{"id":8351,"date":"2026-01-13T13:08:13","date_gmt":"2026-01-13T13:08:13","guid":{"rendered":"https:\/\/www.searchviu.com\/?p=8351"},"modified":"2026-01-16T10:27:22","modified_gmt":"2026-01-16T10:27:22","slug":"the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical","status":"publish","type":"post","link":"https:\/\/www.searchviu.com\/en\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/","title":{"rendered":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"8351\" class=\"elementor elementor-8351\" data-elementor-post-type=\"post\">\n\t\t\t\t<div class=\"elementor-element elementor-element-110e8d7e e-flex e-con-boxed e-con e-parent\" data-id=\"110e8d7e\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;ekit_has_onepagescroll_dot&quot;:&quot;yes&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1f9b637 elementor-widget elementor-widget-html\" data-id=\"1f9b637\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;ekit_we_effect_on&quot;:&quot;none&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t\t <style>\n\n        .container {\n            max-width: 800px;\n            margin: 0 auto;\n            padding: 40px 20px;\n            background: #FFFFFF;\n            box-shadow: 0 2px 10px rgba(19, 26, 45, 0.1);\n        }\n\n        h1 {\n            font-size: 2.5em;\n            color: #131A2D;\n            margin-bottom: 20px;\n            line-height: 1.2;\n            font-weight: 700;\n        }\n        \n        .subtitle {\n            font-size: 1.25em;\n            color: #414141;\n            margin: 30px 0;\n            font-weight: 500;\n        }\n        \n        .meta {\n            color: #414141;\n            font-size: 0.95em;\n            font-style: italic;\n            margin-top: 20px;\n        }\n        \n        article {\n            padding: 0;\n        }\n        \n        h2 {\n            font-size: 1.8em;\n            color: #131A2D;\n            margin: 50px 0 25px 0;\n            padding-bottom: 10px;\n            border-bottom: 2px solid #F4F4F4;\n            font-weight: 700;\n        }\n        \n        h3 {\n            font-size: 1.3em;\n            color: #414141;\n            margin: 35px 0 20px 0;\n            font-weight: 600;\n        }\n        \n        p {\n            margin-bottom: 20px;\n            font-size: 1.05em;\n        }\n        \n        .critical-box {\n            background: #F4F4F4;\n            border-left: 4px solid #FFE62A;\n            padding: 25px;\n            margin: 30px 0;\n            border-radius: 4px;\n        }\n        \n        .critical-box h3 {\n            margin-top: 0;\n            color: #131A2D;\n            font-weight: 700;\n        }\n        \n        .critical-box p {\n            color: #131A2D;\n        }\n        \n        .callout {\n            background: #F4F4F4;\n            border-left: 4px solid #FFE62A;\n            padding: 20px 25px;\n            margin: 30px 0;\n        }\n        \n        .callout-title {\n            font-weight: 700;\n            color: #131A2D;\n            margin-bottom: 10px;\n            font-size: 1.1em;\n        }\n        \n        .callout p {\n            color: #131A2D;\n        }\n        \n        .stats-comparison {\n            display: grid;\n            grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n            gap: 20px;\n            margin: 30px 0;\n        }\n        \n        .stat-card {\n            background: #FFFFFF;\n            border: 2px solid #F4F4F4;\n            padding: 25px;\n            border-radius: 8px;\n            text-align: center;\n            position: relative;\n        }\n        \n        .stat-card.real-usage {\n            border-color: #0B9D96;\n            background: #F4F4F4;\n        }\n        \n        .stat-card.dataset {\n            border-color: #467487;\n            background: #F4F4F4;\n        }\n        \n        .stat-number {\n            font-size: 2.5em;\n            font-weight: 700;\n            display: block;\n            margin-bottom: 10px;\n            color: #131A2D;\n        }\n        \n        .stat-label {\n            font-size: 0.9em;\n            color: #414141;\n            font-weight: 600;\n        }\n        \n        .stat-sublabel {\n            font-size: 0.85em;\n            color: #414141;\n            margin-top: 5px;\n        }\n        \n        .stat-box {\n            background: linear-gradient(135deg, #467487 0%, #0B9D96 100%);\n            color: #FFFFFF;\n            padding: 30px;\n            border-radius: 8px;\n            margin: 35px 0;\n            text-align: center;\n        }\n        \n        .stat-box .stat-number {\n            font-size: 3em;\n            font-weight: 700;\n            display: block;\n            margin-bottom: 10px;\n            color: #FFFFFF;\n        }\n        \n        .stat-box .stat-label {\n            font-size: 1.1em;\n            opacity: 0.95;\n            color: #FFFFFF;\n        }\n        \n        .coverage-visual {\n            background: #f8f9fa;\n            padding: 30px;\n            border-radius: 8px;\n            margin: 30px 0;\n        }\n        \n        .coverage-label {\n            text-align: center;\n            color: #414141;\n            margin-top: 10px;\n            font-size: 0.95em;\n        }\n        \n        .key-point {\n            background: #F4F4F4;\n            border-left: 4px solid #0B9D96;\n            padding: 20px 25px;\n            margin: 25px 0;\n        }\n        \n        .key-point-title {\n            font-weight: 700;\n            color: #131A2D;\n            margin-bottom: 10px;\n        }\n        \n        .key-point p {\n            color: #131A2D;\n        }\n        \n        ul, ol {\n            margin: 20px 0 20px 30px;\n        }\n        \n        li {\n            margin-bottom: 12px;\n            padding-left: 5px;\n            color: #414141;\n        }\n        \n        strong {\n            color: #131A2D;\n            font-weight: 600;\n        }\n        \n        .warning-box {\n            background: #F4F4F4;\n            border-left: 4px solid #FFE62A;\n            padding: 20px 25px;\n            margin: 30px 0;\n            border-radius: 4px;\n        }\n        \n        .warning-box strong,\n        .warning-title {\n            color: #131A2D;\n            font-weight: 700;\n        }\n        \n        .warning-box p {\n            color: #131A2D;\n        }\n        \n       \n        \n        a:hover {\n            color: #467487;\n            border-bottom-color: #467487;\n        }\n        \n        .reference {\n            font-size: 0.9em;\n            color: #414141;\n            margin-top: 5px;\n        }\n        \n        .reality-check {\n            background: #131A2D;\n            color: #FFFFFF;\n            padding: 30px;\n            border-radius: 8px;\n            margin: 40px 0;\n        }\n        \n        .reality-check h3 {\n            color: #FFFFFF;\n            margin-top: 0;\n            font-weight: 700;\n        }\n        \n        .reality-check p,\n        .reality-check li {\n            color: #FFFFFF;\n        }\n        \n        .reality-check strong {\n            color: #FFE62A;\n        }\n        \n        .comparison-table {\n            width: 100%;\n            border-collapse: collapse;\n            margin: 30px 0;\n            font-size: 0.95em;\n        }\n        \n        .comparison-table th {\n            background: #131A2D;\n            color: #FFFFFF;\n            padding: 15px;\n            text-align: left;\n            font-weight: 600;\n        }\n        \n        .comparison-table td {\n            padding: 15px;\n            border-bottom: 1px solid #F4F4F4;\n            color: #414141;\n        }\n        \n        .comparison-table tr:nth-child(even) {\n            background: #F4F4F4;\n        }\n        \n        .negative {\n            color: #131A2D;\n            font-weight: 700;\n        }\n        \n        .positive {\n            color: #0B9D96;\n            font-weight: 700;\n        }\n        \n        \n        blockquote {\n            border-left: 4px solid #0B9D96;\n            padding-left: 20px;\n            margin: 30px 0;\n            font-style: italic;\n            color: #414141;\n            font-size: 1.15em;\n        }\n        \n        .quote {\n            background: #F4F4F4;\n            border-left: 4px solid #467487;\n            padding: 25px 30px;\n            margin: 35px 0;\n            font-style: italic;\n            font-size: 1.15em;\n            color: #414141;\n        }\n        \n        .quote-author {\n            font-style: normal;\n            font-weight: 600;\n            color: #467487;\n            margin-top: 10px;\n            font-size: 0.9em;\n        }\n        \n        .section-intro {\n            font-size: 1.1em;\n            color: #414141;\n            margin-bottom: 25px;\n        }\n        \n        .action-box {\n            background: #F0FFFE;\n            border: 2px solid #0B9D96;\n            border-radius: 8px;\n            padding: 25px;\n            margin: 30px 0;\n        }\n        \n        .action-box h4 {\n            color: #131A2D;\n            margin-bottom: 15px;\n            font-size: 1.2em;\n            font-weight: 700;\n        }\n        \n        .action-box ul {\n            margin-left: 20px;\n        }\n        \n        .timeline {\n            position: relative;\n            padding: 20px 0;\n            margin: 40px 0;\n        }\n        \n        .timeline-item {\n            position: relative;\n            padding-left: 40px;\n            margin-bottom: 30px;\n        }\n        \n        .timeline-item:before {\n            content: '';\n            position: absolute;\n            left: 8px;\n            top: 8px;\n            width: 16px;\n            height: 16px;\n            border-radius: 50%;\n            background: #0B9D96;\n        }\n        \n        .timeline-item:after {\n            content: '';\n            position: absolute;\n            left: 15px;\n            top: 24px;\n            width: 2px;\n            height: calc(100% + 6px);\n            background: #F4F4F4;\n        }\n        \n        .timeline-item:last-child:after {\n            display: none;\n        }\n        \n        .timeline-time {\n            font-weight: 700;\n            color: #0B9D96;\n            margin-bottom: 5px;\n        }\n        \n        .comparison {\n            display: grid;\n            grid-template-columns: 1fr 1fr;\n            gap: 20px;\n            margin: 30px 0;\n        }\n        \n        .comparison-item {\n            background: #F4F4F4;\n            padding: 20px;\n            border-radius: 5px;\n        }\n        \n        .comparison-item.bad {\n            border-top: 3px solid #FFE62A;\n        }\n        \n        .comparison-item.good {\n            border-top: 3px solid #0B9D96;\n        }\n        \n        .comparison-title {\n            font-weight: 700;\n            margin-bottom: 15px;\n            font-size: 1.1em;\n        }\n        \n        .comparison-item.bad .comparison-title {\n            color: #131A2D;\n        }\n        \n        .comparison-item.good .comparison-title {\n            color: #0B9D96;\n        }\n        \n        .conclusion {\n            background: #F4F4F4;\n            padding: 30px;\n            margin-top: 50px;\n            border-radius: 8px;\n            border-top: 4px solid #0B9D96;\n        }\n        \n        .conclusion h2 {\n            border: none;\n            margin-top: 0;\n            color: #131A2D;\n        }\n        \n        .author-note {\n            background: #FFFFFF;\n            border: 1px solid #F4F4F4;\n            padding: 20px;\n            margin-top: 40px;\n            border-radius: 5px;\n            font-size: 0.95em;\n            color: #414141;\n        }\n        \n        .lead {\n            font-size: 1.25em;\n            color: #414141;\n            margin: 30px 0;\n            padding: 25px;\n            background: #F4F4F4;\n            border-left: 4px solid #0B9D96;\n            font-weight: 500;\n        }\n\n    <\/style>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-671161b elementor-widget elementor-widget-text-editor\" data-id=\"671161b\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;ekit_we_effect_on&quot;:&quot;none&quot;}\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<div class=\"lead\">Datasets of &#8220;real AI prompts&#8221; are being marketed to businesses as the ultimate insight into consumer behavior. But here&#8217;s the uncomfortable truth: these datasets may tell you more about who trades privacy for free services than about your actual customers.<\/div>\n<h2>The Scale Problem: A Drop in the Ocean<\/h2>\nLet&#8217;s start with some context. WildChat, the largest publicly available dataset of real AI conversations, contains 4.8 million prompts collected over approximately 15 months. Sounds impressive, right?\n\nNow compare that to the scale of actual usage. ChatGPT processes over 1 billion queries <em>per day<\/em>. During those same 15 months, ChatGPT handled an estimated 450 billion queries. WildChat captured 0.001% of them.\n<div class=\"stats-comparison\">\n<div class=\"stat-card real-usage\">\n\n<span class=\"stat-number\">~450B<\/span>\n<span class=\"stat-label\">ChatGPT Queries in 15 Months<\/span>\n<p class=\"stat-sublabel\">Estimated actual usage<\/p>\n\n<\/div>\n<div class=\"stat-card dataset\">\n\n<span class=\"stat-number\">4.8M<\/span>\n<span class=\"stat-label\">WildChat Dataset<\/span>\n<p class=\"stat-sublabel\">Same 15 months (0.001% captured)<\/p>\n\n<\/div>\n<\/div>\nNow do the math: ChatGPT alone processes over <strong>1 billion queries per day<\/strong>. Over the same 15-month period that WildChat collected data, ChatGPT likely processed approximately <strong>450 billion queries<\/strong>. That means WildChat captured roughly <strong>0.001%<\/strong> of actual ChatGPT usage during that time\u2014and that&#8217;s ignoring Claude, Gemini, Perplexity, and dozens of other AI platforms.\n<p style=\"font-size: 1.15em; color: #467487; font-weight: 600; margin: 30px 0;\">Put another way: The dataset represents about 1 in every 100,000 ChatGPT conversations from that period.<\/p>\n<p class=\"reference\">Want to explore the dataset yourself? Check out <a href=\"https:\/\/wildvisualizer.com\/\" target=\"_blank\" rel=\"noopener\">WildVisualizer<\/a>, an interactive tool for browsing real prompts from the WildChat dataset.<\/p>\n\n<div class=\"critical-box\">\n<h3>\u26a0 Reality Check<\/h3>\nYou wouldn&#8217;t make business decisions based on 0.001% of your market activity\u2014especially when that tiny sample is self-selected from people willing to trade data for free access. So why would you do it with AI prompt data?\n\n<\/div>\n<h2>The Self-Selection Bias Problem<\/h2>\nHere&#8217;s how WildChat collected its data: researchers offered free access to ChatGPT through a Hugging Face-hosted chatbot. In exchange, users had to explicitly consent to having their conversations collected and shared for research.\n<p class=\"reference\">Source: <a href=\"https:\/\/arxiv.org\/abs\/2405.01470\" target=\"_blank\" rel=\"noopener\">WildChat: 1M ChatGPT Interaction Logs in the Wild<\/a><\/p>\n\n<h3>Who Actually Uses This?<\/h3>\nThink about the type of person who:\n<ul>\n \t<li>Knows what Hugging Face is (already eliminates 99% of consumers)<\/li>\n \t<li>Doesn&#8217;t have a ChatGPT Plus subscription ($20\/month)<\/li>\n \t<li>Is willing to trade privacy for free access<\/li>\n \t<li>Feels comfortable with their data being collected for research<\/li>\n<\/ul>\n<h3>The Behavior Change Effect<\/h3>\nResearch shows that people behave differently when they know they&#8217;re being observed\u2014a phenomenon called the Hawthorne Effect. Users aware their prompts will be shared for research may:\n<ul>\n \t<li><strong>Self-censor:<\/strong> Avoid sensitive topics (personal health, finances, relationships)<\/li>\n \t<li><strong>Experiment more:<\/strong> Test edge cases rather than solve real problems<\/li>\n \t<li><strong>Perform for the dataset:<\/strong> Write &#8220;interesting&#8221; prompts rather than practical ones<\/li>\n \t<li><strong>Avoid proprietary information:<\/strong> Can&#8217;t use it for actual work projects<\/li>\n<\/ul>\n<p class=\"reference\">Source: <a href=\"https:\/\/maria-antoniak.github.io\/resources\/2024_colm_trust_no_bot.pdf\" target=\"_blank\" rel=\"noopener\">Trust No Bot: Privacy Concerns in WildChat Dataset<\/a><\/p>\n\n<h2>What&#8217;s Actually Missing: Normal Consumer Behavior<\/h2>\n<div class=\"reality-check\">\n<h3>The Real Gap in the Data<\/h3>\nHere&#8217;s what&#8217;s systematically absent from datasets collected via Hugging Face and similar platforms:\n<ul>\n \t<li><strong>Everyday product research:<\/strong> &#8220;Best wireless headphones under $100&#8221;<\/li>\n \t<li><strong>Shopping comparisons:<\/strong> &#8220;iPhone 15 vs Samsung S24 which should I buy&#8221;<\/li>\n \t<li><strong>Local service searches:<\/strong> &#8220;Find a plumber near me with good reviews&#8221;<\/li>\n \t<li><strong>Travel planning:<\/strong> &#8220;Week-long Italy itinerary with kids under $5000&#8221;<\/li>\n \t<li><strong>Recipe and cooking help:<\/strong> &#8220;How to make pasta carbonara authentic recipe&#8221;<\/li>\n \t<li><strong>Home and DIY:<\/strong> &#8220;How to fix leaky faucet step by step&#8221;<\/li>\n \t<li><strong>Health questions:<\/strong> &#8220;Symptoms of vitamin D deficiency&#8221;<\/li>\n \t<li><strong>Financial planning:<\/strong> &#8220;Should I pay off student loans or invest&#8221;<\/li>\n<\/ul>\n<p style=\"margin-top: 20px;\">Why are these missing? Because typical consumers doing everyday searches aren&#8217;t tech-savvy enough to know what Hugging Face is, let alone sign up for a research chatbot. They&#8217;re using ChatGPT directly, Claude via their phone, or AI features built into Google and Bing.<\/p>\n<p style=\"margin-top: 15px;\"><strong>Someone comfortable using Hugging Face for free ChatGPT access is fundamentally different from someone asking AI to help them choose a dishwasher.<\/strong><\/p>\n\n<\/div>\n<h2>Language and Geographic Bias<\/h2>\nWildChat proudly advertises &#8220;68+ languages detected&#8221; as evidence of diversity. But let&#8217;s look at the actual distribution:\n<table class=\"comparison-table\">\n<thead>\n<tr>\n<th>Language<\/th>\n<th>Percentage in Dataset<\/th>\n<th>Global Internet Users<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>English<\/td>\n<td class=\"negative\">53%<\/td>\n<td>25.9%<\/td>\n<\/tr>\n<tr>\n<td>Chinese<\/td>\n<td class=\"negative\">13%<\/td>\n<td>19.4%<\/td>\n<\/tr>\n<tr>\n<td>Russian<\/td>\n<td class=\"positive\">12%<\/td>\n<td>2.5%<\/td>\n<\/tr>\n<tr>\n<td>Spanish<\/td>\n<td class=\"negative\">~3%<\/td>\n<td>7.9%<\/td>\n<\/tr>\n<tr>\n<td>Arabic<\/td>\n<td class=\"negative\">~2%<\/td>\n<td>5.2%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p class=\"reference\">Dataset source: <a href=\"https:\/\/arxiv.org\/html\/2405.01470v1\" target=\"_blank\" rel=\"noopener\">WildChat Research Paper<\/a> | Internet users: <a href=\"https:\/\/www.internetworldstats.com\/stats7.htm\" target=\"_blank\" rel=\"noopener\">Internet World Stats<\/a><\/p>\nEnglish is massively overrepresented (2x), while Spanish, Arabic, Hindi, and Portuguese speakers\u2014representing billions of people\u2014are dramatically underrepresented. If you&#8217;re marketing globally, this dataset doesn&#8217;t reflect your audience.\n<h2>The Alternative: Browser Extension Data<\/h2>\nSome companies claim to have more representative data collected through browser extensions and proxy services. Users install extensions for features like VPNs or SEO tools, and these extensions passively capture AI conversations.\n<div class=\"critical-box\">\n<h3>Sounds Better, Right? Not So Fast.<\/h3>\nRecent investigations revealed companies selling this data have questionable consent practices. Users may not understand their AI conversations are being harvested and sold to hedge funds and business intelligence firms.\n<p class=\"reference\">Source: <a href=\"https:\/\/www.theregister.com\/2025\/09\/29\/profound_browser_extension_privacy_concern\/\" target=\"_blank\" rel=\"noopener\">Investigation: Your AI Conversations Are a Treasure Trove for Marketers<\/a><\/p>\n\n<\/div>\nEven if ethically collected, browser extension users are still a biased sample:\n<ul>\n \t<li>Skew younger and more tech-savvy<\/li>\n \t<li>Often using free tools (again, price-sensitive)<\/li>\n \t<li>Less likely to be in security-conscious corporate environments<\/li>\n \t<li>May include more casual or personal use cases vs. professional<\/li>\n<\/ul>\n<h2>So What Should Marketers Do?<\/h2>\nThis isn&#8217;t an argument to ignore prompt data entirely. It&#8217;s a call for realistic expectations and proper skepticism.\n<h3>\u2713 Good Uses of Prompt Data<\/h3>\n<ul>\n \t<li><strong>Hypothesis generation:<\/strong> Discover questions or angles you hadn&#8217;t considered<\/li>\n \t<li><strong>Language patterns:<\/strong> See how people naturally phrase certain types of queries<\/li>\n \t<li><strong>Content brainstorming:<\/strong> Identify potential topic areas to explore further<\/li>\n \t<li><strong>Supplement other research:<\/strong> Use as one data point among many<\/li>\n<\/ul>\n<h3>\u2717 Bad Uses of Prompt Data<\/h3>\n<ul>\n \t<li><strong>Strategic decisions:<\/strong> Basing product roadmap on 0.01% of biased sample<\/li>\n \t<li><strong>Assumption of representativeness:<\/strong> Treating it as &#8220;what people actually do&#8221;<\/li>\n \t<li><strong>Competitive intelligence:<\/strong> Competitors&#8217; real users aren&#8217;t in these datasets<\/li>\n \t<li><strong>Replacing proper market research:<\/strong> It&#8217;s no substitute for surveying your actual audience<\/li>\n<\/ul>\n<div class=\"reality-check\">\n<h3>The Bottom Line<\/h3>\nPublic AI prompt datasets are like studying restaurant preferences by surveying only people who use Groupon at Denny&#8217;s at 2am. You&#8217;ll learn <em>something<\/em>, but extrapolating those insights to represent all dining behavior would be absurd.\n<p style=\"margin-top: 20px;\">The same applies here. These datasets reveal behavior patterns of a specific, self-selected, tech-savvy, price-sensitive subset of AI users\u2014not your actual market.<\/p>\n\n<\/div>\n<h2>The Uncomfortable Truth: Only OpenAI Knows<\/h2>\nHere&#8217;s the reality that nobody in the marketing data business wants to acknowledge: <strong>only OpenAI, Anthropic, Google, and the other AI platform providers know what real, representative AI usage looks like.<\/strong>\n\nThey have:\n<ul>\n \t<li>100% of their users&#8217; conversations (not 0.01%)<\/li>\n \t<li>Complete demographic and behavioral data<\/li>\n \t<li>Enterprise usage patterns alongside consumer behavior<\/li>\n \t<li>Paid subscribers alongside free users<\/li>\n \t<li>Global representation without self-selection bias<\/li>\n<\/ul>\nAnd they&#8217;re not sharing it. For good reason\u2014user privacy, competitive advantage, and commercial sensitivity all prevent the release of truly representative data at scale.\n<div class=\"critical-box\">\n<h3>The Data Monopoly<\/h3>\nAs long as AI companies keep their usage data proprietary (which they should, for privacy reasons), we will never have an exact, unbiased picture of how people actually use AI at scale. Any public dataset will be, by definition, a limited and biased sample.\n<p style=\"margin-top: 15px;\">This means marketers must treat <em>all<\/em> publicly available prompt data as directional insights at best\u2014not as ground truth about consumer behavior.<\/p>\n\n<\/div>\n<h2>A Better Proxy: Search Intent Data<\/h2>\nHere&#8217;s something most marketers miss while chasing AI prompt data: <strong>user intent doesn&#8217;t disappear just because the research method changes.<\/strong>\n\nPeople who previously searched Google for &#8220;how to fix a leaking faucet&#8221; are now asking ChatGPT the same question. The underlying need (fixing their faucet) hasn&#8217;t changed. Only the interface has.\n<h3>Why Google Search Volume Still Matters<\/h3>\nWhile AI is changing <em>how<\/em> people find information, it&#8217;s not fundamentally changing <em>what<\/em> information they need. Google search data can give you:\n<ul>\n \t<li><strong>Truly representative scale:<\/strong> Billions of searches with real demographic diversity<\/li>\n \t<li><strong>Intent signals:<\/strong> What problems are people trying to solve?<\/li>\n \t<li><strong>Trend data:<\/strong> Which topics are growing or declining in interest?<\/li>\n \t<li><strong>Seasonality patterns:<\/strong> When do people care about specific topics?<\/li>\n \t<li><strong>Geographic distribution:<\/strong> Where is demand concentrated?<\/li>\n<\/ul>\nThe key insight: <strong>AI doesn&#8217;t eliminate intent\u2014it just changes the expression of it.<\/strong> Someone researching &#8220;best CRM for small business&#8221; has the same underlying need whether they Google it or ask Claude about it.\n<div class=\"reality-check\">\n<h3>The Hybrid Approach<\/h3>\nSmart marketers will combine multiple data sources:\n<ul>\n \t<li><strong>Google search volume:<\/strong> For scale and representativeness of intent<\/li>\n \t<li><strong>Prompt datasets:<\/strong> For understanding conversational phrasing and multi-turn behavior<\/li>\n \t<li><strong>Your own customer research:<\/strong> For validation with your actual audience<\/li>\n \t<li><strong>Behavioral analytics:<\/strong> For measuring what actually drives results<\/li>\n<\/ul>\n<p style=\"margin-top: 20px;\">No single data source tells the complete story. But search volume data\u2014with its scale, diversity, and lack of self-selection bias\u2014often provides a more reliable foundation for understanding market demand than small, biased samples of AI conversations.<\/p>\n\n<\/div>\n\n<h2>Final Thoughts<\/h2>\nPublic AI prompt datasets are fascinating research artifacts that reveal genuine patterns in how certain types of users interact with AI systems. But they suffer from three fundamental limitations:\n<ol>\n \t<li><strong>Scale:<\/strong> They represent a tiny fraction of actual AI usage<\/li>\n \t<li><strong>Selection bias:<\/strong> Only certain types of users contribute to public datasets<\/li>\n \t<li><strong>Data monopoly:<\/strong> Only AI companies themselves have truly representative data, and they&#8217;re not sharing it<\/li>\n<\/ol>\nUntil OpenAI, Anthropic, Google, and others release representative samples of their usage data (which seems unlikely for privacy and competitive reasons), marketers must accept that we simply don&#8217;t have a complete picture of AI usage at scale.\n\n<strong>But here&#8217;s the good news:<\/strong> You probably don&#8217;t need one. The fundamentals of good marketing haven&#8217;t change!\n\n<div class=\"reality-check\">\n<h3>Marketing Fundamentals Still Apply\n<\/h3>\nAI changes how we work \u2014 not what good marketing is built on. Successful marketing is still rooted in the same core principles:\n<ul>\n \t<li><strong>Understand your specific audience<\/strong> (not all AI users)<\/li>\n \t<li><strong>Solve real problems<\/strong> (which show up in search data, customer feedback, and surveys)<\/li>\n \t<li><strong>Test and measure what works for your business<\/strong> <\/li>\n \t<li><strong>Use multiple data sources to triangulate insights<\/strong> <\/li>\n<\/ul>\n<p style=\"margin-top: 20px;\">Traditional search intent data, despite being &#8220;old school,&#8221; often provides more reliable signals about market demand than tiny samples of AI conversations from self-selected users.<\/p>\n\n<\/div>\n\n<h2>Resources &amp; Further Reading<\/h2>\n<div style=\"background: #f8f9fa; padding: 25px; border-radius: 8px; margin-top: 30px;\">\n<h3 style=\"margin-top: 0;\">Essential Links:<\/h3>\n<ul>\n \t<li><a href=\"https:\/\/wildvisualizer.com\/\" target=\"_blank\" rel=\"noopener\">WildVisualizer &#8211; Interactive Prompt Explorer<\/a> (Browse the WildChat dataset yourself)<\/li>\n \t<li><a href=\"https:\/\/huggingface.co\/datasets\/allenai\/WildChat-1M\" target=\"_blank\" rel=\"noopener\">WildChat-1M Dataset on Hugging Face<\/a><\/li>\n \t<li><a href=\"https:\/\/arxiv.org\/abs\/2405.01470\" target=\"_blank\" rel=\"noopener\">WildChat: 1M ChatGPT Interaction Logs in the Wild (Research Paper)<\/a><\/li>\n \t<li><a href=\"https:\/\/maria-antoniak.github.io\/resources\/2024_colm_trust_no_bot.pdf\" target=\"_blank\" rel=\"noopener\">Trust No Bot: Privacy Concerns in WildChat Dataset<\/a><\/li>\n \t<li><a href=\"https:\/\/www.theregister.com\/2025\/09\/29\/profound_browser_extension_privacy_concern\/\" target=\"_blank\" rel=\"noopener\">Investigation: AI Conversations as Marketing Data<\/a><\/li>\n \t<li><a href=\"https:\/\/metehan.ai\/blog\/i-analyzed-1827-real-user-prompts-from-chatgpt-here-what-ive-found-agentic-search\/\" target=\"_blank\" rel=\"noopener\">Analysis: 1,827 Real ChatGPT Prompts<\/a><\/li>\n<\/ul>\n<\/div>\n<div style=\"margin-top: 50px; padding-top: 50px; border-top: 2px solid #eee;\">\n<p style=\"font-size: 1.1em; color: #666; text-align: center; font-style: italic;\">&#8220;Not everything that counts can be counted, and not everything that can be counted counts.&#8221;\n\u2014 William Bruce Cameron<\/p>\n\n<div class=\"lead\">Public AI prompt datasets can be counted. Whether they count for <em>your<\/em> business is the real question.<\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Before you base your strategy on &#8220;real user prompts,&#8221; <br \/>understand what you&#8217;re actually looking at<\/p>\n","protected":false},"author":1,"featured_media":8233,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"no","_lmt_disable":"","footnotes":""},"categories":[36],"tags":[30],"class_list":["post-8351","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-seo-data","tag-english"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring<\/title>\n<meta name=\"description\" content=\"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.searchviu.com\/en\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring\" \/>\n<meta property=\"og:description\" content=\"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.searchviu.com\/en\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/\" \/>\n<meta property=\"og:site_name\" content=\"SEO Data Warehouse And Monitoring\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-13T13:08:13+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-01-16T10:27:22+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Michael\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@searchviu\" \/>\n<meta name=\"twitter:site\" content=\"@searchviu\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Michael\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/\"},\"author\":{\"name\":\"Michael\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#\\\/schema\\\/person\\\/047e04e169af50cb1ca9d948557fa1c2\"},\"headline\":\"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical\",\"datePublished\":\"2026-01-13T13:08:13+00:00\",\"dateModified\":\"2026-01-16T10:27:22+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/\"},\"wordCount\":1691,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/searchVIU_blog-6.png\",\"keywords\":[\"english\"],\"articleSection\":[\"SEO data\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/\",\"url\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/\",\"name\":\"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/searchVIU_blog-6.png\",\"datePublished\":\"2026-01-13T13:08:13+00:00\",\"dateModified\":\"2026-01-16T10:27:22+00:00\",\"description\":\"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/searchVIU_blog-6.png\",\"contentUrl\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/searchVIU_blog-6.png\",\"width\":1200,\"height\":630},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.searchviu.com\\\/en\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#website\",\"url\":\"https:\\\/\\\/www.searchviu.com\\\/\",\"name\":\"SEO Data Warehouse And Monitoring\",\"description\":\"SEO Solutions For Teams And Agencies\",\"publisher\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.searchviu.com\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#organization\",\"name\":\"searchVIU\",\"url\":\"https:\\\/\\\/www.searchviu.com\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2023\\\/02\\\/d3babe41-searchviu-logo2x.png\",\"contentUrl\":\"https:\\\/\\\/www.searchviu.com\\\/wp-content\\\/uploads\\\/2023\\\/02\\\/d3babe41-searchviu-logo2x.png\",\"width\":340,\"height\":340,\"caption\":\"searchVIU\"},\"image\":{\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#\\\/schema\\\/logo\\\/image\\\/\"},\"sameAs\":[\"https:\\\/\\\/x.com\\\/searchviu\",\"https:\\\/\\\/www.linkedin.com\\\/company\\\/searchviu\\\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.searchviu.com\\\/#\\\/schema\\\/person\\\/047e04e169af50cb1ca9d948557fa1c2\",\"name\":\"Michael\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g\",\"caption\":\"Michael\"},\"sameAs\":[\"https:\\\/\\\/www.searchviu.com\"],\"url\":\"https:\\\/\\\/www.searchviu.com\\\/en\\\/author\\\/michaelsearchviu-com\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring","description":"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.searchviu.com\/en\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/","og_locale":"en_US","og_type":"article","og_title":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring","og_description":"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.","og_url":"https:\/\/www.searchviu.com\/en\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/","og_site_name":"SEO Data Warehouse And Monitoring","article_published_time":"2026-01-13T13:08:13+00:00","article_modified_time":"2026-01-16T10:27:22+00:00","og_image":[{"width":1200,"height":630,"url":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png","type":"image\/png"}],"author":"Michael","twitter_card":"summary_large_image","twitter_creator":"@searchviu","twitter_site":"@searchviu","twitter_misc":{"Written by":"Michael","Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#article","isPartOf":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/"},"author":{"name":"Michael","@id":"https:\/\/www.searchviu.com\/#\/schema\/person\/047e04e169af50cb1ca9d948557fa1c2"},"headline":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical","datePublished":"2026-01-13T13:08:13+00:00","dateModified":"2026-01-16T10:27:22+00:00","mainEntityOfPage":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/"},"wordCount":1691,"commentCount":0,"publisher":{"@id":"https:\/\/www.searchviu.com\/#organization"},"image":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#primaryimage"},"thumbnailUrl":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png","keywords":["english"],"articleSection":["SEO data"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/","url":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/","name":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical - SEO Data Warehouse And Monitoring","isPartOf":{"@id":"https:\/\/www.searchviu.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#primaryimage"},"image":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#primaryimage"},"thumbnailUrl":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png","datePublished":"2026-01-13T13:08:13+00:00","dateModified":"2026-01-16T10:27:22+00:00","description":"Discover how Google Search Console\u2019s BigQuery export unlocks thousands of additional keywords and URLs for deeper SEO insights. Learn how to set up daily data exports and analyze your site\u2019s performance.","breadcrumb":{"@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#primaryimage","url":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png","contentUrl":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2025\/10\/searchVIU_blog-6.png","width":1200,"height":630},{"@type":"BreadcrumbList","@id":"https:\/\/www.searchviu.com\/the-problem-with-ai-prompt-data-why-marketers-should-be-skeptical\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.searchviu.com\/en\/"},{"@type":"ListItem","position":2,"name":"The Problem With AI Prompt Data: Why Marketers Should Be Skeptical"}]},{"@type":"WebSite","@id":"https:\/\/www.searchviu.com\/#website","url":"https:\/\/www.searchviu.com\/","name":"SEO Data Warehouse And Monitoring","description":"SEO Solutions For Teams And Agencies","publisher":{"@id":"https:\/\/www.searchviu.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.searchviu.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.searchviu.com\/#organization","name":"searchVIU","url":"https:\/\/www.searchviu.com\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.searchviu.com\/#\/schema\/logo\/image\/","url":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2023\/02\/d3babe41-searchviu-logo2x.png","contentUrl":"https:\/\/www.searchviu.com\/wp-content\/uploads\/2023\/02\/d3babe41-searchviu-logo2x.png","width":340,"height":340,"caption":"searchVIU"},"image":{"@id":"https:\/\/www.searchviu.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/x.com\/searchviu","https:\/\/www.linkedin.com\/company\/searchviu\/"]},{"@type":"Person","@id":"https:\/\/www.searchviu.com\/#\/schema\/person\/047e04e169af50cb1ca9d948557fa1c2","name":"Michael","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/0e383ecb4d55e87b2093a198ac18315bff59afd030de65ea2c5b9172bb951d89?s=96&d=mm&r=g","caption":"Michael"},"sameAs":["https:\/\/www.searchviu.com"],"url":"https:\/\/www.searchviu.com\/en\/author\/michaelsearchviu-com\/"}]}},"modified_by":"Michael","_links":{"self":[{"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/posts\/8351","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/comments?post=8351"}],"version-history":[{"count":51,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/posts\/8351\/revisions"}],"predecessor-version":[{"id":8721,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/posts\/8351\/revisions\/8721"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/media\/8233"}],"wp:attachment":[{"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/media?parent=8351"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/categories?post=8351"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.searchviu.com\/en\/wp-json\/wp\/v2\/tags?post=8351"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}