step after receiving an AI recommendation. This usually involves a Google search for your brand. If your AI presence is strong, you&#8217;ll see an increase in branded search traffic. This indirect relationship makes it vital to coordinate your strategy across both platforms.<\/p>\n<h3>What is the difference between a brand mention and a citation in AI search?<\/h3>\n<p>A brand mention is simply your name appearing within the AI&#8217;s conversational text. A citation is the specific footnote or link that the AI provides to prove where it gathered its information. Citations are more valuable because they provide a direct path for the user to visit your website. I focus on tracking both to ensure your brand isn&#8217;t just being discussed, but is also being properly credited as a source.<\/p>\n<h3>How do I know which AI search engine is most important for my brand?<\/h3>\n<p>I determine importance by looking at your target audience&#8217;s intent. Perplexity is often the leader for technical or research-heavy queries, while ChatGPT is the primary choice for general discovery and local business searches. I suggest testing your primary prompt set across all major models to see where you currently have the highest share of voice. Our LLM tracker software simplifies this by aggregating data from multiple models into one view.<\/p>\n<h3>Can TrackMyBusiness monitor mentions in multiple languages, like Arabic?<\/h3>\n<p>Yes, our LLM tracker software is fully capable of monitoring mentions in multiple languages, including Arabic. This is a critical feature for businesses operating in regions like Saudi Arabia where users search in both English and Arabic. I&#8217;ve designed the system to capture regional nuances so you can maintain a consistent brand image across different linguistic markets. This helps you stay relevant to a global audience.<\/p>\n<h3>What should I do if a competitor is mentioned more often than me by AI?<\/h3>\n<p>If you find a competitor winning the citation battle, I recommend auditing the sources the AI is citing for them. You&#8217;ll often find they have more recent press releases or better-optimized directory listings. Once you identify their advantage, you can update your own digital footprint to meet those same criteria. Knowing <strong>how often to check for ai brand mentions<\/strong> allows you to spot these competitive gaps before they result in a significant loss of market share.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>47% of U.S. adults used AI to find a local business in the past month, which means nearly half of your potential customers are getting their first&#8230;<\/p>\n<p class=\"read-more-wrapper\"><a href=\"https:\/\/trackmybusiness.ai\/blog\/how-often-to-check-for-ai-brand-mentions-the-2026-frequency-guide\/\" class=\"read-more\">Read More \u2192<\/a><\/p>","protected":false},"author":1,"featured_media":2543,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[440],"tags":[431,172,33,217,44,38,210],"class_list":["post-2544","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-ai-brand-mentions","tag-ai-marketing","tag-brand-monitoring","tag-chatgpt","tag-generative-ai","tag-reputation-management","tag-seo"],"_links":{"self":[{"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/posts\/2544","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/comments?post=2544"}],"version-history":[{"count":1,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/posts\/2544\/revisions"}],"predecessor-version":[{"id":2546,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/posts\/2544\/revisions\/2546"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/media\/2543"}],"wp:attachment":[{"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/media?parent=2544"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/categories?post=2544"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/trackmybusiness.ai\/blog\/wp-json\/wp\/v2\/tags?post=2544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}