{"id":7562,"date":"2025-11-05T11:06:09","date_gmt":"2025-11-05T11:06:09","guid":{"rendered":"https:\/\/vettio.com\/blog\/?p=7562"},"modified":"2025-11-05T11:06:13","modified_gmt":"2025-11-05T11:06:13","slug":"real-time-hiring-analytics","status":"publish","type":"post","link":"https:\/\/vettio.com\/blog\/real-time-hiring-analytics\/","title":{"rendered":"Real-Time Hiring Analytics: Using AI to Forecast Candidate Success Before Interviews"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"500\" src=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/05105712\/Real-Time-Hiring-Analytics-Using-AI-to-Forecast-Candidate-Success-Before-Interviews.jpg\" alt=\"hiring analytics illustrated\" class=\"wp-image-7598\" srcset=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/05105712\/Real-Time-Hiring-Analytics-Using-AI-to-Forecast-Candidate-Success-Before-Interviews.jpg 1000w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/05105712\/Real-Time-Hiring-Analytics-Using-AI-to-Forecast-Candidate-Success-Before-Interviews-300x150.jpg 300w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/05105712\/Real-Time-Hiring-Analytics-Using-AI-to-Forecast-Candidate-Success-Before-Interviews-768x384.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n\n\n\n<div class=\"wp-block-group is-nowrap is-layout-flex wp-container-core-group-is-layout-1 wp-block-group-is-layout-flex\">\n<p class=\"has-large-font-size\"><strong>TL;DR<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Real-time hiring analytics gives recruiters instant insights into candidate quality.<\/li>\n\n\n\n<li>AI studies skills, behavior and cultural fit using performance data.<\/li>\n\n\n\n<li>Predictive analytics helps firms avoid talent shortage with workforce planning.<\/li>\n\n\n\n<li>Machine learning boosts accuracy with every hire, making hiring faster and smarter.<\/li>\n<\/ul>\n<\/div>\n\n\n\n<p>Every recruiter has faced that moment where the r\u00e9sum\u00e9 looks perfect, the interview goes well and yet six months later, the \u201cideal\u201d hire quits. The reason? Decisions are often made on instinct, not insight. Traditional hiring relies on human judgment, but data shows intuition alone misses red flags.<\/p>\n\n\n\n<p>That\u2019s where real-time hiring analytics comes in. It gives recruiters a live dashboard of candidate potential before the interview even starts. This blog breaks down the working of real-time hiring analytics, why it matters, and how you can use it to predict, not just guess, who will thrive in your company.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What Is Real-Time Hiring Analytics?<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"500\" src=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140342\/RTHA1.jpg\" alt=\"Real-Time Hiring Analytics\" class=\"wp-image-7568\" srcset=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140342\/RTHA1.jpg 1000w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140342\/RTHA1-300x150.jpg 300w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140342\/RTHA1-768x384.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n\n\n\n<p>Real-time hiring analytics refers to the use of AI and predictive algorithms to process live data from job applications, assessments, and behavioral patterns to forecast how a candidate might perform. Instead of relying solely on CVs or interviews, recruiters now see insights like \u201cfit score,\u201d \u201cattrition risk,\u201d or \u201crole adaptability\u201d in real time.<\/p>\n\n\n\n<p>AI reads and interprets data. It examines text, tone, social cues, and even micro-patterns in responses. This new model pulls data from multiple sources:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Past job performance metrics<\/li>\n\n\n\n<li>Assessment test results<\/li>\n\n\n\n<li>Personality indicators from responses<\/li>\n\n\n\n<li>Engagement patterns (how quickly and thoroughly a candidate interacts)<\/li>\n\n\n\n<li>Public professional data and internal HR systems<\/li>\n<\/ul>\n\n\n\n<p>Together, these datasets feed machine learning models that forecast success probabilities and this process is called <a href=\"https:\/\/vettio.com\/blog\/workforce-forecasting-is-necessary-for-business-growth\/\" target=\"_blank\" rel=\"noreferrer noopener\">workforce forecasting<\/a>. The more the system learns, the sharper it gets at spotting hidden potential and possible dropouts.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Why Predicting Candidate Success Matters<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"500\" src=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140409\/RTHA2.jpg\" alt=\"candidate score\" class=\"wp-image-7569\" srcset=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140409\/RTHA2.jpg 1000w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140409\/RTHA2-300x150.jpg 300w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140409\/RTHA2-768x384.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n\n\n\n<p>Predicting success before interviews saves more than just time. It prevents hiring mistakes that cost real money. The U.S. Department of Labor estimates a bad hire can <a href=\"https:\/\/www.forbes.com\/sites\/falonfatemi\/2016\/09\/28\/the-true-cost-of-a-bad-hire-its-more-than-you-think\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">cost up to 30%<\/a> of the employee\u2019s first-year earnings. For mid-level roles, that\u2019s tens of thousands of dollars gone due to turnover, retraining, and morale loss.<\/p>\n\n\n\n<p>AI hiring analytics solves this by identifying high-potential candidates faster and filtering out those who might underperform or leave early. Here\u2019s why that matters:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Consistency:<\/strong> AI applies the same standards to every applicant, minimizing bias.<br><\/li>\n\n\n\n<li><strong>Speed:<\/strong> It analyzes thousands of data points in seconds, shortening hiring cycles.<br><\/li>\n\n\n\n<li><span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\"><strong>Depth:<\/strong>\u00a0It evaluates qualities beyond the r\u00e9sum\u00e9, like adaptability, problem-solving, and teamwork.<\/span><\/li>\n<\/ul>\n\n\n\n<p>AI models don\u2019t just assess skill fit. They can also flag cultural mismatches. For instance, machine learning can compare communication tone and collaboration style against company culture to assess alignment. This helps recruiters <a href=\"https:\/\/vettio.com\/blog\/how-workforce-planning-prevents-talent-shortages\/\" target=\"_blank\" rel=\"noreferrer noopener\">avoid talent shortage with workforce planning<\/a>, since hiring the right fit reduces early attrition.<\/p>\n\n\n\n<p>The result? Recruiters can focus interviews on candidates most likely to succeed long-term, not just those who \u201csound\u201d good on paper. And with integrated <a href=\"https:\/\/vettio.com\/blog\/how-to-find-the-best-workforce-planning-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\">workforce planning tools<\/a>, organizations can visualize where future skill gaps might appear, turning hiring from guesswork into strategy.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How AI Forecasts Candidate Success<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"500\" src=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140435\/RTHA3.jpg\" alt=\"AI Forecasts Candidates Success\" class=\"wp-image-7570\" srcset=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140435\/RTHA3.jpg 1000w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140435\/RTHA3-300x150.jpg 300w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140435\/RTHA3-768x384.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n\n\n\n<p>AI forecasts candidate success by combining machine learning, behavioral science, and real-time data streams. It is not just about who looks good on paper; it\u2019s about how someone will perform, adapt, and stay.<\/p>\n\n\n\n<p>To make these forecasts, AI systems analyze multiple data layers, both structured and unstructured. Structured data includes test scores, education and experience. Unstructured data includes writing tone, social behavior and assessment answers. Together, these form a candidate\u2019s \u201cdigital fingerprint\u201d of potential.<\/p>\n\n\n\n<p>So, what types of data do AI systems analyze to forecast a candidate\u2019s likelihood of success before the interview?<\/p>\n\n\n\n<p>They look at personality assessments, project outcomes, peer feedback, cognitive tests and even communication styles in emails or chat responses.<\/p>\n\n\n\n<p>Here\u2019s how it works behind the curtain:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Data Cleaning:<\/strong> AI filters incomplete or inconsistent candidate data, ensuring it only learns from reliable inputs. This addresses how AI systems handle inconsistent data without compromising accuracy.<br><\/li>\n\n\n\n<li><strong>Model Training:<\/strong> The system learns patterns from past successful hires and uses them to spot similar traits in new candidates.<br><\/li>\n\n\n\n<li><strong>Continuous Learning:<\/strong> With every new hire and outcome, it gets smarter. That\u2019s the heart of machine learning in recruitment.<br><\/li>\n\n\n\n<li><strong>Soft Skill Mapping:<\/strong> Natural language processing (NLP) models now assess tone, empathy and clarity, allowing AI to identify soft skills or cultural fit before the interview process.<\/li>\n<\/ul>\n\n\n\n<p>In advanced systems, AI can even forecast which candidates are likely to leave a company early, flagging potential flight risks. Over time, this level of foresight becomes a strategic asset, aligning hiring decisions with retention goals and overall business growth.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How Recruiters Use Real-Time Analytics in Practice<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"500\" src=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140512\/RTHA4.jpg\" alt=\"Real-Time Analytics in Practice\" class=\"wp-image-7571\" srcset=\"https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140512\/RTHA4.jpg 1000w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140512\/RTHA4-300x150.jpg 300w, https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/04140512\/RTHA4-768x384.jpg 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/figure>\n\n\n\n<p>In practice, real-time hiring analytics becomes a daily dashboard that recruiters depend on. It\u2019s a workflow upgrade.<\/p>\n\n\n\n<p>Recruiters use live dashboards to track candidate progress, interview readiness and predicted fit scores. Instead of guessing who\u2019s most promising, they get alerts like \u201c85% success likelihood based on role match and behavior data.\u201d<\/p>\n\n\n\n<p>Here\u2019s how it plays out in real-world recruiting teams:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Dynamic Strategy Adjustments:<\/strong> Recruiters can see, in real time, which sourcing channels deliver the best-performing hires, demonstrating how real-time analytics help them adjust hiring strategies on the fly.<strong><br><\/strong><\/li>\n\n\n\n<li><strong>Collaborative Insights:<\/strong> Hiring managers and recruiters use shared dashboards to compare candidates, improving communication and decision speed. This also shows how real-time hiring analytics affect collaboration between recruiters and hiring managers.<br><\/li>\n\n\n\n<li><strong>Proactive Talent Pipelining:<\/strong> Predictive analytics highlight future role gaps and rising skill shortages, allowing companies to prepare pipelines early. Combined with workforce planning tools, it keeps hiring aligned with long-term goals.<br><\/li>\n\n\n\n<li><strong>Smarter Interview Scheduling:<\/strong> AI systems sync calendars, rank interview urgency and automate reminders to improve candidate experience. This directly ties to AI-powered interview scheduling, improving engagement and reducing drop-offs.<\/li>\n<\/ol>\n\n\n\n<p>Organizations adopting these systems report faster placements and lower turnover. It\u2019s not about replacing recruiters but about upgrading them. With AI handling repetitive analysis, recruiters can finally focus on relationship-building, cultural storytelling and final decision-making.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<p>Real-time hiring analytics is changing recruitment from guesswork to guidance. Instead of asking \u201cWho looks good on paper?\u201d, companies now ask \u201cWho will perform best in reality?\u201d<\/p>\n\n\n\n<p>AI\u2019s role isn\u2019t to replace instinct but to refine it with data-backed clarity. It gives recruiters predictive visibility, helps leaders plan for future skill needs and ensures hiring decisions support business growth.<\/p>\n\n\n\n<!-- WordPress Custom HTML block: Real-Time Hiring Analytics FAQs -->\n<section class=\"rtha-faq-wrap\" role=\"region\" aria-label=\"FAQs\">\n  <style>\n    .rtha-faq-wrap{\n      width:100%;\n      background:#0b0b0b;\n      color:#ffffff;\n      padding:28px 16px;\n      box-sizing:border-box;\n      font-family:system-ui,-apple-system,Segoe UI,Roboto,Ubuntu,Cantarell,Noto Sans,Arial,sans-serif;\n    }\n    .rtha-faq{\n      width:100%;\n      margin:0 auto;\n      display:grid;\n      gap:12px;\n    }\n    .rtha-title{\n      margin:0 0 14px 0;\n      font-size:1.4rem;\n      line-height:1.2;\n      color:#ff7a00; \/* orange *\/\n      text-align:left;\n    }\n    .rtha-faq details{\n      background:#111214;\n      border:1px solid #1f1f22;\n      border-left:4px solid #ff7a00;\n      border-radius:10px;\n      transition:border-color .2s ease, background .2s ease;\n      overflow:hidden;\n    }\n    .rtha-faq details[open]{\n      border-color:#ff7a00;\n      background:#141518;\n    }\n    .rtha-faq summary{\n      cursor:pointer;\n      list-style:none;\n      padding:16px 18px;\n      position:relative;\n      font-weight:600;\n      color:#ffffff;\n      outline:none;\n    }\n    .rtha-faq summary::-webkit-details-marker{ display:none; }\n    .rtha-faq summary:focus{ box-shadow:0 0 0 3px rgba(255,122,0,.35); border-radius:8px; }\n    .rtha-faq summary .q{\n      display:flex;\n      align-items:flex-start;\n      gap:10px;\n    }\n    .rtha-faq summary .bullet{\n      width:10px;\n      height:10px;\n      border-radius:50%;\n      background:#ff7a00;\n      margin-top:6px;\n      flex:0 0 10px;\n    }\n    .rtha-faq summary .text{\n      flex:1 1 auto;\n      line-height:1.35;\n    }\n    .rtha-faq .answer{\n      padding:0 18px 18px 18px;\n      color:#e9e9e9;\n      line-height:1.6;\n    }\n    .rtha-faq .answer p{ margin:0; }\n    \/* Toggle icon *\/\n    .rtha-faq summary::after{\n      content:\"+\";\n      position:absolute;\n      right:16px;\n      top:14px;\n      font-weight:700;\n      color:#ff7a00;\n      transition:transform .2s ease;\n    }\n    .rtha-faq details[open] summary::after{\n      content:\"\u2013\";\n      transform:rotate(0deg);\n    }\n    \/* Links inside answers, if any *\/\n    .rtha-faq a{ color:#ffb37a; text-decoration:none; }\n    .rtha-faq a:hover{ text-decoration:underline; }\n    \/* Small screens *\/\n    @media (max-width:640px){\n      .rtha-title{ font-size:1.25rem; }\n      .rtha-faq summary{ padding:14px 16px; }\n      .rtha-faq .answer{ padding:0 16px 16px 16px; }\n    }\n  <\/style>\n\n  <div class=\"rtha-faq\">\n    <h3 class=\"rtha-title\">FAQs<\/h3>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">How can AI-powered interview scheduling and reminders improve candidate engagement?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>They automate the small but crucial parts of hiring such as scheduling, reminders and follow-ups. This keeps candidates informed, reduces waiting time and builds a more professional experience without extra recruiter effort.<\/p>\n      <\/div>\n    <\/details>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">How do I train my recruiting team to effectively use AI recruitment software?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>Start with basic data literacy. Train recruiters to interpret dashboards, understand predictive scores and use insights to guide their interviews rather than replace them. Most platforms offer in-app tutorials and live onboarding sessions.<\/p>\n      <\/div>\n    <\/details>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">What is the difference between AI recruiting assistants and traditional recruiting software?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>Traditional tools store data. AI recruiting assistants analyze it. They track candidate behavior, forecast success and suggest next steps. All in real time.<\/p>\n      <\/div>\n    <\/details>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">Are there any industry-specific AI recruitment tools designed for tech, healthcare or finance hiring?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>Yes. Some AI tools are tailored to niche skill sets. For instance, tech hiring platforms like Eightfold.ai and HiredScore focus on coding and digital skills while healthcare and finance systems emphasize compliance and credential verification.<\/p>\n      <\/div>\n    <\/details>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">What should I expect in terms of time savings when using AI recruitment tools?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>Most organizations see a 30 to 50 percent reduction in time to hire within the first six months. The time saved comes from automated screening, scheduling and candidate ranking.<\/p>\n      <\/div>\n    <\/details>\n\n    <details>\n      <summary>\n        <div class=\"q\">\n          <span class=\"bullet\" aria-hidden=\"true\"><\/span>\n          <span class=\"text\">Are there any AI recruiting solutions specifically designed for startups and growing companies?<\/span>\n        <\/div>\n      <\/summary>\n      <div class=\"answer\">\n        <p>Yes. Lightweight platforms like Recruitee and Breezy HR offer scalable AI-powered tools that support small teams. They provide automation, analytics and predictive scoring without enterprise-level complexity.<\/p>\n      <\/div>\n    <\/details>\n  <\/div>\n<\/section>\n\n\n\n<p><\/p>\n\n\n\n<div class=\"wp-block-buttons text-center is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-1 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-text-align-center wp-element-button\" href=\"https:\/\/vettio.com\" target=\"_blank\" rel=\"noreferrer noopener\"><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>Vettio = Less Guessing, Better Hiring<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Learn how real-time hiring analytics uses AI to forecast candidate success, improve retention and help recruiters hire smarter.<\/p>\n","protected":false},"author":5,"featured_media":7598,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_kadence_starter_templates_imported_post":false,"footnotes":""},"categories":[26],"tags":[41],"class_list":["post-7562","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-driven-recruitment","tag-smarter-hiring"],"taxonomy_info":{"category":[{"value":26,"label":"Data-Driven Recruitment"}],"post_tag":[{"value":41,"label":"Smarter Hiring"}]},"featured_image_src_large":["https:\/\/snabup-prod.s3.amazonaws.com\/blog\/wp-content\/uploads\/2025\/11\/05105712\/Real-Time-Hiring-Analytics-Using-AI-to-Forecast-Candidate-Success-Before-Interviews.jpg",800,400,false],"author_info":{"display_name":"Bisma Naeem","author_link":"https:\/\/vettio.com\/blog\/author\/bisma-naeem\/"},"comment_info":3,"category_info":[{"term_id":26,"name":"Data-Driven Recruitment","slug":"data-driven-recruitment","term_group":0,"term_taxonomy_id":26,"taxonomy":"category","description":"","parent":83,"count":22,"filter":"raw","cat_ID":26,"category_count":22,"category_description":"","cat_name":"Data-Driven Recruitment","category_nicename":"data-driven-recruitment","category_parent":83}],"tag_info":[{"term_id":41,"name":"Smarter Hiring","slug":"smarter-hiring","term_group":0,"term_taxonomy_id":41,"taxonomy":"post_tag","description":"","parent":0,"count":54,"filter":"raw"}],"_links":{"self":[{"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/posts\/7562","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/comments?post=7562"}],"version-history":[{"count":6,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/posts\/7562\/revisions"}],"predecessor-version":[{"id":7610,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/posts\/7562\/revisions\/7610"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/media\/7598"}],"wp:attachment":[{"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/media?parent=7562"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/categories?post=7562"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vettio.com\/blog\/wp-json\/wp\/v2\/tags?post=7562"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}