{"id":658,"date":"2026-05-13T05:05:25","date_gmt":"2026-05-13T05:05:25","guid":{"rendered":"https:\/\/listenlabs.ai\/articles\/ai-moderated-research-cost-2026\/"},"modified":"2026-08-01T05:05:01","modified_gmt":"2026-08-01T05:05:01","slug":"ai-moderated-research-cost-2026","status":"publish","type":"post","link":"https:\/\/listenlabs.com\/articles\/ai-moderated-research-cost-2026\/","title":{"rendered":"AI-Moderated Research Cost in 2026: AI vs. Traditional"},"content":{"rendered":"<p><em>Written by: Anish Rao, Head of Growth, Listen Labs | Last updated: July 31, 2026<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways on 2026 AI Research Costs<\/h2>\n<ul>\n<li>AI-moderated qualitative research typically costs $25\u2013$50 per consumer interview versus $300\u2013$500 for traditional methods, with savings shrinking for B2B and executive audiences.<\/li>\n<li>Cost advantages depend on incidence rates, incentive levels, and quality-control overhead across nine specific evaluation criteria.<\/li>\n<li>AI platforms often cut research spend by 70\u201395% and shorten research cycles from weeks to hours for most consumer insights and UX work.<\/li>\n<li>Listen Labs has run over 1 million AI-powered interviews for enterprises such as Microsoft, Google, Anthropic, and Skims, with results delivered in under 24 hours.<\/li>\n<li><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\">See Listen Labs\u2019 2026 enterprise pricing and panel access firsthand.<\/a><\/li>\n<\/ul>\n<h2>Nine Dimensions for Comparing AI and Traditional Qualitative<\/h2>\n<p>A meaningful cost comparison looks across nine dimensions, not just headline per-interview rates.<\/p>\n<ol>\n<li><strong>Research speed:<\/strong> Calendar time from study brief to final deliverable, including internal coordination.<\/li>\n<li><strong>Per-interview cost:<\/strong> All-in cost that includes moderation, transcription, and analysis, not platform fees alone.<\/li>\n<li><strong>Sample quality and fraud prevention:<\/strong> Screening rigor, behavioral verification, and real-time quality monitoring.<\/li>\n<li><strong>Incentive economics by audience type:<\/strong> How incentive rates for consumers, B2B professionals, and C-suite participants shape total project cost.<\/li>\n<li><strong>Hidden fees:<\/strong> Coordination labor, scheduling overhead, no-show buffers, agency margins, and rework.<\/li>\n<li><strong>Global and multilingual reach:<\/strong> Panel coverage, localization capability, and field firm needs per market.<\/li>\n<li><strong>Analysis and reporting effort:<\/strong> Manual coding and report-writing time versus automated theme extraction and one-click deliverables.<\/li>\n<li><strong>Compliance and security:<\/strong> SOC 2, GDPR, ISO 27001, and data-handling requirements for enterprise procurement.<\/li>\n<li><strong>Long-term repeatability:<\/strong> Support for continuous research programs versus only episodic projects.<\/li>\n<\/ol>\n<h2>2026 Cost Benchmarks by Audience Tier<\/h2>\n<p>Per-interview economics differ sharply by audience. The table below highlights how AI\u2019s cost advantage is dramatic for consumer work and narrows as incentives rise for senior B2B and C-suite participants. Look for the pattern where savings compress at the top of the market because incentives, not platform fees, dominate total cost.<\/p>\n<table>\n<thead>\n<tr>\n<th>Audience Tier<\/th>\n<th>Traditional Agency (per interview)<\/th>\n<th>AI-Moderated Platform (per interview)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>General population consumer<\/td>\n<td>$300\u2013$500<\/td>\n<td>$25\u2013$50<\/td>\n<\/tr>\n<tr>\n<td>Mid-tier B2B professional (manager\/director)<\/td>\n<td>$300+<\/td>\n<td><a href=\"https:\/\/getperspective.ai\/blog\/ai-moderated-interviews-how-they-work-when-to-use\" target=\"_blank\" rel=\"noindex nofollow\">$4\u2013$50<\/a><\/td>\n<\/tr>\n<tr>\n<td>Hard-to-reach enterprise (VP\/C-suite, sub-10% incidence)<\/td>\n<td>$1,000+<\/td>\n<td>$25\u2013$50<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Listen Labs client programs show that enterprise teams can reach hundreds of verified participants at roughly one third the cost of traditional agency approaches, with sub-24-hour delivery instead of the <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\">4\u20136 weeks typical of conventional qualitative cycles<\/a>.<\/p>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\">Get a live walkthrough of Listen Labs\u2019 pricing and panel coverage.<\/a><\/p>\n<h2>Study Setup and Participant Sourcing Effort<\/h2>\n<p>Traditional agency studies rely on a long sequence of setup steps. Teams move through briefing calls, screener development, panel sourcing across multiple vendors, scheduling coordination, and moderator preparation. A 30-interview agency study carries project design and recruitment costs before the first interview starts. Internal coordination for a 20-interview study also consumes substantial researcher time at fully loaded rates, and that cost rarely appears in agency quotes.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.com\/\" 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>AI-moderated platforms compress setup to hours. Listen Labs uses AI-assisted study co-design, where researchers describe objectives in natural language and receive a structured discussion guide in seconds. The platform then recruits from a 30M verified respondent network across 45+ countries. Listen Atlas, the AI orchestration layer, matches and bids across multiple panel partners and the proprietary database at once, which removes the multi-vendor coordination that stretches traditional timelines. Organizations with strong customer lists can also self-recruit, which removes panel fees and lowers per-participant cost further.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.com\/\" 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<h2>Incentives and Audience-Level Economics<\/h2>\n<p>Incentive rates vary sharply by audience tier and often represent the largest variable in AI-moderated study cost. General consumers typically receive $50\u2013$100 for a 60-minute interview. B2B managers and directors often require <a href=\"https:\/\/cleverx.com\/blog\/how-to-provide-incentives-for-research-participants\/\" target=\"_blank\" rel=\"noindex nofollow\">$300\u2013$500<\/a> for a 60-minute session. VP and C-suite participants command $300\u2013$600 or more per session, and fractional CISOs frequently charge <a href=\"https:\/\/www.gofractional.com\/insights\/rates\/ciso\" target=\"_blank\" rel=\"noindex nofollow\">$170\u2013$250 per hour<\/a>.<\/p>\n<p>For general-population consumer studies, incentives remain a modest share of AI-moderated total cost, so the platform\u2019s cost advantage stays strong. For mid-tier B2B studies, incentives become the dominant line item, which narrows but does not erase savings versus traditional methods. For hard-to-reach enterprise audiences with sub-10% incidence and VP-level or above titles, incentive costs can approach or match traditional per-interview rates. At that point, the remaining AI advantage sits in speed, analysis automation, and scale rather than raw per-interview spend.<\/p>\n<p><a href=\"https:\/\/cleverx.com\/blog\/b2b-panel-pricing-vs-consumer-panel-pricing\/\" target=\"_blank\" rel=\"noindex nofollow\">B2B professional recruitment costs five to ten times more per respondent than consumer panel recruitment<\/a>. Higher incentive rates, lower panel density for niche criteria, and elevated screener failure rates drive this gap. No-show rates for B2B interviews also vary by recruitment method, which forces over-recruitment buffers that add to incentive budgets.<\/p>\n<h2>Moderation Style and Qualitative Depth<\/h2>\n<p>Human moderators contribute contextual judgment, empathy, and real-time reading of non-verbal cues. Executive C-suite interviews at $1,500\u2013$5,000 each justify traditional human moderation when named moderators with industry credibility are required for participant trust. Ethnographic fieldwork, sensitive clinical research, and court-defensible studies also remain cases where human presence is structurally necessary.<\/p>\n<p>Outside these specialized scenarios, economics and capacity shift in favor of AI. For the broad middle of qualitative research, AI-moderated video interviews deliver adaptive, personalized conversations with dynamic follow-up probes. The system applies the same probing behavior a trained human moderator uses, but it does so consistently across hundreds of simultaneous sessions. <a href=\"https:\/\/koji.so\/docs\/ai-vs-human-moderators\" target=\"_blank\" rel=\"noindex nofollow\">Human moderators are limited to 4\u20136 interviews per day<\/a>, while AI moderation has no daily capacity ceiling.<\/p>\n<p>Listen Labs\u2019 Emotional Intelligence layer deepens this further by analyzing tone of voice, word choice, and micro-expressions to surface emotional signals that transcripts miss. The system builds on Ekman\u2019s universal emotions framework and works across 50+ languages. This helps capture the gap between what participants say and what they feel, which traditional moderation only captures inconsistently.<\/p>\n<h2>Data-Quality Controls and Fraud Prevention Costs<\/h2>\n<p>Quality control overhead creates a significant hidden cost in traditional research. Manual QA of transcripts, screener audits, and panel deduplication consume researcher hours that rarely appear in agency line items. <a href=\"https:\/\/getperspective.ai\/blog\/online-ai-focus-groups-setup-recruitment-and-quality-control-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">Attention-check failure rates reach 25%+ on general-population paid-survey traffic<\/a>, so a meaningful share of traditional panel completes require exclusion after the fact.<\/p>\n<p>Listen Labs\u2019 Quality Guard operates in real time across video, voice, content, and device signals. It detects fraud, low-effort responses, AI-generated scripts, and mismatched profiles before they enter the dataset. Participants are capped at three studies per month, which removes professional survey-takers. Behavioral matching focuses on intent and past actions instead of self-reported demographics alone. A dedicated recruitment operations team adds human review for hard-to-reach segments. These elements create a compounding quality flywheel, where each additional study strengthens reputation scoring in ways commodity panels cannot match.<\/p>\n<h2>Analysis, Reporting, and Knowledge Reuse<\/h2>\n<p>Analysis and reporting consume a large share of cost in a traditional 20-interview agency study. Manual coding takes time, introduces subjectivity, and often reinforces confirmation bias. Report writing then adds more calendar time after fieldwork ends, which widens the gap between data collection and stakeholder delivery.<\/p>\n<p>Listen Labs\u2019 Research Agent processes all interview data at once. It extracts themes, generates personas, and produces slide decks, memos, video highlight reels, and charts in under a minute. Chat-based analysis lets researchers query findings in natural language and receive segmented breakdowns instantly. Mission Control stores every study in a cross-queryable repository, so teams can answer questions from past research in seconds instead of re-running studies. Each new study compounds the institutional knowledge base in a way that static report archives cannot match.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.com\/\" 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><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\">Explore the Research Agent and Mission Control in action.<\/a><\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.com\/\" 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>When AI Cost Advantages Shrink<\/h2>\n<p>Four conditions erode or remove the cost advantage of AI-moderated research.<\/p>\n<ul>\n<li><strong>High-incentive B2B audiences:<\/strong> When VP or C-suite incentives reach $300\u2013$600 per session, the incentive line item dominates total cost regardless of moderation model. At this tier, AI platforms still reduce moderation and analysis costs, but those savings become marginal because the platform cannot change incentive rates, which reflect participant opportunity cost and market scarcity.<\/li>\n<li><strong>Sub-1% incidence rates:<\/strong> Audiences with very specific professional credentials, rare behaviors, or narrow geographic and demographic intersections require extensive outreach to fill quotas. Screener failures and over-recruitment buffers accumulate in both human and AI-led models.<\/li>\n<li><strong>Professional survey-taker fraud:<\/strong> Commodity panels carry elevated fraud risk that quality-control processes must absorb. Studies sourced from low-quality panels often need post-hoc exclusion, re-fielding, and extra QA labor, which can offset platform savings.<\/li>\n<li><strong>Hidden coordination costs on self-managed studies:<\/strong> Teams that use AI moderation but manage recruitment, scheduling, and incentive fulfillment manually absorb coordination overhead that full-stack platforms remove. Internal coordination overhead typically doubles the true organizational cost of a traditional qualitative study once decision delays and insight decay are included, and partially self-managed AI studies face the same dynamic.<\/li>\n<\/ul>\n<h2>Scenario-Based Guidance by Team Type<\/h2>\n<p>Different teams gain different advantages from AI-moderated research.<\/p>\n<ul>\n<li><strong>Enterprise consumer insights teams<\/strong> running high-volume general-population work, such as concept testing, brand tracking, and shopper insights, see the largest absolute savings. Panel scale, automated analysis, and Mission Control\u2019s cross-study repository directly address the research backlog that defines this team\u2019s main constraint.<\/li>\n<li><strong>UX research groups<\/strong> that need rapid feedback for sprint cycles benefit from AI moderation\u2019s unlimited daily capacity and screen-sharing. Studies that previously stopped at 5\u201310 participants due to scheduling can scale to 50\u2013100+ without proportional cost increases.<\/li>\n<li><strong>Product and marketing teams without dedicated researchers<\/strong> gain AI-assisted study design that turns natural-language briefs into structured guides. This removes the methodology expertise barrier that previously forced agency engagement.<\/li>\n<li><strong>Agencies and consultancies<\/strong> with client timelines measured in days can use AI-moderated platforms to protect margins. A 50-interview AI-moderated study costing $1,250\u2013$2,500 on-platform can be sold as a $3,000\u2013$5,000 engagement, which maintains healthy margins while compressing timelines.<\/li>\n<\/ul>\n<h2>Operational, Compliance, and Global Factors<\/h2>\n<p>Shifting from traditional to AI-moderated research requires more than a platform decision. Stakeholders often need calibration evidence, especially teams used to human-moderated depth interviews. Running parallel cohorts with human and AI moderators once or twice per year provides side-by-side comparisons that help address internal skepticism.<\/p>\n<p>Enterprise procurement also requires clear compliance documentation. Listen Labs holds SOC 2 Type II, GDPR, ISO 27001, ISO 27701, and ISO 42001 certifications, uses 256-bit encryption, and never uses customer data for AI model training. These controls satisfy security requirements for Fortune 500 procurement across regulated industries such as financial services, healthcare, and CPG.<\/p>\n<p>Global programs introduce additional cost in traditional research because each language market often needs a separate field firm. That structure adds coordination overhead and timeline risk. Listen Labs supports 100+ languages with automatic translation and transcription, which removes the per-market field firm model for most global designs.<\/p>\n<h2>Decision Framework Mapped to the Nine Criteria<\/h2>\n<p>The checklist below connects practical study choices back to the nine evaluation dimensions.<\/p>\n<ol>\n<li>If the audience is general population or broad B2B with incidence above 10%, AI-moderated platforms deliver maximum cost and speed advantage on per-interview cost and research speed.<\/li>\n<li>If the study requires 30+ interviews, AI moderation\u2019s scale advantage compounds beyond this threshold, while traditional methods hit moderator capacity ceilings that affect speed and hidden labor costs.<\/li>\n<li>If the timeline is under two weeks, only end-to-end AI-moderated platforms reliably deliver within this window while still covering analysis and reporting effort.<\/li>\n<li>If participants are VP-level or above with incentives above $300 per session, teams should weigh whether AI\u2019s gains in analysis automation and speed offset incentive-driven economics.<\/li>\n<li>If the study involves sensitive clinical topics, physical ethnography, or chain-of-custody legal requirements, human moderation remains the correct choice regardless of cost.<\/li>\n<li>If the study is part of a recurring program, AI-moderated platforms with cross-study repositories compound value over time, while episodic agency projects do not build the same knowledge base.<\/li>\n<li>If the organization has customer lists for self-recruitment, self-recruit can remove panel fees and tie total cost more directly to platform rates and incentive economics.<\/li>\n<li>If emotional signals such as micro-expressions, tone, and hesitation matter to the objective, AI platforms with multimodal emotional intelligence capture data that transcript-only methods miss.<\/li>\n<\/ol>\n<h2>Frequently Asked Questions<\/h2>\n<p><strong>What does AI-moderated qualitative research cost per interview in 2026?<\/strong><\/p>\n<p>All-in per-interview costs for AI-moderated qualitative research vary by audience tier and platform. For general-population consumer studies, fully loaded costs that include recruitment, incentives, moderation, transcription, and analysis usually fall between $25 and $50 per completed interview, depending on platform and panel. For mid-tier B2B studies with manager or director-level participants and hard-to-reach enterprise audiences, incentive rates drive most of the cost, while platform fees typically run $25\u2013$50. Listen Labs uses a subscription and credits model, and enterprise teams go through a demo and pilot to set pricing that matches study volume and audience mix.<\/p>\n<p><strong>How much do participant incentives affect total AI-moderated research costs for B2B studies?<\/strong><\/p>\n<p>For B2B studies, participant incentives usually dominate total cost and explain why AI savings narrow versus consumer research. Manager-level B2B participants often require <a href=\"https:\/\/cleverx.com\/blog\/how-to-provide-incentives-for-research-participants\/\" target=\"_blank\" rel=\"noindex nofollow\">$300\u2013$500<\/a> for a 60-minute interview. These rates reflect participant opportunity cost and market scarcity. AI platforms reduce moderation and analysis costs but cannot change incentive levels. For a 30-interview VP-level study, incentives alone can reach significant amounts before any platform or recruitment fees, which reduces percentage savings versus traditional methods even as absolute savings on labor remain real.<\/p>\n<p><strong>When should organizations retain human moderators instead of using AI?<\/strong><\/p>\n<p>Human moderation remains the right choice in four scenarios. Executive C-suite interviews may require named moderators with industry credibility for access and trust. Ethnographic fieldwork needs physical presence and contextual observation. Sensitive clinical or mental health research depends on real-time human judgment for participant welfare. Court-defensible studies, such as Lanham Act trademark research, require specific protocols and chain-of-custody documentation. Outside these categories, AI-moderated interviews usually deliver comparable qualitative depth at lower cost and greater scale for most consumer insights, UX, and product research.<\/p>\n<p><strong>What is the value of emotional intelligence capture in AI-moderated research?<\/strong><\/p>\n<p>Emotional intelligence analysis closes a gap in transcript-based research, because what participants say and what they feel often differ. Two concepts may receive similar verbal ratings while triggering very different emotional responses, such as genuine enthusiasm versus confusion. Listen Labs\u2019 Emotional Intelligence layer analyzes tone of voice, word choice, and micro-expressions to quantify emotions per question and concept, with each label traceable to the exact timestamp, verbatim quote, and reasoning. This is especially useful for creative testing, concept comparison, usability testing, and brand research, where unspoken emotional friction or delight often provides the most actionable signal.<\/p>\n<p><strong>How do self-recruit studies affect total research costs on AI-moderated platforms?<\/strong><\/p>\n<p>Self-recruitment uses an organization\u2019s own customer or prospect lists instead of a third-party panel and removes panel and platform incentive fees. This configuration reduces per-interview cost to the platform rate and any direct incentives the organization chooses to pay. It works best for organizations with large, engaged customer bases. Listen Labs supports self-recruitment at reduced credit cost per participant. The trade-off is that self-recruited samples mirror the existing customer base rather than a broader market, which suits customer satisfaction, churn analysis, and product feedback, but not competitive or new-audience studies that require access to non-customers.<\/p>\n<h2>Conclusion: Where AI-Moderated Research Delivers the Strongest ROI<\/h2>\n<p>The cost gap between AI-moderated and traditional human-moderated qualitative research is widest for general-population consumer studies and narrows as audience seniority, incidence, and incentive requirements rise. For most enterprise consumer insights, UX, and product research, AI-moderated platforms deliver a 70\u201395% reduction in per-interview cost and compress research cycles from weeks to hours. These savings are structural, driven by replacing per-interview human labor with compute and automated analysis, as long as the platform includes strong fraud prevention, adaptive moderation, and end-to-end delivery.<\/p>\n<p>Listen Labs\u2019 track record with large enterprise clients shows these economics at scale, with a 30M verified respondent network across 45+ countries supporting the rapid delivery times described throughout this analysis. For teams evaluating AI-moderated research costs against current methods, the most reliable benchmark comes from a scoped pilot on a real study rather than a static rate card.<\/p>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\">Get a cost benchmark tailored to your audience tier, study volume, and research objectives.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI-moderated research costs $25\u2013$50\/interview vs. $300\u2013$500 traditionally. See how Listen Labs cuts research spend by up to 95%. Get a demo today.<\/p>\n","protected":false},"author":52,"featured_media":657,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-658","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\/658","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=658"}],"version-history":[{"count":1,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/658\/revisions"}],"predecessor-version":[{"id":1399,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/658\/revisions\/1399"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media\/657"}],"wp:attachment":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media?parent=658"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/categories?post=658"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/tags?post=658"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}