{"id":1896,"date":"2026-09-07T05:01:05","date_gmt":"2026-09-07T05:01:05","guid":{"rendered":"https:\/\/listenlabs.com\/articles\/best-ai-brand-performance-tools\/"},"modified":"2026-09-07T05:01:05","modified_gmt":"2026-09-07T05:01:05","slug":"best-ai-brand-performance-tools","status":"publish","type":"post","link":"https:\/\/listenlabs.com\/articles\/best-ai-brand-performance-tools\/","title":{"rendered":"AI Brand Performance Tools: Measurement Vs. Forecasting"},"content":{"rendered":"<p><em>Written by: Anish Rao, Head of Growth, Listen Labs<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>AI brand performance tools need trend analysis, early warning signals, and sentiment attribution, not just point-in-time visibility metrics.<\/li>\n<li>Most vendors (Semrush, Profound, Peec AI, Otterly.ai, ZipTie.dev, Brandwatch) focus on measuring current AI visibility instead of forecasting future performance.<\/li>\n<li>Qualitative consumer research explains why AI visibility shifts happen and turns directional signals into real prediction.<\/li>\n<li>Enterprise platforms like Listen Labs combine quantitative tracking with AI-powered interviews to reveal customer motivations behind visibility changes.<\/li>\n<\/ul>\n<h2>What To Prioritize In AI Brand Performance Prediction Tools<\/h2>\n<p>Measurement shows where you stand today. Prediction shows where your brand is heading next. These capabilities differ, and most vendors blur the line between them.<\/p>\n<p>Five capabilities separate true prediction from reactive measurement:<\/p>\n<ol>\n<li><strong>Trend analysis over time<\/strong> \u2014 The tool should track your AI visibility across weeks and months, not just provide a single snapshot.<\/li>\n<li><strong>Early warning signals<\/strong> \u2014 The platform should detect emerging threats or opportunities before they affect your KPIs.<\/li>\n<li><strong>Sentiment and source attribution<\/strong> \u2014 It should distinguish between a mention and a recommendation and identify which third-party sources shape AI narratives.<\/li>\n<li><strong>Integration with existing SEO and research stacks<\/strong> \u2014 The tool should connect to Semrush, Ahrefs, Qualtrics, or your existing dashboards.<\/li>\n<li><strong>Actionable insights, not just data<\/strong> \u2014 The output should translate into clear next steps, not just charts and counts.<\/li>\n<\/ol>\n<p>The limits here are structural. <a href=\"https:\/\/forbes.com\/sites\/jasongoldberg\/2026\/08\/17\/ai-visibility-numbers-are-unreliable-measure-them-anyway\" target=\"_blank\" rel=\"noindex nofollow\">A June 2026 study found that repeated identical queries produced overlapping source sets of only 30\u201350% across major AI platforms<\/a>, which means the underlying data is inherently noisy. Some tools provide stronger signals than others, yet no tool delivers perfect prediction.<\/p>\n<h2>Six AI Brand Performance Prediction Tools, Reviewed<\/h2>\n<h3>Semrush: Best For SEO Integration<\/h3>\n<p>Semrush entered the AI visibility space in 2025, rolling out the AI Toolkit on March 4 and the AI Visibility Index in September. The <a href=\"https:\/\/semrush.com\/kb\/1626-ai-visibility-features\" target=\"_blank\" rel=\"noindex nofollow\">AI Visibility Toolkit<\/a> tracks share of voice, sentiment, mentions, and citations across ChatGPT, Perplexity, Gemini, and Google AI Overviews, with weekly updates. For teams already on Semrush, pricing starts at $99\/month for the AI Visibility Toolkit or $199\/month for Semrush One.<\/p>\n<p><strong>Prediction capability:<\/strong> Limited at the standard tier. Semrush\u2019s standard AI visibility reports focus on current state. True forecasting sits in <a href=\"https:\/\/business.adobe.com\/products\/semrush\/enterprise\/aio.html\" target=\"_blank\" rel=\"noindex nofollow\">Semrush Enterprise AIO<\/a>, which offers AI search forecasting powered by 261 million real user prompts and requires custom pricing.<\/p>\n<p><strong>Best for:<\/strong> Teams already invested in Semrush\u2019s SEO stack that want AI visibility data alongside traditional rankings.<\/p>\n<h3>Profound: Best For Enterprise-Scale AI Search Intelligence<\/h3>\n<p>Profound raised a <a href=\"https:\/\/www.tryprofound.com\/blog\/profound-seed-round\" target=\"_blank\" rel=\"noindex nofollow\">$3.5 million seed round in August 2024<\/a> and positions itself as an enterprise answer engine optimization platform. Its <a href=\"https:\/\/tryprofound.com\/blog\/introducing-the-profound-index\" target=\"_blank\" rel=\"noindex nofollow\">Profound Index<\/a>, launched June 2026, ranks brands across six diagnostic metrics: Visibility Score, Share of Voice, Mention Position, Citation Share, Co-citation Share, and Co-mention Share. These metrics draw on 1.5+ billion real user conversations across more than 50 industries.<\/p>\n<p><strong>Prediction capability:<\/strong> Moderate. Metrics like Mention Position and Citation Share highlight weak spots that signal future opportunity. Profound\u2019s closed-loop workflows detect opportunities, generate recommendations, and measure results, creating an optimization feedback loop rather than a full forecast engine.<\/p>\n<p><strong>Best for:<\/strong> Enterprise teams that need deep competitive intelligence and prompt-level tracking across major LLMs.<\/p>\n<h3>Peec AI: Best For Mid-Market Teams On A Budget<\/h3>\n<p>Peec AI focuses on e-commerce brands and mid-market teams that track large prompt sets without enterprise budgets. It offers competitive monitoring across AI platforms with an emphasis on prompt-level data that supports tactical decisions.<\/p>\n<p><strong>Prediction capability:<\/strong> Limited. Peec AI excels at monitoring current visibility across many prompts and does not claim formal forecasting features. Its main value is broad tracking coverage at an accessible price.<\/p>\n<p><strong>Best for:<\/strong> Mid-market e-commerce brands that need wide prompt coverage without enterprise pricing.<\/p>\n<h3>Otterly.ai: Best For Straightforward Monitoring<\/h3>\n<p>Otterly.ai skips a permanent free plan and instead provides a <a href=\"https:\/\/help.otterly.ai\/free-trial\" target=\"_blank\" rel=\"noindex nofollow\">7-day free trial with no credit card required<\/a>, plus paid tiers for tracking AI engine citations. It focuses on monitoring and answers a single question: where a brand appears in AI responses.<\/p>\n<p><strong>Prediction capability:<\/strong> Minimal. Otterly.ai offers current-state citation tracking without trend forecasting or early warning signals. It functions as a measurement tool rather than a prediction platform.<\/p>\n<p><strong>Best for:<\/strong> Teams that want basic AI visibility monitoring with a simple trial entry point.<\/p>\n<h3>ZipTie.dev: Best For LLM Monitoring And Optimization Workflows<\/h3>\n<p>ZipTie.dev combines LLM monitoring with guided optimization workflows, which suits technical teams that want to move from tracking into execution.<\/p>\n<p><strong>Prediction capability:<\/strong> Moderate. ZipTie.dev connects monitoring data to optimization actions and identifies gaps with recommended fixes. Its predictive strength lies in highlighting issues and opportunities instead of projecting detailed future performance.<\/p>\n<p><strong>Best for:<\/strong> Teams with technical resources that want monitoring and optimization in one platform.<\/p>\n<h3>Brandwatch: Best For Enterprise Social Listening<\/h3>\n<p>Brandwatch extends its enterprise social listening platform with AI visibility monitoring, tracking brand mentions across AI engines alongside traditional social channels.<\/p>\n<p><strong>Prediction capability:<\/strong> Limited. Brandwatch\u2019s core strength is large-scale social listening. Its AI visibility features measure current mentions and sentiment without dedicated AI brand performance forecasting.<\/p>\n<p><strong>Best for:<\/strong> Enterprises that want AI visibility data integrated into a comprehensive social listening suite.<\/p>\n<h2>How To Evaluate Predictive Capabilities<\/h2>\n<p>Four factors distinguish a predictive tool from a reactive one:<\/p>\n<ol>\n<li><strong>Historical data depth<\/strong> \u2014 Prediction depends on trend lines instead of isolated snapshots.<\/li>\n<li><strong>Early warning signal design<\/strong> \u2014 The tool should flag anomalies before they harden into trends.<\/li>\n<li><strong>Data input diversity<\/strong> \u2014 Strong models incorporate consumer sentiment, third-party sources, and behavioral signals beyond AI citations.<\/li>\n<li><strong>Scenario modeling<\/strong> \u2014 The platform should project outcomes when you change content strategy, pricing, or positioning.<\/li>\n<\/ol>\n<p>Quantitative tools show that a number moved, yet they rarely explain why. A dashboard might show your AI share of voice dropping from 12% to 8%, while offering no insight into whether customers now see your positioning as outdated or a competitor\u2019s campaign has shifted the conversation.<\/p>\n<p><strong>The Say-Do Gap:<\/strong> Customers often say one thing and do another. Ask Gen Z how they feel about AI customer service and many will claim to prefer humans. In practice, they click the AI agent within seconds. Traditional research struggles to capture this gap. AI visibility tools miss it entirely because they see only the output, not the underlying motivation.<\/p>\n<p>Qualitative consumer research closes that gap and makes prediction credible. <a href=\"https:\/\/www.forbes.com\/sites\/iainmartin\/2026\/01\/14\/this-500-million-ai-startup-runs-customer-interviews-for-microsoft-and-sweetgreen\" target=\"_blank\">Listen Labs has conducted over 1 million AI-powered customer interviews for companies including Microsoft, Perplexity, and Sweetgreen<\/a>, uncovering the motivations behind AI visibility shifts. Its <a href=\"https:\/\/listenlabs.ai\/blog\/emotional-intelligence\" target=\"_blank\">Emotional Intelligence<\/a> feature analyzes tone of voice, word choice, and micro-expressions to surface emotions that transcripts miss. Its <a href=\"https:\/\/listenlabs.ai\/blog\/ai-interviews-beat-focus-groups\" target=\"_blank\">Visual Insights<\/a> capability catches contradictions between what participants say and what they do on screen.<\/p>\n<h2>Pricing And Budget Considerations<\/h2>\n<p>Once you shortlist tools by predictive potential and research fit, budget becomes the next filter. Pricing tiers vary significantly across these platforms:<\/p>\n<ul>\n<li><strong>Free tiers:<\/strong> Otterly.ai offers a 7-day free trial. <a href=\"https:\/\/semrush.com\/kb\/1626-ai-visibility-features\" target=\"_blank\" rel=\"noindex nofollow\">Semrush provides basic AI visibility metrics with a free account.<\/a><\/li>\n<li><strong>Mid-market ($99\u2013$300\/month):<\/strong> Semrush AI Visibility Toolkit ($99\/month), Semrush One ($199\/month), Peec AI, and ZipTie.dev typically fall in this range.<\/li>\n<li><strong>Enterprise (custom pricing):<\/strong> <a href=\"https:\/\/business.adobe.com\/products\/semrush\/enterprise\/aio.html\" target=\"_blank\" rel=\"noindex nofollow\">Semrush Enterprise AIO<\/a>, Profound, Brandwatch, and Listen Labs use custom quotes.<\/li>\n<\/ul>\n<p>Listen Labs uses a subscription model with credits per participant. Enterprises pay for platform access plus variable credits based on audience difficulty. General population studies require fewer credits than niche B2B segments. This structure fits organizations that need ongoing customer intelligence instead of one-off projects.<\/p>\n<h2>Integrating AI Visibility Tools With Your SEO And Research Stack<\/h2>\n<p>Your AI visibility tool should connect to the systems your team already uses. Consider how each option integrates:<\/p>\n<ul>\n<li><strong>Semrush<\/strong> integrates natively with its SEO toolkit and <a href=\"https:\/\/business.adobe.com\/products\/semrush\/enterprise.html\" target=\"_blank\" rel=\"noindex nofollow\">Adobe Analytics for enterprise customers<\/a>.<\/li>\n<li><strong>Ahrefs Brand Radar<\/strong> embeds AI visibility within its SEO platform, and <a href=\"https:\/\/ahrefs.com\/blog\/new-features-february-march-2026\" target=\"_blank\" rel=\"noindex nofollow\">Ahrefs\u2019 API v3 is available on Lite+ plans<\/a>, enabling teams to pull Brand Radar data into custom tools.<\/li>\n<li><strong>Brandwatch<\/strong> connects AI visibility metrics to its social listening suite.<\/li>\n<li><strong>Listen Labs<\/strong> integrates with Qualtrics and Decipher through its <a href=\"https:\/\/listenlabs.ai\/blog\/research-agent\" target=\"_blank\">Listen Pulse tracker<\/a>, so teams keep the KPIs they already report while adding the narrative behind them. Its Research Library supports cross-study queries across your entire body of customer research.<\/li>\n<\/ul>\n<p>The central question is whether the tool complements your existing stack or forces you to replace systems that already work.<\/p>\n<h2>Limitations Of AI Measurement And Prediction<\/h2>\n<p>No tool can perfectly predict AI brand performance. Several structural limits shape what is possible:<\/p>\n<ul>\n<li><strong>Data recency:<\/strong> AI algorithms change constantly, so a tool\u2019s training data can become outdated within weeks.<\/li>\n<li><strong>AI algorithm shifts:<\/strong> When Google or OpenAI update their models, citation patterns often shift in unpredictable ways.<\/li>\n<li><strong>The consumer intent gap:<\/strong> Quantitative tools cannot reveal why customers prefer a competitor without asking them directly.<\/li>\n<\/ul>\n<p><a href=\"https:\/\/winngreenwood.com\/blog\/post\/ai-forecasting-limits-trust\" target=\"_blank\" rel=\"noindex nofollow\">AI models trained on inconsistent data produce \u201cconfident-but-wrong\u201d forecasts<\/a>, which are more dangerous than obviously uncertain ones because the confidence disarms skepticism. This dynamic helps explain why, as <a href=\"https:\/\/fundamental.tech\/news\/why-we-keep-expecting-llms-to-be-good-at-prediction\" target=\"_blank\" rel=\"noindex nofollow\">Fundamental\u2019s Chief Science Officer Marta Garnelo notes<\/a>, LLMs may match patterns without understanding business drivers or causal context. Their benchmark performance can stem from memorization instead of genuine predictive capability.<\/p>\n<p>Most tools measure current state. True prediction requires a view into consumer behavior and sentiment, which is why qualitative research provides the layer that makes prediction actionable.<\/p>\n<h2>A Step-By-Step Framework For Choosing A Tool<\/h2>\n<p>Use this framework to shortlist tools and build a clear business case for your CMO:<\/p>\n<ol>\n<li><strong>Define your goals.<\/strong> Decide whether you prioritize awareness, share of voice, sentiment, or genuine prediction. Your answer determines which tools qualify.<\/li>\n<li><strong>Assess your budget and company size.<\/strong> Free and mid-market tools often work for teams under 500 employees. Enterprise organizations usually need custom solutions with dedicated support.<\/li>\n<li><strong>Evaluate integration needs.<\/strong> Map your existing SEO and research stack before you start vendor conversations.<\/li>\n<li><strong>Trial tools with a clear use case.<\/strong> Run focused tests such as \u201ctrack our share of voice in ChatGPT for our top 50 commercial prompts\u201d and compare tools against that scenario.<\/li>\n<li><strong>Layer in qualitative research.<\/strong> Ask vendors how you will uncover the reasons behind a visibility drop. If they cannot answer, plan for a complementary research solution.<\/li>\n<\/ol>\n<p>Key questions to ask every vendor before signing:<\/p>\n<ul>\n<li>What historical data does your prediction model use?<\/li>\n<li>How do you account for AI algorithm changes?<\/li>\n<li>Can you distinguish between a mention and a recommendation?<\/li>\n<li>What third-party sources influence your visibility scores?<\/li>\n<li>How do you validate prediction accuracy?<\/li>\n<\/ul>\n<h2>Why Listen Labs Delivers Actionable AI Brand Insights<\/h2>\n<p>Every tool in this comparison answers \u201cWhere does my brand appear in AI responses?\u201d but none answers the more important \u201cWhy does it appear there, and what happens next?\u201d<\/p>\n<p>Listen Labs fills that gap. Its end-to-end AI research platform <a href=\"https:\/\/www.forbes.com\/sites\/iainmartin\/2026\/01\/14\/this-500-million-ai-startup-runs-customer-interviews-for-microsoft-and-sweetgreen\" target=\"_blank\">sources participants from a 50M+ verified respondent network<\/a> and conducts AI-moderated interviews in 120+ languages. It then delivers consultant-quality reports in under 24 hours, a process that traditionally takes 4\u20136 weeks.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773098461736-796a7724447a.png\" alt=\"Screenshot of researcher creating a study by simply typing &quot;I want to interview Gen Z on how they use ChatGPT&quot;\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Our AI helps you go from idea to implemented discussion guide in seconds.<\/em><\/figcaption><\/figure>\n<p><strong>Listen Pulse<\/strong>, the conversational tracker, runs the same study wave after wave and analyzes open-ended answers. It sorts responses into themes and charts each theme next to the KPIs you already report. The result is a view of trends forming now, before they hit your tracked metrics. <a href=\"https:\/\/listenlabs.ai\/blog\/what-is-qual-at-scale\" target=\"_blank\">The old trade-off between depth and scale no longer applies<\/a>. Pulse delivers the statistical confidence of large samples alongside the qualitative depth of one-on-one interviews.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773098685817-eaceb6089d9a.png\" alt=\"Listen Labs finds participants and helps build screener questions\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Listen Labs finds participants and helps build screener questions<\/em><\/figcaption><\/figure>\n<p>Consider a clothing brand that was quietly losing customers. Its traditional tracker caught the decline and stopped there. Pulse revealed that price was not the issue. A growing segment of customers felt the brand\u2019s big logos were too loud for their changing lifestyles. That insight explained the current decline and signaled the future trajectory.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773098910279-d16bc544a32e.png\" alt=\"Listen Labs auto-generates research reports in under a minute\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Listen Labs auto-generates research reports in under a minute<\/em><\/figcaption><\/figure>\n<p>Prediction requires more than knowing that a number moved. It depends on understanding the customer motivations behind that movement. Listen Labs delivers that understanding at scale.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773099063654-7132de546a42.png\" alt=\"Listen Labs&apos; Research Agent quickly generates consultant-quality PowerPoint slide decks\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Listen Labs&#039; Research Agent quickly generates consultant-quality PowerPoint slide decks<\/em><\/figcaption><\/figure>\n<h2>Frequently Asked Questions<\/h2>\n<h3>What Is AI Brand Visibility?<\/h3>\n<p>AI brand visibility measures how often and how favorably AI engines like ChatGPT, Perplexity, and Gemini mention, cite, or recommend your brand in response to user prompts. It differs from traditional SEO because AI engines synthesize answers from multiple sources instead of ranking pages. A brand can rank on page one of Google and still be absent from AI-generated responses, because the sources AI engines draw on, such as third-party publishers, review platforms, and community discussions, often differ from the pages that rank organically. Tracking AI brand visibility requires purpose-built tools that query AI platforms directly rather than traditional rank trackers.<\/p>\n<h3>How Do AI Brand Performance Tools Predict Brand Performance?<\/h3>\n<p>Most tools measure current visibility, including share of voice, sentiment, and citations, then present trend lines over time. True prediction requires deeper historical data, early warning signals that flag anomalies, and ideally qualitative consumer insight that explains why changes occur. As noted earlier, the say-do gap means quantitative data alone cannot capture the reasons behind behavior shifts. AI algorithms change, citation patterns remain volatile, and no tool predicts perfectly. The strongest platforms provide directional signals that guide strategy, while qualitative research reveals the motivations behind visibility shifts.<\/p>\n<h3>Are There Free AI Visibility Tools?<\/h3>\n<p>Yes. Otterly.ai offers a 7-day free trial, and Semrush provides basic AI visibility metrics with a free account, including a Domain Overview that shows high-level AI visibility benchmarks alongside traditional SEO metrics. These free options support basic monitoring, such as checking whether your brand appears in AI responses for a small set of prompts. They lack the historical depth, competitive benchmarking, and predictive signals of paid tools. Teams that track dozens or hundreds of prompts, monitor multiple competitors, or need early warning signals will require a paid tier.<\/p>\n<h3>How Is Listen Labs Different From Semrush\u2019s AI Visibility Tool?<\/h3>\n<p>Semrush\u2019s AI Visibility Toolkit measures where your brand appears in AI responses, including share of voice, sentiment, and citations across ChatGPT, Perplexity, Gemini, and Google AI Overviews. It answers the question \u201cWhat is happening to my AI visibility?\u201d Listen Labs answers \u201cWhy is it happening, and what will customers do next?\u201d by running AI-moderated consumer interviews at scale. When Semrush shows that your AI share of voice dropped, Listen Labs can reveal whether that drop reflects a shift in how customers perceive your brand, a competitor\u2019s improved positioning, or a change in the language customers use to describe your category. The two tools work together: Semrush provides the quantitative signal, and Listen Labs provides the qualitative explanation that makes the signal actionable.<\/p>\n<h3>Can Listen Labs Support Ongoing AI Brand Tracking, Not Just One-Off Studies?<\/h3>\n<p>Yes. Listen Pulse is an always-on conversational tracker that runs the same study with the same screeners wave after wave. It combines quantitative KPI tracking with open-ended conversation so every metric movement comes with an explanation. Core questions stay constant to protect the trend line, while timely add-on questions cover new campaigns, competitors, or news events without breaking historical comparability. Pulse integrates with Qualtrics and Decipher, so teams keep the KPIs they already report while adding the narrative behind them. It can deploy alongside an existing tracker or act as the primary tracking system and surfaces emerging themes in customer conversations before they appear as a decline in tracked metrics, giving brand and insights leaders a genuine early warning signal that AI visibility dashboards alone cannot provide.<\/p>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/best-ai-powered-brand-monitoring\" target=\"_blank\">AI-Powered Brand Monitoring Tools: The 2026 Guide<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/ai-brand-monitoring-tools-2026\" target=\"_blank\">AI Brand Monitoring Tools: How to Choose in 2026<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/best-ai-brand-tracking-software\" target=\"_blank\">Best AI Brand Tracking Software: Top Tools for 2026<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/best-ai-brand-intelligence-platforms\" target=\"_blank\">AI Brand Intelligence Platforms: Compare Top Tools<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/real-time-ai-brand-tracking\" target=\"_blank\">Real-Time AI Brand Tracking Compared: Visibility vs. Insight<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Compare 6 AI brand performance prediction tools. Listen Labs delivers actionable forecasting\u2014not just measurement. Start tracking your brand today.<\/p>\n","protected":false},"author":52,"featured_media":1895,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1896","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/1896","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/comments?post=1896"}],"version-history":[{"count":0,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/1896\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media\/1895"}],"wp:attachment":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media?parent=1896"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/categories?post=1896"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/tags?post=1896"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}