{"id":7008,"date":"2026-03-23T20:58:24","date_gmt":"2026-03-23T20:58:24","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/analytics-report\/"},"modified":"2026-03-23T20:58:24","modified_gmt":"2026-03-23T20:58:24","slug":"analytics-report","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/analytics-report\/","title":{"rendered":"Analytics Report: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Analytics"},"content":{"rendered":"\n

An Analytics Report<\/strong> is a structured way to translate raw data into insights that teams can act on. In Conversion & Measurement<\/strong>, it\u2019s the bridge between \u201cwhat happened\u201d (traffic, leads, sales) and \u201cwhat we should do next\u201d (optimize pages, adjust targeting, fix tracking, reallocate budget). In Analytics<\/strong>, it\u2019s the artifact that makes analysis repeatable, shareable, and auditable across stakeholders.<\/p>\n\n\n\n

Modern marketing moves fast: channels fragment, customer journeys span devices, and privacy constraints reduce visibility. A well-designed Analytics Report<\/strong> keeps strategy grounded. It helps organizations measure outcomes consistently, spot meaningful changes early, and prove the impact of marketing work in a way finance, product, and leadership can trust.<\/p>\n\n\n\n

What Is Analytics Report?<\/h2>\n\n\n\n

An Analytics Report<\/strong> is a curated summary of metrics, trends, and interpretations built to answer specific business questions. It combines data selection (what to measure), context (benchmarks, time comparisons), and narrative (what it means) to support decisions.<\/p>\n\n\n\n

At its core, an Analytics Report<\/strong> does three jobs:<\/p>\n\n\n\n

    \n
  1. Describes performance<\/strong> (e.g., conversions, revenue, retention, pipeline).<\/li>\n
  2. Diagnoses drivers<\/strong> (e.g., which channel, campaign, audience, or page caused change).<\/li>\n
  3. Guides action<\/strong> (e.g., what to optimize, what to stop, what to scale).<\/li>\n<\/ol>\n\n\n\n

    From a business perspective, it aligns teams on what \u201csuccess\u201d means and whether the organization is progressing toward it. In Conversion & Measurement<\/strong>, the report is where tracking implementation meets outcomes: it validates whether conversions are being captured correctly and whether those conversions are improving over time. Inside Analytics<\/strong>, it\u2019s the standard deliverable that operationalizes measurement\u2014turning analysis into a repeatable business routine.<\/p>\n\n\n\n

    Why Analytics Report Matters in Conversion & Measurement<\/h2>\n\n\n\n

    In Conversion & Measurement<\/strong>, measurement isn\u2019t the goal\u2014improvement is. An Analytics Report<\/strong> matters because it connects marketing activity to business results while reducing ambiguity and internal debate.<\/p>\n\n\n\n

    Key reasons it\u2019s strategically important:<\/p>\n\n\n\n

      \n
    • Budget accountability:<\/strong> It supports decisions about where to invest by showing performance by channel, campaign, audience, and landing experience.<\/li>\n
    • Faster optimization loops:<\/strong> Weekly or daily reporting surfaces issues (tracking drops, conversion-rate declines, creative fatigue) early enough to respond.<\/li>\n
    • Cross-team alignment:<\/strong> It creates a shared source of truth for marketing, sales, product, and leadership\u2014essential when definitions differ (lead vs qualified lead, trial vs activated user).<\/li>\n
    • Competitive advantage:<\/strong> Teams that interpret data quickly can iterate faster, find efficient segments, and scale winners before competitors catch up.<\/li>\n<\/ul>\n\n\n\n

      In short, the Analytics Report<\/strong> is a core operating system for modern Analytics<\/strong> maturity and a cornerstone of effective Conversion & Measurement<\/strong> strategy.<\/p>\n\n\n\n

      How Analytics Report Works<\/h2>\n\n\n\n

      An Analytics Report<\/strong> is less a single format and more a workflow that turns data into decisions. In practice, it follows a repeatable lifecycle:<\/p>\n\n\n\n

        \n
      1. \n

        Input or trigger<\/strong>\n – A reporting cadence (daily\/weekly\/monthly), a campaign launch, a funnel change, or a business question (e.g., \u201cWhy did conversions fall?\u201d).<\/p>\n<\/li>\n

      2. \n

        Analysis or processing<\/strong>\n – Data is collected from analytics and marketing systems, cleaned, and mapped to consistent definitions.\n – Metrics are segmented (by channel, device, location, landing page, audience) to reveal drivers rather than averages.<\/p>\n<\/li>\n

      3. \n

        Execution or application<\/strong>\n – Insights are translated into actions: change targeting, revise creative, fix tagging, improve page speed, adjust offer positioning, refine qualification rules.<\/p>\n<\/li>\n

      4. \n

        Output or outcome<\/strong>\n – Stakeholders receive a clear view of performance and recommended next steps.\n – Follow-up measurement verifies whether changes improved the targeted outcome in Conversion & Measurement<\/strong>.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        A strong Analytics Report<\/strong> doesn\u2019t just show charts\u2014it shows what changed, why it likely changed, and what to do about it.<\/p>\n\n\n\n

        Key Components of Analytics Report<\/h2>\n\n\n\n

        Most high-performing organizations standardize the structure of an Analytics Report<\/strong> so it\u2019s easy to read and hard to misinterpret. Common components include:<\/p>\n\n\n\n

          \n
        • Purpose and audience<\/strong><\/li>\n
        • Executive summary vs operator-level detail; who needs to act on it.<\/li>\n
        • Scope and timeframe<\/strong><\/li>\n
        • Date ranges, comparison periods (WoW, MoM, YoY), and what\u2019s included\/excluded.<\/li>\n
        • Definitions and governance<\/strong><\/li>\n
        • Clear definitions for conversions, attribution logic, \u201cqualified\u201d criteria, and data ownership.<\/li>\n
        • Data inputs<\/strong><\/li>\n
        • Website\/app events, ad platform delivery data, CRM lifecycle stages, ecommerce transactions, email engagement, call tracking, or offline conversions.<\/li>\n
        • Core metrics<\/strong><\/li>\n
        • KPIs tied to objectives (revenue, leads, CAC, activation rate) plus supporting diagnostics (CTR, CVR, bounce rate, funnel step completion).<\/li>\n
        • Segmentation and context<\/strong><\/li>\n
        • Breakdowns that explain variance: channel, campaign, landing page, device, geography, new vs returning users.<\/li>\n
        • Insights and recommendations<\/strong><\/li>\n
        • Observations, likely causes, prioritized actions, and expected impact.<\/li>\n
        • Quality checks<\/strong><\/li>\n
        • Tracking health, missing data warnings, anomaly flags, and annotation of known changes.<\/li>\n<\/ul>\n\n\n\n

          These elements ensure the Analytics Report<\/strong> supports reliable Analytics<\/strong> and avoids \u201cpretty but misleading\u201d reporting.<\/p>\n\n\n\n

          Types of Analytics Report<\/h2>\n\n\n\n

          \u201cType\u201d usually refers to the report\u2019s intent and level of decision-making rather than a rigid taxonomy. Useful distinctions include:<\/p>\n\n\n\n

          By cadence<\/h3>\n\n\n\n
            \n
          • Recurring reports:<\/strong> Weekly\/monthly performance updates for ongoing Conversion & Measurement<\/strong> monitoring.<\/li>\n
          • Ad hoc reports:<\/strong> Built to answer a specific question (e.g., \u201cDid the pricing page change affect sign-ups?\u201d).<\/li>\n<\/ul>\n\n\n\n

            By purpose<\/h3>\n\n\n\n
              \n
            • Performance reports:<\/strong> Focus on KPIs, targets, and trend lines.<\/li>\n
            • Diagnostic reports:<\/strong> Focus on why<\/em> performance changed (funnel analysis, segment shifts, tracking breaks).<\/li>\n
            • Experiment reports:<\/strong> Summarize A\/B tests, holdouts, or incrementality studies.<\/li>\n<\/ul>\n\n\n\n

              By audience level<\/h3>\n\n\n\n
                \n
              • Executive summary:<\/strong> A concise narrative with a few metrics and decisions needed.<\/li>\n
              • Operator report:<\/strong> Channel, campaign, and creative detail for hands-on optimization.<\/li>\n
              • Technical measurement report:<\/strong> Tagging coverage, event volumes, data quality, and taxonomy compliance.<\/li>\n<\/ul>\n\n\n\n

                Choosing the right type keeps Analytics Report<\/strong> outputs aligned to real decisions in Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                Real-World Examples of Analytics Report<\/h2>\n\n\n\n

                1) Ecommerce weekly revenue and funnel report<\/h3>\n\n\n\n

                A retailer builds an Analytics Report<\/strong> that tracks sessions \u2192 product views \u2192 add-to-cart \u2192 checkout \u2192 purchase, segmented by device and channel. The report shows checkout conversion dropped on mobile after a site update, while desktop stayed stable. The Conversion & Measurement<\/strong> action is clear: prioritize mobile checkout debugging and validate event tracking for payment steps within the Analytics<\/strong> setup.<\/p>\n\n\n\n

                2) B2B lead quality and pipeline contribution report<\/h3>\n\n\n\n

                A SaaS company uses an Analytics Report<\/strong> combining marketing-source data with CRM stages. It highlights that one channel delivers many leads but low SQL rate and low pipeline value. Another channel delivers fewer leads but higher progression and faster close velocity. In Conversion & Measurement<\/strong>, the team shifts optimization from \u201cmore leads\u201d to \u201cmore qualified leads\u201d and refines the conversion definitions in Analytics<\/strong> to reflect lifecycle quality.<\/p>\n\n\n\n

                3) Campaign launch performance and creative fatigue report<\/h3>\n\n\n\n

                An agency produces an Analytics Report<\/strong> for a multi-week paid campaign, tracking spend, reach, CTR, CVR, CPA, and post-click behavior by creative set. It identifies rising frequency and declining CTR as early fatigue indicators. The report recommends rotating assets and adjusting targeting. The measurement plan ensures conversions are consistently captured and comparable across weeks\u2014core Conversion & Measurement<\/strong> hygiene.<\/p>\n\n\n\n

                Benefits of Using Analytics Report<\/h2>\n\n\n\n

                A well-run Analytics Report<\/strong> process improves both outcomes and operations:<\/p>\n\n\n\n

                  \n
                • Performance improvements:<\/strong> Faster identification of bottlenecks in acquisition, landing pages, and funnels.<\/li>\n
                • Cost savings:<\/strong> Reduced wasted spend by cutting underperforming segments and reallocating budget based on evidence.<\/li>\n
                • Efficiency gains:<\/strong> Less time debating numbers and more time executing changes; standardized reporting reduces ad hoc requests.<\/li>\n
                • Better customer experience:<\/strong> Insight into friction points (slow pages, confusing forms, poor mobile UX) leads to smoother journeys and higher conversion rates.<\/li>\n
                • Stronger organizational trust in data:<\/strong> Consistent definitions and governance elevate Analytics<\/strong> credibility across teams.<\/li>\n<\/ul>\n\n\n\n

                  Challenges of Analytics Report<\/h2>\n\n\n\n

                  Even experienced teams struggle to make an Analytics Report<\/strong> consistently reliable and decision-ready. Common challenges include:<\/p>\n\n\n\n

                    \n
                  • Data quality and tracking gaps:<\/strong> Missing events, duplicated conversions, bot traffic, or broken UTM\/tagging can distort results.<\/li>\n
                  • Attribution limitations:<\/strong> Multi-touch journeys, walled gardens, and privacy constraints mean no single model is \u201cthe truth.\u201d<\/li>\n
                  • Metric overload:<\/strong> Too many charts dilute focus; stakeholders stop reading.<\/li>\n
                  • Misaligned definitions:<\/strong> Marketing, sales, and finance may define \u201cconversion\u201d differently, undermining Conversion & Measurement<\/strong> clarity.<\/li>\n
                  • Change management:<\/strong> Site releases, campaign changes, and tracking updates can shift numbers; without annotations, trends get misread.<\/li>\n
                  • Reporting without action:<\/strong> If a report doesn\u2019t drive decisions, it becomes a routine artifact rather than an Analytics<\/strong> lever.<\/li>\n<\/ul>\n\n\n\n

                    Best Practices for Analytics Report<\/h2>\n\n\n\n

                    To keep an Analytics Report<\/strong> actionable and trusted, focus on design, governance, and decision flow:<\/p>\n\n\n\n

                      \n
                    • Start with decisions, not metrics<\/strong><\/li>\n
                    • Define what actions the report should enable (budget shifts, CRO priorities, creative rotation).<\/li>\n
                    • Use a KPI hierarchy<\/strong><\/li>\n
                    • One primary KPI, a small set of secondary KPIs, and diagnostic metrics that explain movement.<\/li>\n
                    • Standardize definitions and document them<\/strong><\/li>\n
                    • Clarify conversions, deduplication logic, and lifecycle stages; align stakeholders in Conversion & Measurement<\/strong> meetings.<\/li>\n
                    • Add context, not commentary<\/strong><\/li>\n
                    • Include targets, benchmarks, and comparisons; label known changes (campaign launches, tracking updates, outages).<\/li>\n
                    • Segment intelligently<\/strong><\/li>\n
                    • Segment by what teams can act on: channel, campaign, landing page, device, audience, geography.<\/li>\n
                    • Build in data QA<\/strong><\/li>\n
                    • Track event volumes, conversion rates by source, and anomaly detection to protect Analytics<\/strong> integrity.<\/li>\n
                    • Tie insights to next steps<\/strong><\/li>\n
                    • Each key insight should have an owner, a recommended action, and a timeline for validation.<\/li>\n<\/ul>\n\n\n\n

                      Tools Used for Analytics Report<\/h2>\n\n\n\n

                      An Analytics Report<\/strong> typically sits at the intersection of multiple systems. In Conversion & Measurement<\/strong> and Analytics<\/strong>, common tool categories include:<\/p>\n\n\n\n

                        \n
                      • Analytics tools<\/strong><\/li>\n
                      • Web\/app analytics platforms that collect events, sessions, and user behavior.<\/li>\n
                      • Tag management and measurement infrastructure<\/strong><\/li>\n
                      • Systems that manage tracking tags, event schemas, and consent-driven firing rules.<\/li>\n
                      • Reporting dashboards and BI<\/strong><\/li>\n
                      • Tools that combine data sources, create repeatable views, and support drill-down analysis.<\/li>\n
                      • Ad platforms<\/strong><\/li>\n
                      • Delivery, spend, clicks, and platform conversions\u2014useful for reconciliation and optimization.<\/li>\n
                      • CRM and marketing automation<\/strong><\/li>\n
                      • Lead stages, pipeline, revenue, and lifecycle attribution\u2014critical for B2B Conversion & Measurement<\/strong>.<\/li>\n
                      • Data warehouses and ETL\/ELT<\/strong><\/li>\n
                      • Centralize and model data for consistent definitions across channels.<\/li>\n
                      • SEO tools<\/strong><\/li>\n
                      • Search visibility and query insights that support acquisition reporting and content performance analysis.<\/li>\n<\/ul>\n\n\n\n

                        The best stack is the one that produces consistent definitions, reliable refresh cycles, and clear ownership\u2014not the one with the most features.<\/p>\n\n\n\n

                        Metrics Related to Analytics Report<\/h2>\n\n\n\n

                        The right metrics depend on your objective, but most Analytics Report<\/strong> frameworks use a mix of outcome and diagnostic indicators:<\/p>\n\n\n\n

                          \n
                        • Conversion metrics<\/strong><\/li>\n
                        • Conversion rate (CVR), leads, purchases, sign-ups, activation rate, checkout completion rate.<\/li>\n
                        • Revenue and ROI metrics<\/strong><\/li>\n
                        • Revenue, average order value (AOV), customer lifetime value (LTV), ROI\/ROAS, margin-adjusted return where possible.<\/li>\n
                        • Efficiency metrics<\/strong><\/li>\n
                        • Cost per acquisition (CPA), cost per lead (CPL), CAC, payback period, funnel drop-off by step.<\/li>\n
                        • Engagement and behavior metrics<\/strong><\/li>\n
                        • Bounce rate\/engaged sessions, time on site, scroll depth, repeat visits, content consumption.<\/li>\n
                        • Quality metrics (especially for B2B)<\/strong><\/li>\n
                        • MQL-to-SQL rate, SQL-to-close rate, pipeline per lead, win rate by source.<\/li>\n
                        • Measurement health metrics<\/strong><\/li>\n
                        • Event match rate, deduplication rate, offline conversion match rate, consent opt-in rates.<\/li>\n<\/ul>\n\n\n\n

                          A strong Analytics Report<\/strong> connects these metrics to a narrative that supports Conversion & Measurement<\/strong> decisions.<\/p>\n\n\n\n

                          Future Trends of Analytics Report<\/h2>\n\n\n\n

                          The Analytics Report<\/strong> is evolving as measurement becomes more automated and more constrained at the same time:<\/p>\n\n\n\n

                            \n
                          • AI-assisted analysis<\/strong><\/li>\n
                          • Automated anomaly detection, narrative summaries, and root-cause suggestions will reduce manual slicing, but still require human validation.<\/li>\n
                          • More automation in reporting operations<\/strong><\/li>\n
                          • Scheduled refreshes, alerts, and stakeholder-specific views will replace static monthly slide decks for many teams.<\/li>\n
                          • Privacy-driven measurement changes<\/strong><\/li>\n
                          • Increased reliance on first-party data, modeled conversions, and aggregate reporting will shape how Analytics<\/strong> is interpreted.<\/li>\n
                          • Experimentation and incrementality<\/strong><\/li>\n
                          • More organizations will add holdouts and lift measurement to complement attribution, strengthening Conversion & Measurement<\/strong> confidence.<\/li>\n
                          • Personalization measurement<\/strong><\/li>\n
                          • As experiences become tailored, reporting must track outcomes by cohort, audience rules, and content variants\u2014without creating fragmented definitions.<\/li>\n<\/ul>\n\n\n\n

                            Future-ready teams treat the Analytics Report<\/strong> as a product: versioned, governed, and continuously improved.<\/p>\n\n\n\n

                            Analytics Report vs Related Terms<\/h2>\n\n\n\n

                            Understanding nearby concepts helps you set expectations and choose the right deliverable:<\/p>\n\n\n\n

                              \n
                            • Analytics Report vs dashboard<\/strong><\/li>\n
                            • A dashboard is often a live view of metrics. An Analytics Report<\/strong> typically adds interpretation, context, and recommendations, even if delivered in a dashboard format.<\/li>\n
                            • Analytics Report vs KPI report<\/strong><\/li>\n
                            • A KPI report focuses on a small set of top metrics and targets. An Analytics Report<\/strong> usually includes diagnostic detail to explain why<\/em> KPIs moved and what to do next.<\/li>\n
                            • Analytics Report vs attribution report<\/strong><\/li>\n
                            • An attribution report focuses on credit assignment across channels\/touchpoints. An Analytics Report<\/strong> may include attribution, but also covers on-site behavior, funnel steps, and measurement health\u2014broader Conversion & Measurement<\/strong> scope.<\/li>\n<\/ul>\n\n\n\n

                              Who Should Learn Analytics Report<\/h2>\n\n\n\n

                              An Analytics Report<\/strong> skill set pays off across roles:<\/p>\n\n\n\n

                                \n
                              • Marketers:<\/strong> Make better channel and creative decisions, align work to measurable outcomes, and communicate results clearly.<\/li>\n
                              • Analysts:<\/strong> Build trusted reporting systems, enforce definitions, and turn Analytics<\/strong> into decision support instead of data delivery.<\/li>\n
                              • Agencies:<\/strong> Prove value, reduce churn risk, and run optimization programs tied to client revenue and leads.<\/li>\n
                              • Business owners and founders:<\/strong> Understand growth drivers, forecast performance, and avoid \u201cvanity metrics\u201d traps in Conversion & Measurement<\/strong>.<\/li>\n
                              • Developers and technical teams:<\/strong> Implement cleaner event tracking, improve data reliability, and reduce reporting disputes caused by instrumentation issues.<\/li>\n<\/ul>\n\n\n\n

                                Summary of Analytics Report<\/h2>\n\n\n\n

                                An Analytics Report<\/strong> is a structured, decision-oriented summary of performance and insights. It matters because it turns Analytics<\/strong> into action: diagnosing what\u2019s driving results and guiding optimization. In Conversion & Measurement<\/strong>, it\u2019s essential for validating tracking, monitoring funnels, and improving the metrics that matter\u2014revenue, leads, and customer growth.<\/p>\n\n\n\n

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

                                1) What should an Analytics Report include to be actionable?<\/h3>\n\n\n\n

                                It should include a clear objective, a small KPI set, context (targets and comparisons), segmentation that explains changes, and specific recommendations with owners and timelines.<\/p>\n\n\n\n

                                2) How often should I produce an Analytics Report?<\/h3>\n\n\n\n

                                Use cadence based on decision speed: weekly for active campaigns and funnel optimization, monthly for executive performance review, and ad hoc for investigations or launches.<\/p>\n\n\n\n

                                3) What\u2019s the difference between Analytics and reporting?<\/h3>\n\n\n\n

                                Analytics<\/strong> is the process of interpreting data to understand causes and predict outcomes. Reporting is the structured communication of those findings. A strong Analytics Report<\/strong> combines both.<\/p>\n\n\n\n

                                4) How do I choose KPIs for Conversion & Measurement reporting?<\/h3>\n\n\n\n

                                Start from business goals (revenue, pipeline, retention), map them to conversions and funnel stages, then select supporting metrics that explain movement (traffic quality, CVR, CPA, step drop-off).<\/p>\n\n\n\n

                                5) How do I prevent stakeholders from misreading an Analytics Report?<\/h3>\n\n\n\n

                                Standardize definitions, annotate major changes, show comparisons and confidence limits when relevant, and include a short \u201cwhat changed \/ why \/ next steps\u201d narrative.<\/p>\n\n\n\n

                                6) Can an Analytics Report work with incomplete attribution?<\/h3>\n\n\n\n

                                Yes. Use triangulation: combine platform data, on-site behavior, CRM outcomes, and experiment\/lift studies where possible. Be explicit about limitations so Conversion & Measurement<\/strong> decisions remain realistic.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                An **Analytics Report** is a structured way to translate raw data into insights that teams can act on. In **Conversion & Measurement**, it\u2019s the bridge between \u201cwhat happened\u201d (traffic, leads, sales) and \u201cwhat we should do next\u201d (optimize pages, adjust targeting, fix tracking, reallocate budget). In **Analytics**, it\u2019s the artifact that makes analysis repeatable, shareable, and auditable across stakeholders.<\/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":[1887],"tags":[],"class_list":["post-7008","post","type-post","status-publish","format-standard","hentry","category-analytics"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7008","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=7008"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7008\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7008"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7008"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7008"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}