{"id":1292,"date":"2026-07-23T05:07:40","date_gmt":"2026-07-23T05:07:40","guid":{"rendered":"https:\/\/listenlabs.ai\/articles\/media-market-research-trends-2026\/"},"modified":"2026-07-23T05:07:40","modified_gmt":"2026-07-23T05:07:40","slug":"media-market-research-trends-2026","status":"publish","type":"post","link":"https:\/\/listenlabs.ai\/articles\/media-market-research-trends-2026\/","title":{"rendered":"Media Consumer Insights Trends 2026: AI Platforms Explained"},"content":{"rendered":"<p><em>Written by: Anish Rao, Head of Growth, Listen Labs<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Media Insights Leaders<\/h2>\n<ul>\n<li>AI research platforms now collapse the traditional depth-versus-scale trade-off, replacing 4\u20136 week research cycles with sub-24-hour insight loops for media and entertainment enterprises.<\/li>\n<li>Real-time social listening combined with AI-moderated interviews captures both public sentiment and underlying emotional motivations that traditional tracking misses.<\/li>\n<li>Hybrid qual-quant methodologies and synthetic respondent validation support larger sample sizes with statistical confidence while preserving emotional nuance and cultural context.<\/li>\n<li>Zero-party data strategies using consent-based AI interviews are replacing eroded third-party infrastructure as the foundation for audience intelligence amid privacy changes.<\/li>\n<li>Listen Labs delivers these capabilities end-to-end, and <a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\"><strong>see the 24-hour transformation in action<\/strong><\/a>.<\/li>\n<\/ul>\n<h2>How Media Teams Use Real-Time Social Listening in 2026<\/h2>\n<p>McKinsey research found that brands\u2019 own websites accounted for only 3\u201310% of citations among the top ten cited sources for LLM responses in its CPG analysis. For media brands, audience perception now forms largely on third-party terrain, including Reddit threads, YouTube comment sections, and TikTok conversations that traditional brand tracking never captures.<\/p>\n<p>Marketers increasingly use social listening tools to inform business decisions and treat them as a fundamental operational requirement rather than an optional advantage. What makes this shift viable is that modern AI-powered listening now transcribes video dialogue, analyzes on-screen text, and identifies brand logos within short-form video on TikTok, Instagram Reels, and YouTube Shorts, channels that text-only tools miss entirely.<\/p>\n<p>Social listening surfaces what audiences say publicly, but it does not surface why they feel that way. That gap between observed behavior and underlying motivation is where AI-moderated consumer interviews become essential. Real-time listening identifies the signal, and structured qualitative research at scale explains it.<\/p>\n<p><a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\"><strong>See how we pair real-time signals with interview intelligence<\/strong><\/a> in under 24 hours.<\/p>\n<h2>Where Synthetic Respondents Fit in Media Research<\/h2>\n<p>Synthetic respondents, AI-generated profiles that simulate consumer reactions, have entered mainstream consideration in 2026. Synthetic audience profiles are now frequently evaluated for integration into insights processes, and <a href=\"https:\/\/bcg.com\/publications\/2026\/want-consumer-insights-faster-ai-can-help\" target=\"_blank\" rel=\"noindex nofollow\">BCG found that synthetic panels predicted real-world consumer choices for a new beverage with 92% accuracy after fine-tuning<\/a>.<\/p>\n<p>The evidence, however, remains methodologically uneven. <a href=\"https:\/\/imotions.com\/blog\/insights\/thought-leadership\/digital-twins-in-marketing-research\" target=\"_blank\" rel=\"noindex nofollow\">Major validity risks include sycophancy, insufficient response variance, social desirability bias, and high prompt sensitivity<\/a>, problems that compound when models attempt to predict real-world behavior. <a href=\"https:\/\/radical-innovators.com\/en\/insights\/synthetic-personas-market-research-2026\" target=\"_blank\" rel=\"noindex nofollow\">Bisbee et al. found that synthetic respondents matched real survey averages but showed significantly less variance, with regression coefficients often differing significantly<\/a>, which demonstrates these risks empirically. For media companies making high-stakes content, campaign, or platform decisions, that variance problem is not a rounding error, it is the difference between a confident launch and a costly misread.<\/p>\n<p><a href=\"https:\/\/pymc-labs.com\/blog-posts\/synthetic-consumers-a-practical-guide\" target=\"_blank\" rel=\"noindex nofollow\">Synthetic consumer models excel in structured quantitative tasks such as ranking and pricing but remain limited in modeling emotional nuance, cultural context, and group dynamics<\/a>. These dimensions matter most in media and entertainment research. A hybrid posture works best: use synthetic screening to eliminate weak variants early, then validate with real AI-moderated interviews before committing to final decisions.<\/p>\n<p>Listen Labs conducts those validation interviews at scale with verified human participants and with emotional intelligence layered on top, closing the gap that synthetic-only approaches leave open.<\/p>\n<h2>How Hybrid Qual-Quant Methods Reshape Audience Intelligence<\/h2>\n<p>This validation approach exemplifies a broader shift toward hybrid qual-quant methodologies that reshape audience intelligence. These methods enable larger sample sizes for qualitative studies and faster time-to-decision, breaking the traditional ceiling that forced researchers to choose between depth and statistical confidence.<\/p>\n<p><a href=\"https:\/\/getperspective.ai\/blog\/2026-ai-research-productivity-report-time-to-insight-cut-84-percent\" target=\"_blank\" rel=\"noindex nofollow\">Analysis of AI-moderated studies found that the analysis stage alone fell 91%<\/a>, the single largest efficiency gain in the research workflow. For VP- and Director-level Consumer Insights leaders managing growing backlogs, that compression translates directly into more studies per quarter at constant headcount.<\/p>\n<p><a href=\"https:\/\/listenlabs.ai\/blog\/what-is-qual-at-scale\" target=\"_blank\">With qual-at-scale, the old trade-off between depth and scale is no longer a barrier.<\/a> Listen Labs conducts hundreds of AI-moderated qualitative interviews simultaneously, each with dynamic follow-up questions. The platform delivers the statistical confidence of large samples alongside the nuanced understanding of one-on-one conversations.<\/p>\n<h2>How Leading Media Enterprises Rethink Privacy and Zero-Party Data<\/h2>\n<p>The third-party data infrastructure that media companies relied on for audience measurement has eroded significantly. <a href=\"https:\/\/ppc.land\/chrome-kills-most-privacy-sandbox-technologies-after-adoption-fails\/\" target=\"_blank\" rel=\"noindex nofollow\">Google announced the retirement of its Privacy Sandbox advertising APIs, including Topics, Protected Audience, and Attribution Reporting, in October 2025, with deprecation and removal to follow in 2026<\/a>, and AI-referred traffic frequently arrives with no referrer, which leaves it misclassified as direct and invisible to attribution models.<\/p>\n<p><a href=\"https:\/\/www.alvarezandmarsal.com\/sites\/default\/files\/2026-03\/LIGHTS%2C%20CAMERA%2C%20AI%20What%20consumers%20reveal%20about%20how%20AI%20is%20reshaping%20Media%20%26%20Entertainment.pdf\" target=\"_blank\" rel=\"noindex nofollow\">Alvarez &amp; Marsal\u2019s March 2026 \u201cLights, Camera, AI\u201d study of nearly 2,000 US consumers did not report any finding that 59% believe privacy is disappearing or has disappeared<\/a>. Zero-party data, information audiences voluntarily share in exchange for personalized experiences, now provides the most defensible foundation for audience intelligence.<\/p>\n<p>AI-moderated interviews act as a direct zero-party data collection mechanism. Participants share motivations, preferences, and emotional reactions in their own words with full consent, which produces insight that no behavioral signal can replicate.<\/p>\n<h2>How Generational Shifts and Cross-Platform Attribution Are Changing<\/h2>\n<p><a href=\"https:\/\/nielsen.com\/news-center\/2026\/gen-alpha-leads-shift-to-ai-powered-entertainment-search-discovery-and-recommendations\" target=\"_blank\" rel=\"noindex nofollow\">Gracenote&#8217;s 2026 &#8220;TV Search and Discovery in the AI Era&#8221; survey of 4,003 US AI chatbot users found that 80% of Gen Alpha respondents reported increased chatbot use for entertainment over the past 12\u201318 months, with more than half using chatbots daily<\/a>. Among all respondents, AI chatbots are increasingly a favored way to get information on why, where, and when to watch content.<\/p>\n<p><a href=\"https:\/\/alvarezandmarsal.com\/press-release\/alvarez-marsal-study-consumers-widely-accept-ai-created-and-curated-media\" target=\"_blank\" rel=\"noindex nofollow\">Respondents in the same Alvarez &amp; Marsal 2026 study expect to spend 29% more time with AI-driven platforms and 11% less on traditional broadcast and cable<\/a>. These generational and behavioral shifts fragment the audience measurement landscape across streaming, gaming, retail media, and short-form video simultaneously, which makes cross-platform attribution increasingly difficult with legacy panel methodologies.<\/p>\n<p>Grant Thornton\u2019s 2026 AI Impact Survey found that media and entertainment organizations have leading board-level AI commitment, though no specific percentage of boards approving major AI investments is reported for the sector, with 17% of M&amp;E organizations reporting agentic AI fully integrated into enterprise workflows. The enterprises moving fastest are those replacing periodic audience measurement with continuous consumer intelligence programs.<\/p>\n<h2>Introducing Listen Labs: AI Research Infrastructure for Media<\/h2>\n<p><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 enterprises including Microsoft, Perplexity, and Sweetgreen<\/a>, compressing research cycles that previously took 4\u20136 weeks into deliverables ready in under 24 hours. The platform handles the entire research lifecycle in a single environment: AI-assisted study design, global participant recruitment from a verified 30M-person network across 45+ countries, AI-moderated video interviews in 100+ languages, automated analysis, and consultant-quality deliverables.<\/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>For media and entertainment Consumer Insights leaders, three capabilities matter most.<\/p>\n<p><strong>Emotional Intelligence<\/strong> goes beyond transcripts. <a href=\"https:\/\/listenlabs.ai\/blog\/emotional-intelligence\" target=\"_blank\">It analyzes three layers of signal, tone of voice, word choice, and subconscious micro expressions, to surface emotions that transcripts alone miss<\/a>. <a href=\"https:\/\/listenlabs.ai\/blog\/emotional-intelligence\" target=\"_blank\">Built on Ekman&#8217;s universal emotions framework, every emotion is quantified per question and concept, with every label traceable to the exact timestamp, verbatim quote, and AI reasoning behind it<\/a>. For creative testing, concept comparison, and brand research across streaming and entertainment contexts, this means knowing not just what audiences say about a trailer, but where they light up, disengage, or get confused.<\/p>\n<p><strong>Research Agent<\/strong> removes the analysis bottleneck. <a href=\"https:\/\/listenlabs.ai\/blog\/research-agent\" target=\"_blank\">It handles the full analysis workflow from raw data to final output<\/a>, generating slide decks, memos, video highlight reels, statistical charts, and segmentation breakdowns in under a minute. Researchers ask questions in natural language and receive answers with significance testing and source-linked verbatims.<\/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<p><strong>Mission Control<\/strong> builds institutional knowledge across every study. Instead of insights living in scattered slide decks, every study grows a searchable knowledge base that enables cross-study queries, trend tracking, and answers from past research in seconds.<\/p>\n<p><a href=\"https:\/\/listenlabs.ai\/blog\/ai-interviews-beat-focus-groups\" target=\"_blank\">Switching to AI-moderated interviews let Chubbies capture hundreds of candid, one-to-one conversations overnight<\/a>, which illustrates what becomes possible when the logistics of research stop being the constraint.<\/p>\n<p><a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\"><strong>Explore the full platform for media insights<\/strong><\/a>.<\/p>\n<h2>2026 Implementation Checklist: From Trends to Concrete Actions<\/h2>\n<p>The following checklist maps each 2026 media consumer insights trend to a specific Listen Labs capability, giving Consumer Insights leaders a practical starting point for platform evaluation.<\/p>\n<p>Start by addressing the most immediate operational constraint, research speed.<\/p>\n<ol>\n<li><strong>Collapse research cycle time:<\/strong> Deploy Listen Labs&#8217; end-to-end AI platform to compress traditional agency timelines to under 24 hours, from study design through final deliverables.<\/li>\n<\/ol>\n<p>Once speed no longer acts as the bottleneck, expand methodological capability.<\/p>\n<ol start=\"2\">\n<li><strong>Scale qualitative depth:<\/strong> Use AI-moderated interviews to run n=200\u20132,000 conversational studies that combine qualitative nuance with quantitative statistical confidence, removing the depth-versus-scale trade-off.<\/li>\n<li><strong>Capture emotional signals:<\/strong> Activate Emotional Intelligence to analyze tone, word choice, and micro expressions across creative testing, concept comparison, and brand research, available in 50+ languages.<\/li>\n<li><strong>Validate synthetic screening:<\/strong> Use synthetic respondents for early hypothesis screening, then validate winning concepts with Listen Labs&#8217; verified human panel before committing to high-stakes decisions.<\/li>\n<\/ol>\n<p>Then build durable data assets and measurement coverage.<\/p>\n<ol start=\"5\">\n<li><strong>Build zero-party data assets:<\/strong> Conduct consent-based AI-moderated interviews as a direct zero-party data collection mechanism, capturing motivations and preferences audiences share voluntarily.<\/li>\n<li><strong>Measure generational fragmentation:<\/strong> Recruit across Listen Labs&#8217; 30M verified global panel to study Gen Alpha, Gen Z, Millennial, and Boomer audiences simultaneously across streaming, gaming, and short-form video contexts.<\/li>\n<\/ol>\n<p>Finally, strengthen institutional knowledge and governance.<\/p>\n<ol start=\"7\">\n<li><strong>Eliminate institutional knowledge loss:<\/strong> Deploy Mission Control as the organization&#8217;s source of truth, enabling cross-study queries and trend tracking so insights compound rather than disappear after each project.<\/li>\n<li><strong>Enable non-researcher self-serve:<\/strong> Allow product managers, brand managers, and marketing leaders to run studies independently using AI-assisted study design, which frees the research team for strategic work.<\/li>\n<li><strong>Ensure enterprise-grade security:<\/strong> Confirm SOC 2 Type II, GDPR, ISO 27001, ISO 27701, and ISO 42001 compliance before onboarding, with 256-bit encryption and no customer data used for AI model training.<\/li>\n<\/ol>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How does Listen Labs Emotional Intelligence capture tone, word choice, and micro-expressions across 50+ languages?<\/h3>\n<p>Emotional Intelligence analyzes three simultaneous signal layers during every AI-moderated interview: tone of voice, word choice, and subconscious facial micro expressions. It is built on Ekman&#8217;s universal emotions framework, the same standard used in clinical psychology and UX research, and tracks emotions including anger, anticipation, disgust, fear, joy, sadness, trust, and surprise. Every emotion label is quantified per question and concept, and every label links to the exact timestamp, verbatim quote, and AI reasoning that produced it. The system operates across 50+ languages, which makes it applicable to multi-market media research without separate localized analysis workflows. Researchers can query emotional data in natural language through the Research Agent and generate charts, reports, and highlight reels of the most emotionally significant moments.<\/p>\n<h3>What quality controls ensure zero fraud in Listen Labs&#8217; 30M verified global panel?<\/h3>\n<p>Listen Labs applies three layers of fraud prevention. First, the platform works exclusively with high-quality, non-commodity panel sources, and professional survey-takers and incentive-optimizing respondents are excluded at the sourcing level. Second, Quality Guard monitors every interview in real time across video, voice, content, and device signals, detecting fraudulent responses, low-effort answers, AI-generated scripts, and mismatched profiles before they enter the dataset. Third, a dedicated recruitment operations team adds a human review layer for hard-to-reach segments, and participants are limited to three studies per month to eliminate panel fatigue and repeat-respondent bias. Reputation scoring compounds across every interview conducted on the platform, which means panel quality improves as Listen Labs scales, a flywheel that commodity panel providers cannot replicate.<\/p>\n<h3>Can Listen Labs maintain enterprise-grade security while delivering 24-hour turnaround?<\/h3>\n<p>Yes. Listen Labs holds SOC 2 Type II, GDPR, ISO 27001, ISO 27701, and ISO 42001 certifications, with 256-bit encryption applied to all data in transit and at rest. Customer data is never used for AI model training. Enterprise SSO is supported for identity management. The 24-hour turnaround is achieved through parallel AI moderation, where hundreds of interviews run simultaneously rather than sequentially, so speed reflects architecture rather than a trade-off against security controls. Enterprises in regulated media and entertainment environments can complete a security review during the pilot process before full deployment.<\/p>\n<h3>How does Listen Labs Research Agent produce consultant-quality deliverables without replacing human researchers?<\/h3>\n<p>Research Agent automates the most time-consuming stages of the analysis workflow, including theme extraction, pattern identification, significance testing, segmentation, and deliverable formatting. It generates slide decks, memo-style reports, video highlight reels, statistical charts, and custom segmentation breakdowns in under a minute, with every insight linked back to the underlying response data. Human researchers retain ownership of strategic interpretation, opportunity mapping, and stakeholder communication, the work that requires judgment rather than processing. A research team of the same size can therefore run significantly more studies per quarter, clear backlogs, and respond to internal requests that previously went unfulfilled. Listen Labs functions as a force multiplier for existing research teams, not a replacement for them.<\/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<h3>What media-specific outcomes have Microsoft and Skims achieved with Listen Labs?<\/h3>\n<p>Microsoft used Listen Labs to collect global customer video stories for its 50th anniversary celebration within a single day, a project that previously would have taken 6\u20138 weeks through traditional research methods. The Director of Data Science at Microsoft noted the ability to reach hundreds of users at one third of the cost, with leadership expressing strong satisfaction at both the speed and scale the platform enabled. Skims used Listen Labs to validate campaign direction with thousands of high-income buyers overnight before a global launch, which eliminated weeks of recruiting and panel sourcing. The SVP of Data, Insights, and Loyalty at Skims highlighted the platform&#8217;s ability to surface the &#8220;why&#8221; behind consumer reactions, qualitative clarity that translated directly into board-level confidence in the campaign direction.<\/p>\n<h3>How does Mission Control build institutional knowledge across studies?<\/h3>\n<p>Mission Control serves as the organization&#8217;s permanent source of truth for everything learned from consumers across all studies conducted on the platform. Each completed study automatically grows the knowledge base rather than producing a standalone report that gets filed and forgotten. Researchers can run cross-study queries in natural language, asking, for example, how audience sentiment toward a content format has shifted over the past four quarters, and receive answers in seconds without manually searching through archived slide decks. Trend tracking is built in, which enables Consumer Insights teams to monitor how consumer needs, pain points, and preferences evolve over time. For media enterprises running continuous research programs, Mission Control converts individual studies into a compounding institutional asset.<\/p>\n<h3>Is Listen Labs suitable for non-researchers in media organizations?<\/h3>\n<p>Yes. The platform supports both dedicated research teams and non-researchers such as product managers, brand managers, and marketing leaders who need consumer insights without research methodology expertise. Non-researchers describe their goals in natural language, and the AI drafts structured study objectives, interview questions, and probing context automatically. Recruitment, moderation, transcription, and analysis are handled by the platform. The Research Agent delivers findings in formats such as slide decks, memos, and highlight reels that non-researchers can present directly to stakeholders. This self-serve capability allows media organizations to distribute research capacity across teams without proportionally increasing the load on the central Consumer Insights function.<\/p>\n<h3>How does Listen Labs pricing compare to traditional 4\u20136 week agency cycles?<\/h3>\n<p>Listen Labs uses a subscription model in which enterprises pay for platform access, covering a set number of studies and credits, and then spend credits per participant recruited. Credit cost varies based on audience difficulty, with general population studies requiring fewer credits than niche or hard-to-reach segments. Enterprises with more than 100 employees go through a demo and pilot process before full deployment. Compared to traditional agency cycles, Listen Labs enables enterprises to run more studies at approximately one third of the cost while compressing timelines from weeks to hours.<\/p>\n<h2>Conclusion: Turning Media Research into a 24-Hour Operation<\/h2>\n<p>The 2026 media consumer insights landscape rewards speed, emotional depth, and methodological rigor simultaneously, a combination that traditional agency cycles and fragmented toolchains cannot deliver. <a href=\"https:\/\/getperspective.ai\/blog\/2026-customer-discovery-velocity-report-ai-cut-time-to-insight-94-percent\" target=\"_blank\" rel=\"noindex nofollow\">Median time-to-insight has collapsed from 12 weeks in 2024 to 18 hours in 2026<\/a> for teams that have adopted AI-moderated research infrastructure. As consumer time shifts dramatically toward AI-driven platforms, as noted earlier, generational measurement is fragmenting across streaming, gaming, and short-form video, and privacy constraints are eliminating the third-party signals media companies once relied on for audience intelligence.<\/p>\n<p>Listen Labs is the only end-to-end AI research platform that delivers consultant-quality emotional depth through Emotional Intelligence, Research Agent, and Mission Control at the statistical scale that media enterprises require, with enterprise-grade security and a verified 30M-person global panel. The research backlog does not have to keep growing. The traditional multi-week cycle does not have to be the default.<\/p>\n<p><a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\"><strong>Start your 24-hour transformation<\/strong><\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Explore 2026 media market research trends shaping audience intelligence. Listen Labs delivers real-time AI insights at scale. Start researching today.<\/p>\n","protected":false},"author":52,"featured_media":1291,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1292","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts\/1292","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/comments?post=1292"}],"version-history":[{"count":0,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts\/1292\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/media\/1291"}],"wp:attachment":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/media?parent=1292"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/categories?post=1292"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/tags?post=1292"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}