{"id":7128,"date":"2026-03-24T01:19:43","date_gmt":"2026-03-24T01:19:43","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/cta-test\/"},"modified":"2026-03-24T01:19:43","modified_gmt":"2026-03-24T01:19:43","slug":"cta-test","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/cta-test\/","title":{"rendered":"Cta Test: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRO"},"content":{"rendered":"\n

A Cta Test<\/strong> is a structured way to evaluate which call-to-action (CTA) drives better user behavior\u2014such as clicks, sign-ups, purchases, or qualified leads\u2014using measurable evidence rather than opinion. In Conversion & Measurement<\/strong>, it\u2019s a focused experiment that connects what people see<\/em> (CTA copy, design, placement) to what people do<\/em> (conversion events). In CRO<\/strong>, it\u2019s one of the highest-leverage testing activities because small changes to a CTA can meaningfully affect revenue, pipeline, and customer acquisition efficiency.<\/p>\n\n\n\n

Modern teams can\u2019t rely on \u201cbest practices\u201d alone. Audiences vary by intent, device, channel, and trust level. A well-designed Cta Test<\/strong> helps you learn what works for your<\/em> users, with your<\/em> offer, under your<\/em> constraints\u2014while keeping decisions grounded in Conversion & Measurement<\/strong> discipline and aligned with broader CRO<\/strong> goals.<\/p>\n\n\n\n

What Is Cta Test?<\/h2>\n\n\n\n

A Cta Test<\/strong> is an experiment that compares two or more CTA variants to determine which version produces better outcomes against a defined success metric. The CTA may be a button (for example, \u201cStart free trial\u201d), a text link, a form submit label, an in-app prompt, or a spoken\/visual prompt in other channels\u2014anything that asks the user to take the next step.<\/p>\n\n\n\n

The core concept is simple: change one or more CTA attributes and observe whether user behavior improves in a statistically credible way. The business meaning is not \u201cwhich button looks better,\u201d but \u201cwhich CTA reduces friction and increases the rate of meaningful conversions.\u201d<\/p>\n\n\n\n

In Conversion & Measurement<\/strong>, a Cta Test<\/strong> sits at the intersection of instrumentation (tracking CTA interactions correctly) and evaluation (attributing downstream impact like sign-ups, revenue, or lead quality). Within CRO<\/strong>, it\u2019s a tactical testing method used to improve funnel performance, landing pages, product pages, emails, and in-product onboarding flows.<\/p>\n\n\n\n

Why Cta Test Matters in Conversion & Measurement<\/h2>\n\n\n\n

A Cta Test<\/strong> matters because CTAs are often the final nudge between interest and action. If your CTA is unclear, misaligned with intent, or placed at the wrong moment, users hesitate\u2014even when everything else is strong.<\/p>\n\n\n\n

From a Conversion & Measurement<\/strong> perspective, CTA testing creates a clear cause-and-effect learning loop: a change is made, behavior is measured, and decisions improve. This is especially valuable when multiple stakeholders have conflicting opinions about copy, design, or brand tone.<\/p>\n\n\n\n

In CRO<\/strong>, the strategic value is compounding. Winning CTA improvements can raise conversion rate, reduce paid media waste, increase email program yield, and improve the efficiency of sales-assisted funnels. Over time, systematic Cta Test<\/strong> programs create a competitive advantage: faster learning, better user understanding, and more predictable growth.<\/p>\n\n\n\n

How Cta Test Works<\/h2>\n\n\n\n

In practice, Cta Test<\/strong> follows a disciplined workflow that fits naturally into Conversion & Measurement<\/strong> and CRO<\/strong> operations:<\/p>\n\n\n\n

    \n
  1. \n

    Input \/ trigger (hypothesis and context)<\/strong>\n You start with a reason to test: analytics show low click-through on a key button, heatmaps suggest the CTA is ignored, user research reveals confusing language, or a new offer is being launched. You convert this into a hypothesis such as: \u201cIf we make the CTA more specific, more users will complete checkout.\u201d<\/p>\n<\/li>\n

  2. \n

    Analysis \/ planning (measurement and design)<\/strong>\n Define primary and secondary metrics, the audience segment, and the test design (A\/B, multivariate, etc.). Confirm tracking is correct: CTA clicks, form submissions, purchases, and any micro-conversions should be consistently captured. This step is where Conversion & Measurement<\/strong> rigor prevents misleading results.<\/p>\n<\/li>\n

  3. \n

    Execution \/ application (run the experiment)<\/strong>\n Launch variants and ensure traffic allocation is correct. Monitor for technical issues (broken links, inconsistent UI, slow load times). In CRO<\/strong>, good execution includes ensuring the experiment doesn\u2019t degrade user experience or introduce bias across devices and browsers.<\/p>\n<\/li>\n

  4. \n

    Output \/ outcome (interpretation and rollout)<\/strong>\n Evaluate results for statistical credibility and practical impact. A lift in clicks is not always a win if downstream conversions or lead quality drop. A mature Cta Test<\/strong> practice assesses the full funnel, not just the button.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

    Key Components of Cta Test<\/h2>\n\n\n\n

    A reliable Cta Test<\/strong> program depends on several components that support trustworthy Conversion & Measurement<\/strong> and consistent CRO<\/strong> execution:<\/p>\n\n\n\n

      \n
    • Clear hypotheses and decision rules<\/strong>: Define what \u201cwin\u201d means before launching (for example, \u201cIncrease completed purchases per session by 3% with no drop in AOV\u201d).<\/li>\n
    • CTA variables to test<\/strong>: Copy (specific vs generic), value framing (benefit vs feature), urgency, risk reduction (\u201cCancel anytime\u201d), design (color, size, icon), placement, and surrounding context (supporting text, trust signals).<\/li>\n
    • Experiment design and traffic allocation<\/strong>: A\/B testing is common, but the right design depends on traffic, number of variants, and risk tolerance.<\/li>\n
    • Instrumentation and event tracking<\/strong>: Click events, form submissions, step completion, revenue, and qualified lead events must be accurately captured and consistently named.<\/li>\n
    • Segmentation<\/strong>: New vs returning users, mobile vs desktop, paid vs organic, high-intent vs low-intent, and geography can change what CTA works best.<\/li>\n
    • Governance and roles<\/strong>: Product\/engineering for implementation, analytics for measurement, marketing for messaging, and a shared testing backlog for CRO<\/strong> prioritization.<\/li>\n<\/ul>\n\n\n\n

      Types of Cta Test<\/h2>\n\n\n\n

      \u201cTypes\u201d of Cta Test<\/strong> are usually best understood as testing approaches and contexts rather than rigid categories:<\/p>\n\n\n\n

      A\/B CTA testing<\/h3>\n\n\n\n

      Compares one CTA variant to another (for example, \u201cGet a demo\u201d vs \u201cTalk to an expert\u201d). This is the most common approach in CRO<\/strong> because it\u2019s easier to interpret and often faster to reach reliable Conversion & Measurement<\/strong> conclusions.<\/p>\n\n\n\n

      Multivariate CTA testing<\/h3>\n\n\n\n

      Tests combinations of CTA elements (copy + color + placement) at once. It can uncover interactions but typically requires much more traffic to achieve clarity.<\/p>\n\n\n\n

      Sequential testing (iteration-based)<\/h3>\n\n\n\n

      Runs a series of tests over time, learning from each result. This is often the most practical approach for smaller sites because it balances learning with sample-size realities.<\/p>\n\n\n\n

      Contextual\/personalized CTA testing<\/h3>\n\n\n\n

      Shows different CTAs to different segments (for example, returning users see \u201cContinue your trial\u201d while new users see \u201cStart free trial\u201d). This can be powerful but increases measurement complexity in Conversion & Measurement<\/strong> and requires careful governance in CRO<\/strong>.<\/p>\n\n\n\n

      Channel-specific CTA testing<\/h3>\n\n\n\n

      CTAs behave differently in emails, landing pages, ads, and in-product prompts. A Cta Test<\/strong> should account for channel constraints and user intent at that moment.<\/p>\n\n\n\n

      Real-World Examples of Cta Test<\/h2>\n\n\n\n

      Example 1: E-commerce product page CTA clarity<\/h3>\n\n\n\n

      A retailer sees strong product page traffic but modest add-to-cart rates. They run a Cta Test<\/strong> comparing:\n– Variant A: \u201cAdd to cart\u201d\n– Variant B: \u201cAdd to cart \u2014 Ships today\u201d<\/p>\n\n\n\n

      They measure add-to-cart rate and completed purchases. Conversion & Measurement<\/strong> analysis shows Variant B increases add-to-cart clicks but also slightly increases checkout completion because it sets a shipping expectation earlier. In CRO<\/strong>, this is a strong win because it improves both micro- and macro-conversions.<\/p>\n\n\n\n

      Example 2: SaaS pricing page CTA alignment with intent<\/h3>\n\n\n\n

      A SaaS company tests the primary pricing CTA:\n– Variant A: \u201cStart free trial\u201d\n– Variant B: \u201cSee plans and pricing\u201d<\/p>\n\n\n\n

      For high-intent users, \u201cStart free trial\u201d may convert better. For comparison shoppers, \u201cSee plans and pricing\u201d may reduce anxiety. The Cta Test<\/strong> reveals mobile users convert better with the clarity of Variant B, while desktop users perform similarly. The team uses segmentation to guide a rollout that improves overall Conversion & Measurement<\/strong> outcomes without harming brand trust\u2014classic CRO<\/strong> decision-making.<\/p>\n\n\n\n

      Example 3: Lead-gen form submission friction<\/h3>\n\n\n\n

      A B2B site tests the form submit button:\n– Variant A: \u201cSubmit\u201d\n– Variant B: \u201cGet my ROI estimate\u201d<\/p>\n\n\n\n

      They track form completion rate and downstream lead qualification. The Cta Test<\/strong> shows higher completion on Variant B, but the big insight is improved lead quality because the CTA pre-frames value and filters casual clicks. This ties directly to Conversion & Measurement<\/strong> goals (quality, not just volume) and supports CRO<\/strong> outcomes across the funnel.<\/p>\n\n\n\n

      Benefits of Using Cta Test<\/h2>\n\n\n\n

      A disciplined Cta Test<\/strong> practice can deliver benefits that extend beyond button clicks:<\/p>\n\n\n\n

        \n
      • Higher conversion rates<\/strong>: Clearer CTAs reduce hesitation and improve completion rates on key steps.<\/li>\n
      • Lower acquisition costs<\/strong>: Better on-site conversion efficiency reduces wasted ad spend and can improve paid media ROI.<\/li>\n
      • Faster learning cycles<\/strong>: Instead of debating subjective preferences, teams use measured evidence\u2014an essential Conversion & Measurement<\/strong> advantage.<\/li>\n
      • Better user experience<\/strong>: Strong CTAs make next steps obvious, reducing confusion and decision fatigue.<\/li>\n
      • Improved message-market fit<\/strong>: CTA performance often reveals which value propositions resonate, feeding broader CRO<\/strong> and messaging strategy.<\/li>\n<\/ul>\n\n\n\n

        Challenges of Cta Test<\/h2>\n\n\n\n

        Even though Cta Test<\/strong> seems straightforward, pitfalls are common:<\/p>\n\n\n\n

          \n
        • Low sample size and false confidence<\/strong>: Small traffic sites can\u2019t reliably detect small lifts, which can lead to overreacting to noise\u2014an ongoing Conversion & Measurement<\/strong> challenge.<\/li>\n
        • Measuring the wrong \u201cwin\u201d<\/strong>: Optimizing for clicks can backfire if downstream conversions, revenue, or lead quality decline.<\/li>\n
        • Implementation complexity<\/strong>: On some stacks, client-side testing can cause flicker, performance issues, or inconsistent experiences across devices\u2014hurting both UX and CRO<\/strong> results.<\/li>\n
        • Confounding changes<\/strong>: Launching pricing updates, campaigns, or site redesigns during a Cta Test<\/strong> can contaminate results.<\/li>\n
        • Brand and compliance constraints<\/strong>: Some industries must follow strict language rules; CTA creativity must stay within policy boundaries.<\/li>\n<\/ul>\n\n\n\n

          Best Practices for Cta Test<\/h2>\n\n\n\n

          To make Cta Test<\/strong> a reliable part of Conversion & Measurement<\/strong> and CRO<\/strong>, focus on execution quality:<\/p>\n\n\n\n

            \n
          • Start with user intent<\/strong>: Match the CTA to where the user is in the journey. Early-stage visitors may prefer \u201cLearn more,\u201d while high-intent visitors want \u201cBuy now\u201d or \u201cStart checkout.\u201d<\/li>\n
          • Test one clear idea at a time<\/strong>: Especially in A\/B testing, isolate the main change so you can attribute outcomes.<\/li>\n
          • Define primary and guardrail metrics<\/strong>: Use a primary conversion metric (purchase, sign-up, qualified lead) and guardrails (bounce rate, refund rate, unsubscribe rate, lead quality) to prevent harmful wins.<\/li>\n
          • Ensure tracking and attribution are consistent<\/strong>: A Cta Test<\/strong> is only as good as the events and funnels you measure. Validate events across browsers and devices.<\/li>\n
          • Run tests long enough<\/strong>: Cover typical weekly cycles and avoid calling winners based on short-term spikes.<\/li>\n
          • Document learnings in a testing library<\/strong>: Record hypothesis, variants, audience, results, and interpretation so future CRO<\/strong> work compounds rather than repeats mistakes.<\/li>\n
          • Roll out thoughtfully<\/strong>: Consider phased rollouts for high-risk pages and verify performance after shipping (post-test monitoring is part of Conversion & Measurement<\/strong>, too).<\/li>\n<\/ul>\n\n\n\n

            Tools Used for Cta Test<\/h2>\n\n\n\n

            A Cta Test<\/strong> is supported by tool categories rather than any single platform. In Conversion & Measurement<\/strong> and CRO<\/strong>, common tool groups include:<\/p>\n\n\n\n

              \n
            • Experimentation and feature management systems<\/strong>: To create variants, control traffic allocation, and manage rollouts.<\/li>\n
            • Analytics tools<\/strong>: To analyze funnels, segments, cohorts, and attribution paths tied to CTA interactions.<\/li>\n
            • Tag management and event instrumentation<\/strong>: To standardize tracking and reduce engineering friction for measurement updates.<\/li>\n
            • Session replay, heatmaps, and on-page behavior tools<\/strong>: To diagnose why users ignore CTAs or abandon steps.<\/li>\n
            • CRM and marketing automation systems<\/strong>: Essential when a CTA leads to leads or lifecycle actions; they help measure quality, pipeline, and retention beyond the initial click.<\/li>\n
            • Reporting dashboards and BI<\/strong>: To combine experiment results with revenue, margin, and cohort health\u2014strengthening Conversion & Measurement<\/strong> insights for CRO<\/strong> decisions.<\/li>\n<\/ul>\n\n\n\n

              Metrics Related to Cta Test<\/h2>\n\n\n\n

              A strong Cta Test<\/strong> uses metrics that reflect both immediate behavior and business impact:<\/p>\n\n\n\n

                \n
              • CTA click-through rate (CTR)<\/strong>: Useful, but rarely sufficient alone.<\/li>\n
              • Conversion rate (CVR)<\/strong>: Purchases, sign-ups, demo requests, or completed key actions per session\/user.<\/li>\n
              • Micro-conversions<\/strong>: Add-to-cart, \u201cbegin checkout,\u201d form step completion, account creation, email confirmation.<\/li>\n
              • Revenue per visitor (RPV)<\/strong> and average order value (AOV)<\/strong>: Critical for e-commerce-focused Conversion & Measurement<\/strong>.<\/li>\n
              • Lead quality indicators<\/strong>: Qualified lead rate, sales acceptance rate, opportunity creation\u2014vital for B2B CRO<\/strong>.<\/li>\n
              • Downstream retention signals<\/strong>: Trial-to-paid conversion, churn rate, activation rate (when relevant).<\/li>\n
              • Statistical metrics<\/strong>: Confidence\/credibility, effect size, and sample size\u2014so results are not just \u201cgreen arrows.\u201d<\/li>\n<\/ul>\n\n\n\n

                Future Trends of Cta Test<\/h2>\n\n\n\n

                Cta Test<\/strong> is evolving alongside changes in Conversion & Measurement<\/strong> expectations and CRO<\/strong> technology:<\/p>\n\n\n\n

                  \n
                • AI-assisted variant generation<\/strong>: Teams increasingly use AI to propose CTA copy variants, but disciplined testing is still needed to validate impact and avoid off-brand language.<\/li>\n
                • Automation and adaptive experimentation<\/strong>: Bandit-style allocation and faster iteration loops can reduce time-to-learning, especially for high-traffic funnels.<\/li>\n
                • Deeper personalization<\/strong>: CTAs tailored by intent signals (returning status, content consumed, account stage) will grow\u2014raising the bar for measurement design in Conversion & Measurement<\/strong>.<\/li>\n
                • Privacy-driven measurement constraints<\/strong>: As tracking becomes more restricted, first-party data strategies and server-side measurement become more important for credible Cta Test<\/strong> evaluation.<\/li>\n
                • Cross-channel experimentation<\/strong>: More teams will connect on-site CTAs with email, ads, and in-product prompts to optimize the full journey, not isolated pages\u2014an expanded CRO<\/strong> approach.<\/li>\n<\/ul>\n\n\n\n

                  Cta Test vs Related Terms<\/h2>\n\n\n\n

                  Cta Test vs A\/B testing<\/h3>\n\n\n\n

                  A\/B testing is the broader method; Cta Test<\/strong> is a specific application of A\/B testing focused on CTA elements. You can A\/B test headlines, layouts, pricing, or onboarding flows\u2014CTA is just one high-impact area within CRO<\/strong>.<\/p>\n\n\n\n

                  Cta Test vs Landing page test<\/h3>\n\n\n\n

                  A landing page test may change multiple page components (hero, proof, layout, imagery). A Cta Test<\/strong> is narrower and often aims to isolate CTA effects to produce cleaner Conversion & Measurement<\/strong> conclusions.<\/p>\n\n\n\n

                  Cta Test vs Copy testing<\/h3>\n\n\n\n

                  Copy testing can evaluate messaging across many touchpoints (headlines, body copy, emails, ads). Cta Test<\/strong> focuses specifically on action-oriented microcopy and interaction prompts, ideally measured through conversions rather than preference surveys.<\/p>\n\n\n\n

                  Who Should Learn Cta Test<\/h2>\n\n\n\n
                    \n
                  • Marketers<\/strong> benefit because CTAs sit at the heart of campaign performance, and Cta Test<\/strong> turns creative choices into measurable growth.<\/li>\n
                  • Analysts<\/strong> need it to connect user behavior to outcomes, design experiments properly, and strengthen Conversion & Measurement<\/strong> integrity.<\/li>\n
                  • Agencies<\/strong> use Cta Test<\/strong> to demonstrate impact, prioritize work, and build repeatable CRO<\/strong> playbooks across clients.<\/li>\n
                  • Business owners and founders<\/strong> gain a practical lever for improving acquisition efficiency without immediately increasing spend.<\/li>\n
                  • Developers<\/strong> play a key role in implementing experiments cleanly, ensuring performance, and maintaining trustworthy measurement pipelines for Conversion & Measurement<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                    Summary of Cta Test<\/h2>\n\n\n\n

                    A Cta Test<\/strong> is an experiment that determines which call-to-action drives better user outcomes based on measured behavior. It matters because CTAs influence the moment of decision, and even small improvements can compound across acquisition channels. In Conversion & Measurement<\/strong>, it provides a disciplined framework for tracking, evaluating, and learning from CTA changes. In CRO<\/strong>, it\u2019s a foundational practice for improving funnels, increasing revenue, and reducing wasted traffic.<\/p>\n\n\n\n

                    Frequently Asked Questions (FAQ)<\/h2>\n\n\n\n

                    1) What is a Cta Test and what should it measure?<\/h3>\n\n\n\n

                    A Cta Test<\/strong> compares CTA variants to see which one improves a defined outcome. It should measure a primary business metric (purchase, sign-up, qualified lead) and supporting metrics like CTA CTR and funnel progression, so you don\u2019t optimize clicks at the expense of real results.<\/p>\n\n\n\n

                    2) How long should a Cta Test run?<\/h3>\n\n\n\n

                    Long enough to capture normal traffic cycles and reach a reliable sample size. Many teams aim to cover at least one full business cycle (often a week) and avoid ending early due to short-term spikes.<\/p>\n\n\n\n

                    3) Should I test CTA color or CTA copy first?<\/h3>\n\n\n\n

                    In most cases, test copy and clarity<\/strong> first because it changes meaning and reduces uncertainty. Visual design can matter, but wording often has a more direct connection to intent and value in Conversion & Measurement<\/strong> outcomes.<\/p>\n\n\n\n

                    4) What\u2019s a good primary metric for CRO-focused CTA testing?<\/h3>\n\n\n\n

                    For CRO<\/strong>, the best primary metric is usually the deepest, most meaningful conversion you can measure reliably (completed checkout, activated trial, qualified lead), with guardrails to ensure experience and quality don\u2019t degrade.<\/p>\n\n\n\n

                    5) Can a Cta Test hurt performance?<\/h3>\n\n\n\n

                    Yes. A misleading or overly aggressive CTA can increase clicks but reduce trust, increase refunds, lower lead quality, or raise churn. That\u2019s why Conversion & Measurement<\/strong> guardrails and post-rollout monitoring are essential.<\/p>\n\n\n\n

                    6) How do I interpret mixed results (more clicks but fewer conversions)?<\/h3>\n\n\n\n

                    Treat clicks as a micro-conversion and prioritize the business outcome. Mixed results often indicate a mismatch between the CTA promise and the next-step experience (landing page, form, pricing). In CRO<\/strong>, the fix may be aligning the CTA with what users actually get next.<\/p>\n\n\n\n

                    7) What if my site doesn\u2019t have enough traffic for a Cta Test?<\/h3>\n\n\n\n

                    Use higher-signal qualitative inputs (user testing, session replays) to form stronger hypotheses, test bigger changes (larger expected effect), or focus on high-traffic steps first. You can also iterate sequentially and measure over longer periods, while keeping Conversion & Measurement<\/strong> definitions consistent.<\/p>\n","protected":false},"excerpt":{"rendered":"

                    A **Cta Test** is a structured way to evaluate which call-to-action (CTA) drives better user behavior\u2014such as clicks, sign-ups, purchases, or qualified leads\u2014using measurable evidence rather than opinion. In **Conversion & Measurement**, it\u2019s a focused experiment that connects what people *see* (CTA copy, design, placement) to what people *do* (conversion events). In **CRO**, it\u2019s one of the highest-leverage testing activities because small changes to a CTA can meaningfully affect revenue, pipeline, and customer acquisition efficiency.<\/p>\n","protected":false},"author":10235,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1889],"tags":[],"class_list":["post-7128","post","type-post","status-publish","format-standard","hentry","category-cro"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7128","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/users\/10235"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/comments?post=7128"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7128\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7128"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7128"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7128"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}