{"id":1977,"date":"2026-05-08T05:08:36","date_gmt":"2026-05-08T05:08:36","guid":{"rendered":"https:\/\/blog.aigrowthagent.co\/growth-marketing-metrics-2026\/"},"modified":"2026-09-02T06:02:32","modified_gmt":"2026-09-02T06:02:32","slug":"growth-marketing-metrics-2026","status":"publish","type":"post","link":"https:\/\/aigrowthagent.co\/articles\/growth-marketing-metrics-2026\/","title":{"rendered":"Growth Marketing Metrics: The Complete 2026 List"},"content":{"rendered":"<p><em>Written by: Mariana Fonseca, Editorial Team, AI Growth Agent | Last updated: August 28, 2026<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Growth Teams<\/h2>\n<ul>\n<li>Growth marketing metrics track cohort-level data across acquisition, activation, retention, and monetization. This structure reveals revenue leaks and connects directly to business outcomes.<\/li>\n<li>A North Star metric reflects customer value delivered, predicts retention or expansion, and stays measurable on a weekly cadence.<\/li>\n<li>Acquisition, activation, retention, revenue, and experimentation metrics each need model-specific benchmarks. Healthy LTV:CAC ratios usually range from 3.0x to 5.6x depending on business type.<\/li>\n<li>Vanity metrics such as total page views or raw follower counts should give way to actionable rates that pass the \u201cSo what?\u201d test and connect to pipeline or revenue.<\/li>\n<li>AI Growth Agent supplies a headless engine that maps queries, produces authoritative content, and maintains living dashboards that self-heal. Teams gain incremental visibility without adding headcount. <a href=\"https:\/\/aigrowthagent.co\/book-a-demo\/\" target=\"_blank\"><strong>Book a consultation to see the platform in action.<\/strong><\/a><\/li>\n<\/ul>\n<h2>Choosing a North Star Metric That Actually Drives Growth<\/h2>\n<p>A North Star metric reflects customer value delivered, predicts retention or expansion, and stays measurable weekly. <a href=\"https:\/\/growthengineer.ai\/blog\/north-star-metric-examples\" target=\"_blank\" rel=\"noindex nofollow\">A 2020 survey of 40+ growth-stage companies by Lenny Rachitsky found that approximately 50% use revenue-style North Star metrics such as ARR or GMV, 30% use consumption metrics such as messages sent or nights booked, and 30% use engagement metrics such as DAU or MAU.<\/a> These patterns reflect each model\u2019s core value exchange.<\/p>\n<p>SaaS teams often select messages sent or weekly active editors because usage shows whether customers receive the product\u2019s promise. <a href=\"https:\/\/eic.agency\/resources\/north-star-metric\" target=\"_blank\" rel=\"noindex nofollow\">E-commerce teams select lifetime-value-adjusted ROAS instead of a flat ROAS target because first purchases often lose money while repeat purchases over 6 or 12 months determine true profitability.<\/a> Marketplaces often select completed transactions or nights booked because each transaction delivers value to both sides at once. The North Star must correlate with 30-, 60-, and 90-day retention so every team can influence it.<\/p>\n<p>Once you anchor on a North Star, the five AARRR layers beneath it show exactly where users drop off or accelerate. The next sections walk through those layers, starting with how users enter your funnel.<\/p>\n<h2>1. Acquisition Metrics That Bring Qualified Users In<\/h2>\n<p>Acquisition metrics quantify the first meaningful action that brings a prospect into the funnel. <a href=\"https:\/\/kompassify.com\/blog\/pirate-metrics-guide\" target=\"_blank\" rel=\"noindex nofollow\">Visitor-to-signup rate equals signups divided by unique visitors multiplied by 100, with a typical SaaS range of 2% to 5%. Customer acquisition cost equals total sales and marketing spend divided by new customers acquired.<\/a> <a href=\"https:\/\/www.getaleph.com\/answers\/cltv-cac-ratio-saas-2026\" target=\"_blank\" rel=\"noindex nofollow\">The SaaS and AI Performance Benchmarks report published jointly by Aleph and Benchmarkit on June 1, 2026, covering 342 B2B SaaS and AI-native companies on full-year 2025 actuals, reports that horizontal SaaS had a median 4.1x LTV:CAC and vertical SaaS had a median 5.6x, against a conventional healthy floor of 3.0x.<\/a><\/p>\n<p>Model-specific acquisition examples include:<\/p>\n<ul>\n<li>SaaS: trial starts per paid-search click<\/li>\n<li>E-commerce: new-visitor conversion to first purchase<\/li>\n<li>Marketplace: new-buyer or new-seller signups per month<\/li>\n<\/ul>\n<p><a href=\"https:\/\/aigrowthagent.co\/book-a-demo\/\" target=\"_blank\"><strong>See how AI Growth Agent tracks acquisition at scale.<\/strong><\/a><\/p>\n<h2>2. Activation Metrics That Capture First Value<\/h2>\n<p>Activation metrics measure the moment a user receives concrete value. <a href=\"https:\/\/kompassify.com\/blog\/pirate-metrics-guide\" target=\"_blank\" rel=\"noindex nofollow\">Activation rate equals users who reach the defined core action divided by signups in the same cohort multiplied by 100, with benchmarks ranging from 20% to 40% for most teams and higher for top product-led SaaS. Time-to-value records the median days from signup to that activation event.<\/a> <a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">Intercom research highlights the importance of activation in driving revenue growth.<\/a><\/p>\n<p>Model-specific activation examples include:<\/p>\n<ul>\n<li>SaaS: first invoice sent or first dashboard published<\/li>\n<li>E-commerce: first purchase completed<\/li>\n<li>Marketplace: first transaction between buyer and seller<\/li>\n<\/ul>\n<h2>3. Retention Metrics That Show Whether Users Stay<\/h2>\n<p>Retention metrics track whether users return after the activation moment. <a href=\"https:\/\/kompassify.com\/blog\/pirate-metrics-guide\" target=\"_blank\" rel=\"noindex nofollow\">Day-30 retention equals cohort users active on day 30 divided by cohort size multiplied by 100. Monthly churn equals customers lost in the month divided by customers at the start multiplied by 100.<\/a> <a href=\"https:\/\/churntools.com\/churn-rate-benchmarks\" target=\"_blank\" rel=\"noindex nofollow\">2026 benchmarks show a median monthly churn rate of 3.9% for B2B SaaS and 6.7% for B2C SaaS.<\/a><\/p>\n<p>Model-specific retention examples include:<\/p>\n<ul>\n<li>SaaS: DAU\/MAU ratio above 20%<\/li>\n<li>E-commerce: repeat-purchase rate within 90 days<\/li>\n<li>Marketplace: monthly active buyers and sellers<\/li>\n<\/ul>\n<h2>4. Revenue Metrics That Tie Usage to Dollars<\/h2>\n<p>Revenue metrics connect product usage to actual dollars. <a href=\"https:\/\/kompassify.com\/blog\/pirate-metrics-guide\" target=\"_blank\" rel=\"noindex nofollow\">Trial-to-paid rate equals paying conversions divided by trials started multiplied by 100, with a typical range of 15% to 25% for opt-in trials. Net revenue retention equals starting MRR plus expansion minus churn and contraction divided by starting MRR.<\/a> <a href=\"https:\/\/getfairview.com\/blog\/saas-churn-rate-benchmarks\" target=\"_blank\" rel=\"noindex nofollow\">At Series A, investors typically expect NRR at 100%+ with best-in-class at 110%+; at Series B the bar rises to NRR 105%+.<\/a> <a href=\"https:\/\/www.subjolt.com\/guides\/nrr-grr-benchmarks\/\" target=\"_blank\" rel=\"noindex nofollow\">Mid-market SaaS (ACV $25K\u2013$100K) median NRR is ~108% (top quartile ~120\u2013125%), while usage-based\/PLG SaaS reaches 115\u2013130% median NRR.<\/a><\/p>\n<p>Model-specific revenue examples include:<\/p>\n<ul>\n<li>SaaS: MRR expansion from usage-based add-ons<\/li>\n<li>E-commerce: average order value multiplied by repeat-purchase rate<\/li>\n<li>Marketplace: GMV per active user and take-rate stability<\/li>\n<\/ul>\n<p><a href=\"https:\/\/aigrowthagent.co\/book-a-demo\/\" target=\"_blank\"><strong>Explore how AI Growth Agent helps teams instrument revenue metrics.<\/strong><\/a><\/p>\n<h2>5. Experimentation Metrics That Prove Compounding Impact<\/h2>\n<p>Experimentation meta-metrics show whether the growth program itself compounds over time. <a href=\"https:\/\/tolinku.com\/blog\/growth-experimentation-culture\" target=\"_blank\" rel=\"noindex nofollow\">Growth teams track five core experimentation meta-metrics: test velocity (experiments completed per month), win rate (percentage producing statistically significant positive results), implementation rate (percentage of winning experiments shipped to 100% of users), cumulative impact (total estimated revenue or conversion lift from implemented experiments over a rolling 12-month period), and time to result (average days from launch to statistical significance). A healthy win rate sits between 20% and 35%. Rates above 40% indicate teams are only testing safe, obvious ideas.<\/a><\/p>\n<p><a href=\"https:\/\/dripagency.de\/blog\/experiment-velocity-metrics\" target=\"_blank\" rel=\"noindex nofollow\">Across DRIP Agency&#8217;s database of 4,000+ e-commerce experiments from 90+ brands, mature programs running 18+ months typically achieve 6 to 8+ experiments per month, 35% to 45% win rates, and 80% to 95% implementation rates, producing 10% to 20% annual cumulative validated uplift.<\/a> <a href=\"https:\/\/dripagency.de\/blog\/experiment-velocity-metrics\" target=\"_blank\" rel=\"noindex nofollow\">Implementation rate is the most under-tracked velocity metric. Raising it from 60% to 90% has a larger impact on annual validated uplift than increasing experiment count by 50%.<\/a><\/p>\n<p>Model-specific experimentation examples include:<\/p>\n<ul>\n<li>SaaS: activation-lift experiments tied to onboarding flows<\/li>\n<li>E-commerce: checkout-conversion experiments measured against LTV impact<\/li>\n<li>Marketplace: liquidity experiments measured against completed-transaction volume<\/li>\n<\/ul>\n<p>While the AARRR framework applies broadly, the specific metrics at each stage shift with your revenue model. The next section compares how three common models translate the same lifecycle into different measurements.<\/p>\n<h2>6. Growth Marketing Metrics by Business Model<\/h2>\n<p>The following table maps each AARRR stage to the metric that best captures progress for SaaS, e-commerce, and marketplace models. It shows how one lifecycle framework turns into different measurement approaches depending on how your business earns revenue.<\/p>\n<table>\n<thead>\n<tr>\n<th>Stage<\/th>\n<th>SaaS<\/th>\n<th>E-Commerce<\/th>\n<th>Marketplace<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Acquisition<\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">Trial starts, signups per paid-search click<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">New visitors, first-purchase conversion rate<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">New buyers and sellers per month<\/a><\/td>\n<\/tr>\n<tr>\n<td>Activation<\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">Onboarding completion rate<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">First purchase completed<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">First transaction between buyer and seller<\/a><\/td>\n<\/tr>\n<tr>\n<td>Retention<\/td>\n<td><a href=\"https:\/\/productgrowth.in\/resources\/cheatsheets\/growth-metrics-cheat-sheet\" target=\"_blank\" rel=\"noindex nofollow\">DAU\/MAU ratio<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">Repeat-purchase rate<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">Monthly active buyers and sellers<\/a><\/td>\n<\/tr>\n<tr>\n<td>Revenue<\/td>\n<td><a href=\"https:\/\/kompassify.com\/blog\/pirate-metrics-guide\" target=\"_blank\" rel=\"noindex nofollow\">MRR, NRR<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">AOV multiplied by repeat-purchase rate<\/a><\/td>\n<td><a href=\"https:\/\/vidcogroup.com\/pirate-metrics-aarrr\" target=\"_blank\" rel=\"noindex nofollow\">GMV and take-rate stability<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Metrics to Avoid in Growth Marketing<\/h2>\n<p><a href=\"https:\/\/vested.marketing\/blog\/vanity-metrics-vs-revenue-metrics-are-you-measuring-what-matters\" target=\"_blank\" rel=\"noindex nofollow\">Vanity metrics such as total page views, raw follower counts, email open rates, and total signups measure activity but have no reliable connection to revenue, pipeline, or customer outcomes. The key test is whether the number can increase without producing a clear next action for the team. If it fails this \u201cSo what?\u201d test, remove it from dashboards.<\/a><\/p>\n<p><a href=\"https:\/\/swydo.com\/blog\/vanity-metrics\" target=\"_blank\" rel=\"noindex nofollow\">Post-Apple Mail Privacy Protection, email open rates became inflated industry-wide because images are pre-fetched. Campaigns showing 40% open rates have generated less revenue than those with 15% open rates.<\/a> <a href=\"https:\/\/www.forbes.com\/sites\/forbescommunicationscouncil\/2023\/07\/28\/why-marketers-need-to-ditch-meaningless-metrics\/\" target=\"_blank\" rel=\"noindex nofollow\">Forbes reports, citing a DMA study, that 41% of marketing measures are vanity metrics.<\/a><\/p>\n<p>Replace vanity counts with the following actionable alternatives:<\/p>\n<ul>\n<li>Total page views \u2192 conversion rate by traffic source<\/li>\n<li>Raw follower counts \u2192 qualified leads generated from social channels<\/li>\n<li>Email open rates \u2192 email click-to-conversion rate<\/li>\n<li>Total signups \u2192 activation rate per cohort<\/li>\n<li>Gross MRR alone \u2192 net revenue retention with expansion context<\/li>\n<\/ul>\n<p>Each alternative informs a specific next action and connects directly to pipeline or revenue. <a href=\"https:\/\/muroanalytics.com\/blog\/vanity-metrics-vs-real-metrics\" target=\"_blank\" rel=\"noindex nofollow\">A metric earns its place on a dashboard only if it has a denominator (making it a rate rather than a raw count), a change in the metric would prompt investigation or action, and it reflects the health of a specific funnel step.<\/a><\/p>\n<h2>Synthesis: From Spreadsheets to a Cohort-Based System<\/h2>\n<p>A single North Star supported by cohort-tracked AARRR metrics surfaces leaks faster than any spreadsheet. Scattered vanity counts in disconnected tools hide the exact stage where customers drop, expand, or refer. A focused metrics architecture solves this problem with one North Star that reflects delivered customer value, five AARRR layers that each own a distinct lifecycle stage, and experimentation meta-metrics that prove the growth program itself is compounding.<\/p>\n<p>AI Growth Agent supplies a headless engine that maps the full universe of queries, produces authoritative content validated against primary sources, and maintains living dashboards that self-heal. Teams gain incremental visibility without adding headcount. Across the first twelve weeks, clients average more than 12,000 additional AI citations and mentions, over 100,000 additional bot visits, and a 20%+ lift in impressions, with content indexing in as little as ten days.<\/p>\n<figure style=\"text-align: center;\"><a href=\"https:\/\/aigrowthagent.co\/book-a-demo\/\" target=\"_blank\"><img src=\"https:\/\/cdn.aigrowthmarketer.co\/1784771022564-85ed1a3833cc.png\" alt=\"AI Growth Agent&#039;s personalization section lets brands add Local Business schema.\" style=\"max-height: 500px;\" loading=\"lazy\" decoding=\"async\"><\/a><figcaption><em>AI Growth Agent&#039;s personalization section lets brands add Local Business schema.<\/em><\/figcaption><\/figure>\n<p><a href=\"https:\/\/aigrowthagent.co\/book-a-demo\/\" target=\"_blank\"><strong>Schedule a consultation session to see if you\u2019re a good fit.<\/strong><\/a><\/p>\n<h2>FAQ<\/h2>\n<h3>How do I select the right North Star metric for my business model?<\/h3>\n<p>A North Star metric must satisfy four criteria. It reflects customer value delivered rather than company activity. It serves as a leading indicator of retention or expansion. It is measurable on a weekly cadence. Every team in the organization can influence it with their work. For SaaS, common choices include consumption metrics such as messages sent or weekly active editors because these track whether users receive the product&#8217;s core promise.<\/p>\n<p>For e-commerce, lifetime-value-adjusted ROAS outperforms flat ROAS because it accounts for repeat purchase behavior over a 6- or 12-month window. For marketplaces, completed transactions or nights booked reflect value delivered to both sides of the platform at the same time. Validate any candidate metric by checking its correlation with 30-, 60-, and 90-day retention in your own cohort data before adopting it as the organizational anchor.<\/p>\n<h3>Why does cohort-based measurement produce more reliable results than blended averages?<\/h3>\n<p>Cohort-based measurement produces more reliable results because it groups users by signup window and tracks them forward in time. Blended averages mix users who signed up at different times, under different acquisition conditions, and with different product experiences. When acquisition volume changes, blended metrics drift even if underlying user behavior stays constant. That drift makes it hard to attribute a shift to a product change versus a change in the mix of new users.<\/p>\n<p>Cohort-based measurement isolates users who signed up in a specific window so activation rate, retention curves, and revenue expansion reflect a consistent population. This structure makes leaks visible. If the Month-3 cohort shows a 15-point retention drop versus the Month-1 cohort, the team can investigate what changed in the product or onboarding during that period instead of averaging the signal away.<\/p>\n<h3>What LTV:CAC benchmarks should growth teams use by company stage?<\/h3>\n<p>The conventional healthy floor for LTV:CAC is 3.0x across operator rules of thumb, with recent benchmarks for horizontal and vertical SaaS noted in the Acquisition section above. The KeyBanc Capital Markets Annual SaaS Survey of 2025, covering over 400 private SaaS companies, found median LTV:CAC of 3.0x for companies under $10M ARR, 3.8x for $10M to $50M ARR, and 4.5x for companies above $50M ARR, with top quartile at 5.0x or above across all sizes.<\/p>\n<p>Teams below 3.0x should prioritize reducing churn and expanding NRR before increasing acquisition spend. Net revenue retention explains more LTV variance than gross margin, ARPU, or initial contract value combined across the public SaaS comp set.<\/p>\n<h3>How should growth teams interpret experimentation win rates?<\/h3>\n<p>Win rate is calculated as experiments producing statistically significant positive results divided by total concluded tests multiplied by 100. A healthy range sits between 20% and 35% as discussed in the Experimentation section. Rates below 20% can indicate that hypotheses are poorly formed, sample sizes are insufficient, or the team is testing in high-noise areas of the product.<\/p>\n<p>Rates above 40% typically indicate the team is only testing safe, obvious ideas rather than ambitious hypotheses that could produce meaningful lifts. Win rate should always be read alongside implementation rate, which tracks the share of winning tests shipped to 100% of users. Raising implementation rate from 60% to 90% produces a larger impact on annual cumulative validated uplift than increasing experiment count by 50%, which makes it the most under-tracked velocity metric in many programs.<\/p>\n<h3>How do I identify whether a metric on my dashboard is a vanity metric?<\/h3>\n<p>Three diagnostic tests help identify vanity metrics. The decision test asks whether a 30% drop in the number would cause the team to take a specific, identifiable action. If the answer requires multiple assumptions to reach a next step, the metric is likely vanity. The denominator test checks whether the metric has a denominator that makes it a rate rather than a cumulative count. Cumulative counts such as total signups, all-time page views, and total followers can only go up over time and provide no signal about the health of a specific funnel stage.<\/p>\n<p>The cohort test asks whether the aggregate number hides cohort-level problems. A rising total registered user count can mask a collapsing activation rate in recent cohorts. Common vanity metrics to remove from growth dashboards include total page views without conversion context, raw follower counts, email open rates post-Apple Mail Privacy Protection, total signups without activation rate, and gross MRR reported without net revenue retention context.<\/p>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/aigrowthagent.co\/articles\/growth-marketing-examples-2026\" target=\"_blank\">12 Growth Marketing Examples SaaS Teams Are Testing in 2026<\/a><\/li>\n<li><a href=\"https:\/\/aigrowthagent.co\/articles\/growth-marketing-best-practices-2026\" target=\"_blank\">The 10-Step Growth Experimentation Engine for 2026<\/a><\/li>\n<li><a href=\"https:\/\/aigrowthagent.co\/articles\/top-growth-marketing-trends-2026\" target=\"_blank\">6 Growth Marketing Trends That Replace Paid Acquisition<\/a><\/li>\n<li><a href=\"https:\/\/aigrowthagent.co\/articles\/top-growth-marketing-channels-2026\" target=\"_blank\">Growth Marketing Channels 2026: Ranked by Speed and ROI<\/a><\/li>\n<li><a href=\"https:\/\/aigrowthagent.co\/articles\/growth-marketing-framework-2026\" target=\"_blank\">Growth Loops, ICE Scoring &amp; AI Visibility in 2026<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Stop guessing with spreadsheets. AI Growth Agent tracks the growth marketing metrics that drive real revenue in 2026. Start measuring smarter today.<\/p>\n","protected":false},"author":1,"featured_media":1976,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-1977","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-wordpress"],"_links":{"self":[{"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/posts\/1977","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/comments?post=1977"}],"version-history":[{"count":3,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/posts\/1977\/revisions"}],"predecessor-version":[{"id":5043,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/posts\/1977\/revisions\/5043"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/media\/1976"}],"wp:attachment":[{"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/media?parent=1977"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/categories?post=1977"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aigrowthagent.co\/articles\/wp-json\/wp\/v2\/tags?post=1977"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}